Assessment prepared in accordance with the methodological specifications of the Digital Sovereignty Index (DSI v2.0), under the academic cooperation framework of the Global South Academic Forum.

Chapter 1 — Executive Summary

Argentina exhibits a paradoxical pattern of digital sovereignty: a regulatory scaffolding and a software-engineering capability that are comparatively sophisticated for the region coexist with a deep structural dependence on infrastructure, institutional enforcement capacity and capability autonomy — all of it cross-cut by a trajectory of active deregulation that operates as a ceiling factor during the assessment period (2024–2026, Milei administration). The country knows how to legislate on data, and to export software services, but it does not capture the economic value of its data, it does not enforce with deterrent effect, and, in the cross-border flow, it has ceded sovereignty through the adequacy commitment with the United States. The result is a mid-to-low-grade digital sovereignty, without a single indicator reaching the competence level (Level 4), and with two indicators collapsed to the initial level (Level 1).

On the DSI framework’s 1–5 scale, Argentina obtains a sovereignty score of 2.00 / 5.0 (a total of 32 out of 80). The score is computed as the arithmetic mean of the sixteen indicator ratings; no indicator exceeds Level 3. The distribution by dimension reveals that the weakness is concentrated in data ownership.

Table 1.1. Indicator ratings (UNGS_2026 corpus).

Table 1.2. Averages by dimension.

Three principal strengths. First, a mature and long-standing data-protection framework: Law No. 25326 (Personal Data Protection Act), enacted in 2000, has been in continuous force, operated by a functional enforcement authority, and Argentina has retained the European Union’s adequacy status since 2003 ¹ — indicator 1.1 is the only one in the entire matrix that reaches Level 3 on its own legislative merit. Second, a software industry of international scale: revenue of USD 22,221 million and more than 158,000 registered jobs in 2024, with a domestic fintech subsector that commands 88% of digital banking ² — indicator 4.3 is the second and last Level 3. Third, an installed base of policy recognition and bounded technical capacity in Dimension 2: a state GNU/Linux distribution, a national public cloud on open-source code, and citizen platforms authored by the State ³.

Three principal weaknesses. First, the collapse of cross-border flows: the commitment to recognise the United States as an adequate jurisdiction, formalised in November 2025 and February 2026, brings indicator 1.3 down to Level 1 through the mechanism of Principle #7 ⁴. Second, the total absence of data value capture: Argentina gives its public data away for transparency but possesses no fiscal instrument, no B2G mandate, and no recognition of data as an economic asset, which places indicator 1.4 at Level 1 ⁵. Third, a cross-cutting structural dependence in Dimensions 2 and 4: the country does not manufacture hardware, does not control its system-software stack, and exports its most capable talent abroad ⁶.

The cross-cutting finding that orders the entire assessment is the Milei administration’s deregulation trajectory as a ceiling factor. This is not a context that explains low ratings, but an active policy that subtracts capacity: 543 measures that modify or eliminate 2,519 norms across 15,144 articles ⁷, a cumulative real cut of 50.6% in the science-and-technology budget function ⁸, and the cession of sovereignty over data flows. Where other countries build, Argentina dismantles — and the DSI framework, through its trajectory clause and its Principle #7, registers that direction as a ceiling, not as a mitigating circumstance.

Chapter 2 — Methodological Framework

2.1 The DSI 4×4 framework

The Digital Sovereignty Index evaluates the degree to which a country has attained independence in the digital domain: the extent to which its data, its infrastructure, its governance and its capabilities are determined by the country itself and not by foreign actors, jurisdictions, or platforms. The operational definition, set out in the DSI methodological specifications, rests on the word ‘independence’: the index does not measure whether a country aspires to be sovereign, but whether, in fact, it is. The framework organises the assessment into a matrix of four dimensions by four indicators — sixteen indicators in total — defined in the Digital Sovereignty Index specifications coordinated by Global South Insights through the DSI Assessment Team, under the Global South Academic Forum. This Argentina assessment was prepared by UNGS as an associate university, applying those methodological specifications to the national situation: evidence collection from Argentine sources, the local implementation of the assessment pipeline, and the drafting of the analysis in academic Spanish constitute UNGS’s contribution to the global index compiled by GSI.

The four dimensions are: Dimension 1 — Independence in data ownership (1.1 Data-ownership legislation; 1.2 Domestic storage; 1.3 Protection of cross-border flows; 1.4 Data value for public benefit); Dimension 2 — Digital infrastructure independence (2.1 Basic hardware; 2.2 System software; 2.3 Application software; 2.4 Information security); Dimension 3 — Digital governance independence (3.1 Legislative capacity; 3.2 Enforcement capacity; 3.3 Leadership in international technical rules; 3.4 Leadership in international conduct rules); and Dimension 4 — Digital capacity independence (4.1 Frontier research; 4.2 University talent; 4.3 Industrial engineering; 4.4 National strategic alignment).

2.2 The 1–5 scale

Each indicator is rated on a scale of five progressive levels of independence: 1 Initial (the issue has not been addressed; potentially complete dependence), 2 Aware (the importance of independence is recognised and discussions or actions have been initiated, typically at the planning stage), 3 Developing (work is actively underway towards independence, with policies implemented but still with strong external dependence), 4 Competent (international competitiveness and full potential autonomy) and 5 Independent (basic self-sufficiency, with minimal external constraints). The scale is applied per indicator and prohibits decimal ratings: each level must be tied to a defensible path through a four-node decision tree (existence of critical evidence → effective implementation → meaningful enforcement → international competitiveness vs. self-sufficiency).

2.3 Principles, pitfalls, and the decision tree

Rating is governed by seven immutable principles that prevail over the decision tree when they come into tension with it: Facts over Law (effective implementation prevails over legal text), Effectiveness Supreme (laws that cannot be enforced receive lower ratings), Pragmatism (real status, not declared goals), Dependency Penalty (dependence on foreign platforms caps the ceiling), Corporate-Capture Degradation (legislative blocking by Big Tech lowers the rating), Context Explains but Does Not Excuse (geopolitical pressure explains but does not modify consequences), and the Digital Hegemony Reality Check — Principle #7 (designating the United States as an ‘adequate jurisdiction’ significantly lowers ratings). To the principles are added eight pitfalls, or rating traps — among them confusing activity with outcomes, underestimating weaknesses, and geographic presence without control — that must be cleared before finalising a rating, together with a horizontal-consistency check against the anchors of China, Russia, and Brazil.

2.4 The UNGS 2026 corpus

The assessment is grounded in the UNGS_2026 corpus, built by the UNGS agent pipeline. The collector gathered 373 raw pieces of evidence across the three search rounds; the verifier removed 91 for verification failures (invalid URL, lack of content match, or suspected hallucination); the integrator consolidated the remainder by removing 41 duplicates through exact URL match, leaving 241 integrated pieces of evidence (AR-EV-001 to AR-EV-241) plus 31 documented gaps. The composition by type covers regulation, case studies, quantitative data, reports, analysis, policy, and gaps; confidence is distributed across 125 high-confidence items, 80 medium, and 36 low. The share of Tier-1 sources (official domains *.gob.ar, InfoLEG, Boletín Oficial (Official Gazette)) reaches 48.5%, above the 40% minimum but below the 60% target. Each [AR-EV-NNN] citation in this report is traceable to a verified URL in evidence_base_UNGS_2026.json.

2.5 The Principle #7 override mechanism

One methodological element deserves anticipating because it proves decisive for indicator 1.3. Principle #7 does not function as a gradual downward adjustment but as a categorical-collapse mechanism: the active designation of the United States as an adequate jurisdiction for personal-data transfers relocates indicator 1.3’s rating to Level 1, overriding the result that the decision tree would have yielded on its own merits. The reasoning is that ceding adequacy to a jurisdiction without comprehensive federal privacy legislation and with statutory extraterritorial-access regimes (CLOUD Act) hollows out the protective purpose of the indicator, regardless of how sophisticated the rest of the framework may be.

2.6 Limitations

The assessment acknowledges four limitations. First, 31 candidate items were discarded as URL_BLOCKED owing to anti-bot barriers, TLS, or 403 responses (ITU documentary databases, 3GPP partner listings, W3C sources); human re-retrieval is recommended for future runs, since these are transport limits, not veracity limits. Second, indicators 3.3 and 3.4 fell below the sufficiency threshold of 15 pieces of evidence (11 and 12 respectively) after the verifier’s removals, which limits their confidence to Low. Third, several de facto quantitative metrics rest on single Tier-3 sources or on inference (hyperscaler market shares, the brain-drain rate specific to computer science), which reduces confidence without invalidating the direction of the rating. Fourth, two items suspected of hallucination were removed by the verifier and do not appear in the library; this report does not reproduce their claims, in keeping with the anti-hallucination discipline that governs the pipeline.

Chapter 3 — Indicator-by-Indicator Analysis

Dimension 1 — Independence in Data Ownership

Dimension 1 asks who owns, controls, and benefits from the data generated by Argentine residents, firms and institutions. It is the dimension where Argentina displays its sharpest internal contrast: it has the oldest and most recognised data-protection legislative framework in Latin America — the first regional adequacy status before the European Union, in 2003 ⁹ — but that historical asset coexists with a flow protection collapsed by US adequacy and with a categorical absence of value-capture mechanisms. The relevant institutional landscape includes the AAIP (Agency for Access to Public Information) as the enforcement authority and the Law No. 25326 regime as the central piece. The dimension finding is unequivocal: with an average of 1.75, data ownership is Argentina’s weakest dimension, dragged down by the simultaneous collapse of two of its four indicators to Level 1.

3.1.1 Indicator 1.1 — Data ownership legislation

Rating: 3 — Developing. Confidence: High.

Argentina has a general data-protection statute in continuous force since the year 2000 — Law No. 25326 ¹⁰ — operationalised by Decree 1558/2001, verified as in force, and amended on thirty-two occasions ¹¹, and administered by the AAIP, an autonomous statutory body with a permanent National Directorate for the Protection of Personal Data ¹². The authority is not nominal: it issues resolutions of operational substance — security measures, model contractual clauses for transfers, and the tiering of sanctions ¹³ — and exhibits a multi-year activity trace (491 case files and 52 sanctions in 2022) ¹⁴. The framework retains current external recognition: the European Union’s adequacy status was reaffirmed in January 2024 ¹⁵ and Convention 108+ was ratified by Law No. 27699 in 2022 ¹⁶. This conjunction of an operative statute, a functional regulator, and international recognition defines the Level 3 profile.

What prevents an ascent to Level 4 is the conjunction of two independent failures. First: the modernised text is not in force. The reform bill (Message 87/2023), which incorporated breach notification, impact assessments, portability, and the data-protection officer, lost parliamentary status at the end of 2024 after more than thirty months without consideration ¹⁷; the post-GDPR-era provisions remain absent from the text in force ¹⁸. By Principle #1 (Facts over Law), a bill cannot anchor a higher rating. Second: enforcement is not deterrent. The fine cap was never updated by law and stands at around USD 70–100; AAIP Resolution 126/2024 graduated infractions but could not raise the legal ceiling, because an administrative resolution does not amend a law ¹⁹; the total of 2022 fines was some USD 30,621 ²⁰ and the mass leaks of 2024–2025 (Renaper, ARCA, ANSES) were not sanctioned ²¹. By Principle #2 (Effectiveness Supreme), enforcement without deterrent magnitude is capped at Level 3. It does not descend to Level 2 because the statute is in force — it is not a draft — the regulator operates and there is an enforcement trace: Argentina comfortably clears the band of ‘preliminary discussions or planning’. In the comparative frame, 1.1 sits well below the Chinese anchor (Level 5) and groups with Brazil (Level 3): both regimes are transplanted from external standards and their enforcement scaling has lagged, although the Argentine weakness is specific — an obsolete text from 2000 whose modernisation stalled. An ascent to Level 4 would require the modernised text to enter into force and the fine cap to reach deterrent magnitudes on the order of 2–4% of revenue; erosion towards Level 2 would only follow the dismantling of the AAIP or the repeal of the regime in force.

3.1.2 Indicator 1.2 — Domestic data storage

Rating: 2 — Aware. Confidence: Medium.

Argentina lacks a general data-localisation mandate. The personal-data regime (Law No. 25326, art. 12) governs cross-border flows through adequacy and contractual clauses, not through territorial storage, and the AAIP’s own security resolution imposes no geographic restriction whatsoever ²². The only operative sectoral rule is the Central Bank’s prudential regime on third-party control and delegated technology (BCRA (Central Bank of the Argentine Republic) Communication A 7724, updated by A 8401) ²³, which structures the supervision of outsourced services but does not require storage in national territory. Two reform bills explicitly preserve the transfer-based model and decline to introduce a localisation mandate ²⁴. A residual sovereign capacity exists — ARSAT’s Tier III data centre and the national public cloud on open-source code ²⁵ — but it is niche, oriented to the public sector, and undergoing partial privatisation (49%) ²⁶. This configuration — a sectoral-only rule, residual domestic infrastructure, non-localising bills — corresponds precisely to Level 2.

The indicator does not reach Level 3 because that would require effectively enforced localisation in multiple substantive sectors plus a domestic cloud industry with measurable share: Argentina meets neither. The installed national capacity (~32 MW) is orders of magnitude smaller than a single hyperscale facility ²⁷, while the growth of the cloud market is captured by foreign providers — AWS’s Local Zone in Buenos Aires and the OpenAI/Sur Energy 500 MW project under the RIGI ²⁸ — a configuration that the framework rates as geographic presence under foreign jurisdiction (CLOUD Act), not as sovereignty (Pitfall #8). State policy actively incentivises foreign-controlled infrastructure without a localisation counterpart ²⁹. It does not descend to Level 1 because there coexist a sectoral mandate in force, an operative state alternative and documented legislative discussion — the presence of the three elements the criterion requires to clear the initial floor. Argentina groups with Brazil (Level 2): both lack a general mandate and see their markets dominated by hyperscalers, while Russia (Level 4, Law 242-FZ with documented enforcement) marks exactly the regime that the Argentine bills decline to adopt. An ascent to Level 3 would require a sectoral localisation mandate effectively audited in finance and health or government, together with a domestic cloud industry of non-residual share.

3.1.3 Indicator 1.3 — Protection of cross-border flows

Rating: 1 — Initial. Confidence: High.

On paper, Argentina possesses a comprehensive and operationally exercised cross-border transfer regime: article 12 of Law No. 25326 prohibits transfers to jurisdictions without adequate protection ³⁰, Decree 1558/2001 empowers the regulator to assess adequacy ³¹, Disposition 60-E/2016 publishes model contractual clauses ³², AAIP Resolution 34/2019 maintains a granular adequacy list from which the United States was explicitly absent ³³, and the country retains European adequacy status since 2003, revalidated in January 2024 ³⁴. This conjunction of an operative statute, a functional regulator and international recognition defines the Level 3 profile.

However, the Joint Statement of 13 November 2025 and the USTR Fact Sheet ³⁶, formalised by the signing of the Agreement on Reciprocal Trade and Investment on 5 February 2026 ³⁷, commit Argentina to recognising the United States as an adequate jurisdiction for personal-data transfers. By Principle #7 (Digital Hegemony Reality Check) and the indicator’s ‘collapse through extreme permissiveness’ mechanism, an active US adequacy designation caps the rating at Level 1, overriding the narrowing of the decision tree. Sophistication on paper does not anchor the rating; the operational reality of structural deference to a hegemonic jurisdiction does (Principle #1). This is a Level 1 by way of collapse, not by regulatory void: the regime exists and is exercised, but the adequacy designation to the dominant jurisdiction of data platforms removes the only protective barrier — historically, US Big Tech operated via contractual clauses, not by adequacy ³⁸. In the comparative frame, the decisive separator with respect to China (≈5) and Russia (≈4) is exactly the variable that Principle #7 isolates: neither anchor grants adequacy to the United States, while Argentina now does. The result coincides with the BRICS 2025 baseline (also Level 1) by identical collapse reasoning. The only possible upward move would be the non-entry-into-force or the reversal of the US adequacy commitment; without it, no level above 1 is attainable.

3.1.4 Indicator 1.4 — Data value for public benefit

Rating: 1 — Initial. Confidence: High.

Argentina sustains a mature and long-standing open-data programme — Decree 117/2016, Law No. 27275 on access to information, and the datos.gob.ar portal with 1,235 datasets from 42 agencies ³⁹ — together with an active civic-tech ecosystem that reuses public data ⁴⁰. But that programme operates entirely on a logic of transparency and reuse, not of economic value capture from the data. The conceptual distinction is decisive: a robust open-data programme ‘gives data away to enable innovation’, while the indicator measures ‘capturing the value of data for public benefit’. All of Argentina’s substantive positive evidence belongs to the first category.

The indicator’s critical enablers are absent and documented as gaps with Tier-1 search: there is no state recognition of data as a factor of production or economic asset ⁴¹, there is no operative B2G mandate requiring platforms to share datasets of public interest ⁴², there is no fiscal value-capture instrument — the PAIS tax was a consumption tax, excluded by criterion, and was moreover repealed in December 2024 ⁴³, and the OECD’s Pillar One and Pillar Two were not implemented ⁴⁴ — antitrust is not applied to data monopolies — the CNDC (National Commission for the Defence of Competition) maintains a study group without sanctioning power, and none of the eleven concentrated markets under investigation is a digital-native platform ⁴⁵ — and there are no institutional data trusts ⁴⁶. Decree 780/2024, moreover, restricted the scope of active transparency: a regression, not an advance ⁴⁷. By Principle #3 (Pragmatism), aspirational bills do not anchor higher levels; the categorical absence of the critical piece ends the decision tree at Level 1. The indicator does not ascend to Level 2 because there does not even exist governmental recognition of data as an asset — not merely civil-society discourse — in a strategy or bill. The sophistication of the open-data programme places Argentina at the high end of Level 1, above a country with no policy at all, but transparency is not value capture. Against China (Level 4–5: data as the fifth factor of production since 2019), Argentina exhibits a lag of several levels; even against Russia and Brazil it remains a step below, lacking the limited B2G mechanisms and the digital-services taxation that those countries possess. An ascent to Level 2 would require the BCRA’s Open Finance System to enter into force or a bill to recognise data as an economic asset.

Intra-dimensional analysis. Dimension 1 reveals the Argentine paradox in its pure state: indicator 1.1, the strongest of the entire matrix on its own merit (the only framework with 2003 European adequacy), coexists with the collapse of 1.3 to Level 1 through the 2026 US adequacy, and with the total void of 1.4. The common bottleneck is that Argentina built capacity for protection without capacity for exploitation: it legislates the data point, but neither retains it territorially, nor protects it on its way out to the hegemonic jurisdiction, nor captures its economic value. The regulatory sophistication of 1.1 does not compensate for, and in fact contrasts with, the cession of sovereignty of 1.3 and the absence of economic vision of 1.4.

Dimension 2 — Digital Infrastructure Independence

Dimension 2 evaluates whether the country can operate its digital infrastructure without dependence on, or interruption by, foreign providers, across four layers: hardware, system software, application software and security. The relevant institutional landscape includes ARSAT and the national public cloud, the Tierra del Fuego regime, INTI, and INVAP on the technical plane, and CERT.ar in security. The dimension finding is notably uniform: all four indicators sit at Level 2 (average 2.00), a pattern of ‘awareness without substantive capacity’ in which Principle #4 (Dependency Penalty) — which the framework declares dominant for this dimension — operates across the board. Argentina recognises its dependencies and possesses real traces of capacity, but in each layer the structural dependence on the foreign stack caps the rating.

3.2.1 Indicator 2.1 — Basic hardware autonomy

Rating: 2 — Aware. Confidence: Medium.

There is explicit recognition of hardware dependence in national-level instruments — the Compre Argentino (Buy Argentine) regime (Law No. 27437) and the Knowledge Economy promotion regime (Law No. 27506) ⁴⁸ — and an at-scale capacity for assembling imported components under the Tierra del Fuego regime (Law No. 19640), where close to 93% of telephones, air conditioners, and televisions sold are assembled domestically ⁴⁹. But assembly is not manufacturing: by the principle ‘assembly is not autonomy’, assembling imported boards is value-added activity, not the substitution of foreign capacity. There exists no funded foundational hardware programme reaching the hinge threshold of ~USD 1,000 million over five years oriented to chip design or wafer fabrication: the RIGI attracts foreign investment in an enclave model without a technology-transfer obligation ⁵⁰, the Knowledge Economy benefits target software and services, not manufacturing ⁵¹, and the national science-and-technology strategy (CTI Guidelines 2025–2027) explicitly omits microelectronics and semiconductors ⁵². Semiconductor capacity is design-only: the INTI provides integrated-circuit design services that are synthesised in foreign foundries, and Argentina operates no wafer plant ⁵³.

The trajectory, moreover, is downward within the band: Decree 333/2025 reduces the import tariff on mobile phones from 8% to 0% by January 2026 ⁵⁴, Decree 111/2025 dilutes the Fuegian promotion fund, and the Mirgor Group suspended around 360 workers in response ⁵⁵. The indicator does not reach Level 3 because that requires a funded foundational programme in design or fabrication, or a domestic-supplier share of 10–30% in some hardware category designed in the country: Argentina meets neither. It does not descend to Level 1 because both policy recognition and an operative assembly capacity persist. In the comparative frame, Argentina sits alongside Brazil (Level 1–2, with its failed CEITEC plant) and on a par with the Russian anchor (Level 2); Level 3 in this region requires extraordinary evidence — a sustained fabrication programme with output measured in wafers. An ascent to Level 3 would require a funded foundational programme; erosion towards Level 1 would follow the complete collapse of the Fuegian assembly base.

3.2.2 Indicator 2.2 — System software autonomy

Rating: 2 — Aware. Confidence: High.

Argentina presents the canonical Level 2 pattern: policy recognition and demonstrated engineering capacity, without a funded national programme or measurable domestic share. There is explicit recognition of software sovereignty — the ONTI Public Software initiative, ONTI Disposition 2/2019 requiring code to be shared under open licences across the entire National Public Sector, and Santa Fe’s provincial law on the preferential use of free software ⁵⁶ — and a bounded implementation footprint: a state GNU/Linux distribution (Huayra, developed at EDUCAR) ⁵⁷, a national public cloud on open-source code ⁵⁸ and an ecosystem of official repositories (argob, 43 repositories) ⁵⁹. This satisfies the existence and implementation nodes, but no piece crosses the Level 3 thresholds.

Foreign dominance is overwhelming and quantified: the domestic desktop operating system is marginal (Windows 81.64%, total Linux 2.21%) ⁶⁰, the mobile market is more than 99.97% foreign ⁶¹ and the database market is dominated by Oracle, SAP, Microsoft, and IBM, with effectively zero domestic share ⁶². Decisively, ARSAT’s own state cloud runs its network operations centre on Red Hat OpenShift — control software from a US provider ⁶³ — so the control plane is not domestic: the physical location of the data centre does not equate to autonomy (Principle #7). The only domestic operating-system footprint (Huayra) was confined to the education sector and was suspended and intervened in the Milei era: the Conectar Igualdad and Educ.ar platforms were left in ‘construction mode’ and Decree 963/2024 appointed an intervenor for EDUC.AR S.E. ⁶⁴, downgrading that single case to symbolic status. Linux adoption is necessary but not sufficient, because its upstream is controlled from outside the country. It does not descend to Level 1 because a documented state distribution and a nationally scoped public-software regulation persist. Argentina is directly comparable to Brazil (Level 2) and remains a step below Russia (Level 3–4, with certified Astra Linux and sanctions-accelerated substitution). An ascent to Level 3 would require critical-infrastructure systems running on a domestic operating system with audited patching independence, or more than 5% domestic share in cloud, databases, or server operating systems.

3.2.3 Indicator 2.3 — Application software autonomy

Rating: 2 — Aware. Confidence: Medium.

Argentina presents the textbook Level 2 profile for this indicator: a capable software industry and genuine domestic dominance in several vertical categories, against complete foreign control of every horizontal category. On the vertical plane the evidence is strong and verified: Mercado Libre led national app downloads in 2024 (11.7 million) ⁶⁵, Mercado Pago surpassed 50 million monthly active users in Latin America with USD 8,600 million in revenue ⁶⁶, three domestic neobanks retain 88% of digital banking ⁶⁷ and the State deploys self-authored citizen platforms at scale — Mi Argentina, with 21 million registered users ⁶⁸. On the horizontal plane, dependence is almost total and quantified: WhatsApp with 93% penetration in messaging, Instagram with 86.7% ⁶⁹, Google with 94.01% of searches ⁷⁰, and productivity, ERP, and CRM dominated by Microsoft, SAP, Oracle, and Salesforce with no domestic provider of measurable share ⁷¹.

The decisive test of the indicator is horizontal share: an ascent to Level 3 requires ≥30% domestic share in at least one major horizontal category (office software, ERP, or industrial software). The Argentine shares above 30% are all in vertical categories — e-commerce, payments, digital banking — which the criterion explicitly excludes from the horizontal denominator. Policy is one of promotion, not substitution: Law No. 27506 sustains a service-export industry (USD 2,674 million in 2024, 46.9% to the United States) ⁷² rather than the substitution of horizontal products, and a domestic champion in a horizontal-adjacent category (Auth0, authentication) was acquired by the US firm Okta, reversing the sovereignty relationship (Principle #5) ⁷³. It does not descend to Level 1 because there are measurable domestic products, policy recognition, and a substantive software industry. Argentina groups with the lower band of Brazil but below it, because Brazil has, in TOTVS, a domestic ERP provider with measurable horizontal share — exactly what Argentina lacks — and remains a level below Russia (Level 3, with 1C in ERP and MyOffice in office software). An ascent to Level 3 would require a domestic provider to reach 30% share in a horizontal category or the public-procurement preference for nationally originated software to be applied with auditing.

3.2.4 Indicator 2.4 — Information security autonomy

Rating: 2 — Aware. Confidence: Low.

Argentina possesses a comparatively rich cybersecurity institutional architecture but fails the three substantive tests that separate Level 2 from Level 3. There is a national CERT in regulation (CERT.ar, Disposition 1/2021) ⁷⁴, operative on paper — it registered 438 incidents in 2024, 15% above 2023, with 61% in the state sector ⁷⁵ — and internationally recognised through FIRST membership. The scope of that figure must be made explicit: CERT.ar’s mandate is confined to the National Public Sector, within a deliberately federated incident-response architecture. Alongside it operate a second national-level team at the Ministry of Security and a network of sub-national centres — among them the BA-CSIRT of the Autonomous City of Buenos Aires, the CSIRT of the Province of Buenos Aires, and that of the Province of Córdoba, several of them integrated into the OAS CSIRT Americas Network — each with its own jurisdiction and sectors. These teams do not aggregate into the national score of this indicator, which measures federal-level capacity; their existence, however, means that CERT.ar’s register must not be read as an exhaustive count of the country’s incident activity, but as the activity of the federal-level team. A layered regulatory regime governs the public sector: the PNICIC critical-infrastructure programme, minimum security requirements with a duty to notify the CERT within 48 hours (Administrative Decision 641/2021) ⁷⁶, a second National Cybersecurity Strategy and the reorganisation of Decree 941/2025 that creates the National Cybersecurity Centre, and the Federal Cyberintelligence Agency ⁷⁷. But, by Principles #1 and #2, strategies, and constitutive instruments are activity, not measured effectiveness.

The triple test fails simultaneously: the CERT’s capacity (438 total incidents — not ‘major’ — reported without standardised FIRST-type operational metrics — mean time to respond, severity classification, or a trace of advisories adopted; the count is a raw aggregate that, moreover, reflects only the National Public Sector perimeter, and does not evidence the handling of major incidents with disclosed timelines) ⁷⁸; the market test (no measurable domestic share and no documented sovereign cryptographic research) ⁷⁹; and the product test (no verifiable domestic security product in critical infrastructure) ⁸⁰. Three major breaches of the period are reverse evidence that the regime does not protect: the leak of the national driver’s-licence database (~5.7–6 million records, 1.25 TB, April 2024) ⁸¹, the December 2024 defacement of Mi Argentina and SUBE — where the attackers reported the absence of two-factor authentication on central-government sites ⁸² — and the recurring RENAPER incidents ⁸³. Confidence is capped at Low because the evidence subset (14 items) falls below the sufficiency threshold and the corpus entirely lacks market-share data. It does not descend to Level 1 because CERT.ar exists in a constitutive instrument and registers incidents, and a substantive strategy is published and under active reform. Argentina sits at the lower edge of the Brazilian band (Level 2–3) and well below Russia (Level 4, with Kaspersky and the sovereign GOST cryptography). An ascent to Level 3 would require a public trace of major incidents with response times, a domestic security-product industry of measurable share, and a sovereign cryptographic regime applied in critical infrastructure.

Intra-dimensional analysis. The four indicators of Dimension 2 share a single bottleneck: the Dependency Penalty. Argentina recognises every dependence — it has Compre Argentino, Public Software, a thriving software industry, and a CERT — but in each layer the real capacity is assembly (2.1), foreign upstream (2.2), vertical strength without horizontal substitution (2.3) or architecture without effectiveness (2.4). The symptomatic tension is that the dimension’s most visible asset — the software industry — feeds service exports to foreign clients and champions that are acquired by US firms, so that engineering capacity does not translate into infrastructure autonomy. The uniformity of Level 2 is no coincidence: it is the hallmark of an economy that is a net integrator of every layer of the digital stack.

Dimension 3 — Digital Governance Independence

Dimension 3 asks whether the country governs its digital space or is governed within others’ rules, through legislative capacity, enforcement, and leadership in international rules. The institutional landscape includes the Congreso de la Nación (National Congress), the AAIP, and the competition authority (CNDC, succeeded by the National Competition Authority), IRAM in technical standards and the Cancillería (Ministry of Foreign Affairs) in multilateral fora. The dimension finding (average 2.00) combines two high-confidence profiles — legislative capacity and enforcement, both capped at Level 2 by a subtractive trajectory and symbolic enforcement — with two low-confidence profiles owing to insufficient evidence (3.3 and 3.4), both also at Level 2: international participation without leadership.

3.3.1 Indicator 3.1 — Legislative capacity in digital matters

Rating: 2 — Aware. Confidence: High.

Argentina possesses a foundational but dated digital legal corpus: a cybercrime law (Law No. 26388, 2008), electronic signature (Law No. 25506, 2001), grooming (Law No. 26904, 2013), a statute on internet-provider content (Law No. 25690, 2002) and the telecommunications framework (Law No. 27078, 2014) ⁸⁴, alongside a data-protection statute (Law No. 25326, 2000) never substantively modernised. On a static reading, this corpus sits at the high end of Level 2: the foundational statutes are pre-2015 in substance, the frontier domains (artificial intelligence, platforms, statutory cybersecurity) are governed by executive instruments or non-binding guidance ⁸⁵, and the modernisation bills remain pending without enactment ⁸⁶.

Decisively, the trajectory is subtractive. The Ministry of Deregulation accumulates 543 measures that modify or eliminate 2,519 norms across 15,144 articles — verified textually against the official source ⁸⁷ — article 15 of Law No. 27078 was repealed by decree in April 2024 ⁸⁸ and the national artificial-intelligence strategy was institutionally discontinued ⁸⁹. By the indicator’s trajectory clause, a corpus under active dismantling cannot exceed Level 2 regardless of its historical base: this is the binding constraint, and it confirms Level 2 regardless of the static result of the decision tree. The indicator does not reach Level 3 because that would require at least one enacted — not proposed — frontier statute plus a trace of legislative modernisation in the last five years, conditions that the deliberate deregulatory trajectory (Argentina articulated as a ‘low-regulation hub’ for AI) ⁹⁰ renders unattainable. It does not descend to Level 1 because a genuine digital corpus is in force and the Budapest Convention and Convention 108+ have been incorporated. Against Brazil (Level 3, with the operative LGPD and an AI bill advancing), Argentina remains a level below precisely because its frontier bills do not advance to enactment and its existing corpus is being dismantled. The convergence with the BRICS 2025 rating (also Level 2) validates the reading. An ascent to Level 3 would require the enactment of a frontier statute (AI or platforms) and the cessation of the subtractive trajectory.

3.3.2 Indicator 3.2 — Enforcement capacity

Rating: 2 — Aware. Confidence: High.

Argentina has operative digital regulators with statutory sanctioning powers — the AAIP in data protection, the CNDC (replaced by the National Competition Authority on 17 November 2025) in competition, and the BCRA in financial cybersecurity — but enforcement is symbolic rather than consequential. The AAIP’s statutory fine scale runs from ARS 1,000 to ARS 100,000 (~USD 88–100 at its maximum) ⁹¹, orders of magnitude below the GDPR’s 4%-of-revenue standard; the largest sanction against a Big Tech firm ever imposed is the one against Google, for ARS 280,000 aggregated (~USD 215, 2020), equivalent to around 0.0001% of the offender’s revenue ⁹². The competition authority issued 89 merger-control decisions and a single procedural fine for late notification in 2024, with zero anticompetitive-conduct sanctions ⁹³.

The binding fact is the closure of the flagship case: the CNDC shelved the abuse-of-dominant-position investigation against WhatsApp and Meta on 2 July 2025 without a final sanction, after four years and two rounds of precautionary measures confirmed judicially ⁹⁴. A regulator that opened, litigated, and then abandoned its emblematic case against a foreign Big Tech firm without extracting any concession exemplifies the Level 2 ceiling. The indicator does not reach Level 3 because that requires at least one concluded enforcement action that produces documented behaviour change among the regulated, together with non-testimonial sanctions proportional to the infraction: the behaviour-change test is mandatory and fails resoundingly. It does not descend to Level 1 because the AAIP has concluded real monetary sanctions — even against a Big Tech firm — and the competition authority processes merger control at volume with professional staff. Argentina remains below Brazil (Level 2–3), whose CADE demonstrated the capacity to extract compliance even from foreign platforms (the X/Twitter episode), and well below China (Level 5, with the structural decisions against Alibaba and Didi). An ascent to Level 3 would require a concluded sanction with verifiable behaviour change and the updating of the fine cap to deterrent magnitudes.

3.3.3 Indicator 3.3 — Leadership in international technical rules

Rating: 2 — Aware. Confidence: Low.

Argentina is an active participant in international technical-standards bodies, with a genuine contribution but without leadership. It maintains its level of access through the general standards ecosystem — IRAM is the sole national representative before ISO and, together with CEA/AEA, before IEC, as well as a representative in the regional bodies COPANT and AMN ⁹⁵ — and the country rejoined IEC in 2001. The strongest and verified contribution is that of Verónica Marinelli, of IRAM’s SC 27 mirror committee, as one of three editors of the adopted international standard ISO/IEC 27002:2022 ⁹⁶; alongside her, editors from a single institution (UTN’s Santa Fe Regional Faculty) act as editors of at least five Y-series Recommendation projects of the ITU-T’s Study Group 20 ⁹⁷.

But the concentration in a single institution and a single body is exactly what the criterion caps at Level 2: an isolated editor/rapporteur contribution — the lowest leadership level — does not cross the frontier to Level 3, which requires multi-body adoptions and a handful of leadership roles. The chair leadership level is verifiably absent: there is no Argentine vice-chair in the 2025–2028 leadership roster of the ITU-T’s Study Group 20 ⁹⁸, nor any Argentine organisation among the 329 members of the W3C ⁹⁹ — Argentina is a rule-taker in web protocols. The regional engagement (chair of CITEL’s Steering Committee in 2018) is real but, by Pitfall #5, regional harmonisation is categorically distinct from global rule-making and does not raise the global rating ¹⁰⁰. Confidence is capped at Low because the corpus lost around ten candidate items to verification failures and ended up at 11 items, below the sufficiency threshold. Argentina groups with the Brazilian anchor (Level 2): both are regional leaders with limited global presence. An ascent to Level 3 would require contributions adopted in multiple bodies by multiple institutions, plus leadership roles above the editor level.

3.3.4 Indicator 3.4 — Leadership in international conduct rules

Rating: 2 — Aware. Confidence: Low.

Argentina is a recurrent and substantive participant in the main arenas of international digital governance — the UN Open-Ended Working Group on ICT security, the Ad Hoc Committee that produced the Convention on Cybercrime, the Council of Europe’s Convention 108 system and regional internet-governance fora — but the evidence shows participation without independent agenda-setting. The strongest signal, the election of Beatriz Anchorena to chair the Council of Europe’s Convention 108 Committee ¹⁰¹, is a genuine credential of treaty engagement, but it is a rotating institutional chairmanship over an instrument anchored in the European Union that advances the Council of Europe’s own work programme, not a doctrine of Argentine origin adopted by other States. The interventions in the Working Group were carried out explicitly ‘without co-sponsoring substantive thematic resolutions’ ¹⁰².

Decisively, a domestic–international coherence failure undermines any claim to independent normative leadership: a data-protection bill with extraterritorial scope and anti-CLOUD Act provisions (1948-D-2025) runs contemporaneously with the Framework Agreement that grants the United States data-adequacy status ¹⁰³ — Argentina advocates data sovereignty while conceding it. The indicator does not reach Level 3 because that requires co-sponsorship of a substantive instrument with documented impact on the final text, visible independent positioning, and domestic–international coherence, and the surviving evidence satisfies none of these. As to the Argentine withdrawal from the Pact for the Future and the Global Digital Compact, it is treated qualitatively as dissent-without-alternative — Level 2 positioning, not Level 3 leadership — without reproducing the specific date or cohort, whose evidentiary carrier was removed by the verifier. It does not descend to Level 1 because Argentina is an active participant of substance, with recurrent delegations and a treaty-committee chairmanship. Against Brazil (Level 3, with NETmundial 2014 and sustained leadership in the IGF), Argentina remains just below, at the upper edge of Level 2, for lacking a flagship convened process and for exhibiting the incoherence that Brazil does not show. An ascent to Level 3 would require a co-sponsored instrument with documented influence and the resolution of the domestic–international incoherence.

Intra-dimensional analysis. Dimension 3 exposes a coherent internal hierarchy: legislative capacity (3.1) exceeds enforcement (3.2) in its historical base, but both are capped at Level 2 for distinct reasons — a subtractive trajectory in 3.1, the absence of deterrent effect in 3.2 — satisfying the cross-cutting consistency rule that requires enforcement ≤ legislation. International leadership (3.3 and 3.4) remains at participation without influence, consistent with the rule that requires influence in international rules ≤ domestic R&D capacity. The common bottleneck is that Argentina possesses real institutions that operate within others’ rules: it legislates but dismantles, it enforces but does not deter, it participates but does not lead. The domestic–international incoherence of 3.4 — advocating data sovereignty while conceding US adequacy — is the dimension’s sharpest cross-cutting symptom.

Dimension 4 — Digital Capacity Independence

Dimension 4 analyses whether the country has the human, scientific, and industrial capacity to sustain digital sovereignty across generations, along four indicators: frontier research, university talent, industrial engineering, and strategic alignment. The institutional landscape includes CONICET, the free public university system, the MinCyT/Secretariat of Science and Technology, and the software industry. The dimension finding (average 2.25) makes it Argentina’s highest, sustained entirely by industrial engineering (4.3, the dimension’s only Level 3); the other three indicators remain at Level 2, cut across by the fiscal collapse of the period.

3.4.1 Indicator 4.1 — Frontier-technology research

Rating: 2 — Aware. Confidence: Medium.

Argentina possesses genuine institutional infrastructure for frontier digital research: CONICET, the first governmental scientific institution in Latin America, and the twentieth in the world among governmental research bodies ¹⁰⁴; a CNEA-CONICET superconducting-qubit programme (QUANTEC) ¹⁰⁵; a sovereign high-performance computing facility (Clementina XXI, 15.3 PFLOPs, ranked 82nd in the TOP500) ¹⁰⁶; and budgeted quantum-infrastructure calls ¹⁰⁷. What it does not possess is the binding condition that Level 3 requires: sustained presence in top-tier global venues (NeurIPS, ICML, ICLR) at a non-trivial volume over a five-year window. Argentina’s aggregate output at these venues is documented as low and dependent on foreign co-authorship ¹⁰⁸.

The existing artefacts are below the ‘more than a prototype’ threshold: QUANTEC targets 4–6 qubits, with coherent manipulation still a goal for 2025 ¹⁰⁹, and Clementina XXI is an acquired Lenovo cluster, a sovereign capacity but not a domestically designed artefact. The decisive modifier is a verified downward fiscal trajectory: R&D investment fell to 0.216% of GDP in 2024, a real decline of 31.3% and 55.4% below the 0.39% mandated by Law No. 27614 for that fiscal year ¹¹⁰, with that law’s progressivity articles suspended ¹¹¹. By Pitfall #3, the rating reflects the downward trajectory, not the inherited institutional stock. It does not descend to Level 1 because CONICET operates a substantive research community and there are funded programmes and sovereign HPC. Argentina remains a level below Brazil (Level 3), whose differential is a longer trajectory of sustained investment; the 2024 fiscal collapse sharpens the gap rather than narrowing it. An ascent to Level 3 would require sustained presence in top-tier venues and a funding trajectory that is at least stable.

3.4.2 Indicator 4.2 — University talent development

Rating: 2 — Aware. Confidence: Low.

Argentina operates a free and recognised university system that produces digital-technology graduates at a measurable but modest and declining volume, has no university among the world’s top 500 in computer science, and loses its most capable graduates to foreign labour markets through a structurally selective brain drain. The production system exists; the retention system has failed. The base is real: close to 6,500 engineering graduates per year nationally, with UTN producing 42.75% ¹¹², and specialised postgraduate programmes in data science, and artificial intelligence emerging in several universities ¹¹³. A State policy for repatriating the diaspora (RAICES) and pipeline programmes (Sadosky, Numéricas) evidence recognition of talent as a strategic asset ¹¹⁴.

But the indicator does not reach Level 3 for four reasons. No Argentine university appears in the global top 500 in computer science (UBA at 555th) ¹¹⁵. The production of computer-science graduates is small and decreasing (a decline of 23.68% in the 2010–2019 decade). The brain drain is the dominant structural pattern: Argentina is among the 30 largest emitters of highly qualified talent, with close to 30,000 scientists and engineers in the United States alone, and the service-export model rents domestic talent to foreign clients via remote work ¹¹⁶. And the fiscal trajectory collapses: science-and-technology investment around 0.2% of GDP (the level of the 2002 crisis) and CONICET doctoral scholarships cut by around 30% in 2024 ¹¹⁷. Confidence is capped at Low because the emigration rate specific to computer-science doctorates cannot be substantiated with Tier-1 sources and is sealed as a gap. It does not descend to Level 1 because the pipeline is operative and measurable. Argentina remains a level below Brazil (Level 3), whose sustained investment is the multi-year differential. An ascent to Level 3 would require a university in the top 200 in a digital discipline and the control of brain drain below the operational threshold.

3.4.3 Indicator 4.3 — Industrial engineering capacity

Rating: 3 — Developing. Confidence: High.

Argentina sits firmly at Level 3 in industrial engineering capacity. The industry has substantive scale: software-industry revenue reached USD 22,221 million in 2024 (+13.1% year-on-year) with 158,179 registered jobs ¹¹⁸, and more than 140,000 formal sector employees exceed the automotive, oil, and mining industries combined ¹¹⁹. Software and IT-service exports reached a record USD 2,674 million in 2024 and the knowledge-based-services export complex was USD 8,047 million in 2022 ¹²⁰, placing Argentina second in Latin America among software exporters. At least one subsector is internationally competitive: fintech, where three domestically headquartered digital banks (Ualá, Brubank, Naranja X) retain 88% of the digital-banking market with 16.44 million clients ¹²¹, and where the 2024 venture-capital rounds were led by fintech ¹²². This comfortably exceeds Level 2: it is a real industry of products and services with domestically headquartered firms of national consequence. Argentina has produced more than a dozen unicorn-scale companies over the past decade, of which Auth0 — built by Argentine engineers and sold to the US firm Okta for some USD 6,500 million in 2021 — is the emblematic surviving case in the verified corpus ¹²³.

But the configuration falls decidedly short of Level 4 owing to five verified structural limits. First, the export base is skewed towards services with a thin product layer: in the 2022 mix, software was 33%, professional services 30%, architecture and engineering 22%, and R&D only 8% ¹²⁴, and the sector ‘tends more towards development than research’ ¹²⁵. Second, the dominant exit pattern is foreign acquisition at the growth stage, not independent scaling: the Auth0→Okta case is the canonical pattern of the migration of intellectual property and decision rights abroad ¹²⁶. Third, Argentina loses global market share — from 0.6% of world software sales in 2011 to 0.3% in 2021 ¹²⁷. Fourth, the capital base is fragile: venture capital fell from a peak of USD 1,337 million in 2021 to USD 412 million in 2024 ¹²⁸. Fifth, there is no autonomy of the foundational layer: the largest announced technology investment is the OpenAI/Sur Energy data centre under the RIGI — foreign hyperscaler capacity settled in the territory, not domestic cloud or foundational-model capacity ¹²⁹. By Principle #4, an industry built on foreign cloud, models and design tools is engineering capacity deployed on others’ rails. Argentina sits on a par with Russia and Brazil (both Level 3) and well below China (Level 5); the differential with Brazil is precisely the Argentine capital fragility. An ascent to Level 4 would require service–product parity, autonomy of the foundational layer, a domestic venture-capital ecosystem at scale, and independent scaling without foreign-acquisition pressure.

3.4.4 Indicator 4.4 — Alignment with national strategy

Rating: 2 — Aware. Confidence: Medium.

Argentina possesses an abundant and sophisticated catalogue of digital and science-and-technology strategy instruments at the highest level of government: the National Science, Technology, and Innovation Plan 2030 enacted by Law No. 27738 ¹³⁰, the Digital Agenda 2030 by decree ¹³¹, the Strategic Guidelines 2025–2027 ¹³², a National Artificial Intelligence Plan, and an inter-ministerial AI roundtable spanning ten jurisdictions ¹³³. On the axis of the strategy document, the country is comprehensive. But on each execution axis that the indicator measures — budget alignment, statutorily funded coordination, indicator tracking, and continuity across administrations — the evidence shows symbolic strategy without execution.

The AI roundtable was created ‘without its own budget allocation’ ¹³⁴ and the National AI Plan lacks a budget; the only funding dedicated to AI is an external IDB loan of USD 35 million ¹³⁵, which by Principle #4 is execution driven by an external lender, not domestic strategic alignment. The science-and-technology budget function fell 50.6% in cumulative real terms across 2024–2026 ¹³⁶, the national budget has been carried over for two consecutive years ¹³⁷, and the flagship programmes are cancelled and relaunched cyclically — Conectar Igualdad was created, suspended, relaunched, restored, and defunded across four administrations ¹³⁸; the MinCyT was created, downgraded, restored, and downgraded again ¹³⁹. The governing strategic posture is active deregulation (DNU 70/2023, which repealed or modified 366 norms, including Law No. 27078 Argentina Digital) ¹⁴⁰ framed within an ambition to be a ‘low-regulation hub’ ¹⁴¹, which Principle #7 treats as hegemonic alignment, not as a sovereignty strategy. The indicator does not reach Level 3 because that requires a budget partially aligned with the priorities, coordination operating with funded decisions and sustained execution across at least one complete administrative mandate: the budget-alignment and continuity tests both fail. It does not descend to Level 1 because statutory-level strategies and a coordination architecture exist on paper. Argentina mirrors Brazil’s Level 2 through the same mechanism (political discontinuity) but in more acute form. An ascent to Level 3 would require a budget effectively aligned with strategy and the cessation of the cyclical-cancellation pattern.

Intra-dimensional analysis. Dimension 4 shows a broken synergy: Argentina has real human and industrial capacity (4.1, 4.2, 4.3) and abundant strategy (4.4), but the period’s fiscal collapse disarticulates them. Industrial engineering (4.3) sustains the dimension at Level 3, but its own ceiling — foundational-layer dependence, capital flight and talent flight — refers directly back to the weaknesses of 4.1 and 4.2. The explicit cross-cutting contradiction is that the AI strategy depends on a stock of university and research capacity that the same budget cuts are depleting, leaving the country, in the words of the evidence itself, as a data-centre operator rather than an AI innovator ¹⁴². The consistency rule that requires capacity ≤ infrastructure is satisfied: Dimension 4’s capacity does not exceed Dimension 2’s infrastructure, both anchored in structural dependence.

Chapter 4 — Cross-cutting Findings

4.1 Synthesis by dimension

The dimension-by-dimension reading reveals a country of uneven but internally coherent digital sovereignty. Dimension 1 (1.75) is the weakest: the historical legislative asset (1.1) does not prevent the simultaneous collapse of flow protection (1.3) and value capture (1.4) to Level 1. Dimension 2 (2.00) exhibits uniform awareness without substantive capacity: all four indicators at Level 2, cut across by the Dependency Penalty that the framework declares dominant for infrastructure. Dimension 3 (2.00) combines operative institutions with the absence of deterrent effect (3.2) and of international leadership (3.3, 3.4), its legislative capacity (3.1) capped by the subtractive trajectory. Dimension 4 (2.25), the highest, rests entirely on the software industry (4.3); its other three indicators remain at Level 2 owing to the period’s fiscal collapse.

4.2 Horizontal comparison: AR against CN, RU, BR

The DSI framework anchors horizontal consistency against China, Russia, and Brazil. Across the set of sixteen indicators, Argentina groups consistently with Brazil, sits systematically below Russia, and is at a wide structural distance from China. China operates as the ceiling in every dimension — an exporting and expanding legislative corpus, a domestic hardware and software ecosystem, international agenda-setting, and global industrial champions — sitting around Level 5 in most indicators. Russia occupies a Level 3–4 band, with sanctions-forced substitution that produced domestic foundational layers (Astra Linux, Yandex, GOST cryptography) that Argentina does not possess. Brazil is the closest comparator: both countries share transplanted data-protection regimes, Level 3 software and fintech industries, hyperscaler dependence in infrastructure, and regional participation without global leadership.

The key distinction between Argentina and Brazil is instructive. Brazil surpasses Argentina in three precise indicators: it has, in TOTVS, a domestic ERP provider with horizontal share (2.3), it advances an AI bill towards enactment (3.1) and it exhibits enforcement capacity that extracts compliance from foreign platforms (3.2). Argentina, in turn, retains an asset that Brazil does not have in the same form: the 2003 European adequacy and an older data-protection regime (1.1). But the decisive divergence is direction: where Brazil builds, Argentina — in the assessment period — dismantles. That directionality is what, via the trajectory clause (3.1) and Principle #7 (1.3), separates Argentina from the Level 3 band that Brazil reaches in several indicators.

Table 4.1. Approximate comparative positioning by dimension.

4.3 The computation of the sovereignty score

The digital sovereignty score is computed as the arithmetic mean of the sixteen indicator ratings on the 1–5 scale; the total is the sum of the sixteen ratings, with a maximum of 80. Argentina totals 32 out of 80, which yields a score of 2.00 / 5.0. The computation is transparent and consistent with the dimension averages: (1.75 + 2.00 + 2.00 + 2.25) / 4 = 2.00. The dimension that drags the score down most is Dimension 1 (data ownership), owing to its two indicators at Level 1; the one that most sustains it is Dimension 4, owing to the only Level 3 of industrial merit (4.3). The cross-cutting consistency check is satisfied on all its axes: enforcement (3.2, Level 2) does not exceed legislation (3.1, Level 2); international influence (3.3–3.4, Level 2) does not exceed R&D capacity (4.1, Level 2); and capacity (Dimension 4) is aligned with infrastructure (Dimension 2). No anomalous inversions are detected. The score of 2.00 places Argentina at the threshold between awareness and development: the country systematically recognises its sovereignty deficits but, except in two indicators, has not crossed over into the effective construction of independence.

4.4 The Milei pattern: active deregulation as a ceiling factor

The most significant cross-cutting finding is that the Milei administration’s trajectory operates as a ceiling factor that manifests independently in at least four indicators, through distinct methodological mechanisms. In indicator 1.3, the adequacy commitment with the United States activates the Principle #7 override and collapses the rating to Level 1 ¹⁴³. In indicator 3.1, the trajectory clause caps legislative capacity at Level 2 owing to the Ministry of Deregulation’s quantified normative dismantling — 543 measures over 2,519 norms ¹⁴⁴. In indicators 4.1 and 4.4, the fiscal collapse — a real cut of 50.6% in the science-and-technology function and the suspension of the Law No. 27614 financing law ¹⁴⁵ — invalidates the investment trajectory that Level 3 requires. The methodological distinction is important: the framework does not penalise the Argentine macroeconomic situation (that would be context, which by Principle #6 explains but does not excuse), but the active policy of capacity subtraction. Deregulation is not a circumstance Argentina suffers; it is a government decision that the index registers as direction.

4.5 The Argentine paradox

The second cross-cutting finding is the paradox between the regulatory sophistication of the data point and the collapse of its sovereignty in the flow. Argentina possesses the most mature data-protection framework in Latin America — the only one with European Union adequacy since 2003 ¹⁴⁶, reaffirmed in 2024 ¹⁴⁷ — which earns it the only Level 3 of Dimension 1 on its own legislative merit (1.1). But that same country, in the same period, commits to the recognition of the United States as an adequate jurisdiction, bringing the protection of cross-border flows down to Level 1 (1.3). The contrast is not accidental: the Law No. 25326 regime was designed looking towards Europe — it is a transplant of the European standard — and adequacy flows towards Argentina (inbound recognition), while the new US adequacy flows from Argentina towards the hegemonic jurisdiction of platforms (outbound cession). Argentina knows how to write European-class data laws, but at the decisive moment it cedes sovereignty over the outflow of those data to where the platforms that exploit them reside. The paradox extends to 1.4: the country that best legislates the data point is also the one that least exploits it economically.

4.6 Structural and multi-actor constraints

The multi-actor analysis confirms these patterns. The government of the period prioritises deregulation and the attraction of foreign investment (RIGI) over the construction of sovereign capacity. The large foreign platforms capture cloud growth (AWS, OpenAI/Sur Energy) ¹⁴⁸ and acquire domestic champions (Auth0→Okta) ¹⁴⁹, in a pattern that the framework reads as corporate capture and dependency penalty. Civil society and academia sustain real capacity — civic-tech, CONICET, the free university system — but without budget or retention: the most capable talent emigrates ¹⁵⁰ and scientific investment collapses ¹⁵¹. The dominant geopolitical constraint is the realignment with the United States, which materialises the sovereignty cost of Principle #7. By Principle #6, these circumstances explain the pattern but do not raise any rating.

4.7 Prospective synthesis

Should the deregulation trajectory be sustained through 2027 — fiscal cuts in science and technology, deepening of US adequacy, absence of legislative modernisation — Argentina’s average score would tend to decline from the current 2.00, driven by additional erosion in Dimensions 1 and 4 and by the downward pressure already noted in 2.1 (collapse of the Fuegian assembly base) and 4.1 (depletion of the research stock). Chapter 5 develops the scenarios and actions that could reverse this direction.

Chapter 5 — Conclusions and Recommendations

5.1 Five principal conclusions

First: Argentina is a country of mid-to-low-grade digital sovereignty (2.00 / 5.0) without a single competent indicator. The matrix records no Level 4 or 5; its two high points (1.1 and 4.3) reach Level 3, and two low points (1.3 and 1.4) fall to Level 1. The country systematically recognises its deficits — it is ‘aware’ in ten of sixteen indicators — but awareness has not translated into effective capacity ¹⁵².

Second: data ownership is the central fracture. With an average of 1.75, Dimension 1 concentrates the Argentine weakness, not for absence of a legal framework but for its paradoxical use: a sophisticated protection regime (1.1) that does not retain data territorially (1.2), cedes them to the hegemonic jurisdiction (1.3), and does not capture their value (1.4) ¹⁵³.

Third: structural dependence is cross-cutting and concentrated in infrastructure and capacity. Dimensions 2 and 4 show that Argentine engineering capacity — real and of international scale — is deployed on others’ rails: hardware assembled but not manufactured, software with foreign upstream, an industry that exports services, and exports its talent ¹⁵⁴.

Fourth: the deregulation of the period operates as a ceiling factor, not as context. US adequacy (1.3), normative dismantling (3.1), and fiscal collapse (4.1, 4.4) are active policies that the framework registers as a downward direction, not as mitigating circumstances ¹⁵⁵.

Fifth: Argentina groups with Brazil, separated by direction. The closest regional comparator surpasses Argentina in the indicators where it builds (domestic ERP, AI law, effective enforcement), while Argentina retains its historical advantage only where it inherited capacity (1.1). Directionality — construction versus dismantling — is the decisive separator ¹⁵⁶.

5.2 Five recommendations

1. To the Congreso de la Nación: enact the data-protection reform within the term of the next ordinary session. The modernising bill (successor to Message 87/2023, lost for lack of consideration) must enter into force with regulated breach notification, impact assessments, the data-protection officer, and, non-negotiably, a fine cap no lower than 2% of the offender’s annual revenue, to restore the deterrence that the USD 70–100 scale has lost ¹⁵⁷. Without updating the cap, indicators 1.1 and 3.2 will remain capped at Level 3 and Level 2 respectively.
2. To the Executive and the Cancillería: condition the Framework Agreement’s US adequacy commitment on equivalent protection guarantees. In the short term, before the operational implementation of the Agreement on Reciprocal Trade and Investment, the Executive should incorporate safeguards — redress mechanisms for data subjects and limitation of extraterritorial access — that mitigate the sovereignty cost that Principle #7 penalises ¹⁵⁸. Without it, indicator 1.3 will remain collapsed at Level 1.
3. To the Ministry of Economy and the Secretariat of Innovation, Science and Technology: align budget with strategy and restore the path of Law No. 27614. Within the term of the next national budget (ending the two-year carryover), the inter-ministerial AI roundtable, and the National AI Plan should be endowed with their own budget allocation, and the suspended progressivity articles of Law No. 27614 should be reactivated ¹⁵⁹. Indicator 4.4 will not exceed Level 2 while the strategy lacks a living budget.
4. To the private sector and the promotion agencies: orient the Knowledge Economy incentives towards horizontal substitution and the foundational layer. In the medium term, the tax benefits of Law No. 27506 should be conditioned on the generation of product — not only export services — and on the retention of intellectual property in the country, to reverse the foreign-acquisition pattern exemplified by the Auth0→Okta case ¹⁶⁰. This is a prerequisite for indicator 4.3 to move towards Level 4.
5. To academia and CONICET: institutionalise talent retention and production in frontier venues. In the medium and long term, the restoration of doctoral scholarships and the creation of retention incentives and of incentives to publish in top-tier venues — linked to the already-existing sovereign infrastructure (Clementina XXI, QUANTEC) — are a condition for moving indicators 4.1 and 4.2 ¹⁶¹.

5.3 Future trajectory: three scenarios

Favourable scenario. If Congress enacted the data reform with deterrent caps, the Executive introduced safeguards to US adequacy and the budget restored the science-and-technology path, Argentina could recover Level 4 in 1.1 and Level 3 in 1.3 and 3.2, raising the average score towards 2.3–2.5 over a horizon of three to five years.

Continuity scenario. Should current trends hold — strategy without budget, stalled legislative modernisation, US adequacy in force — the score would hold around 2.00, with the industrial strength (4.3) compensating for the gradual erosion in other areas.

Unfavourable scenario. If deregulation were to deepen — collapse of the Fuegian assembly base, depletion of the research stock, statutory codification of US adequacy — the score would decline towards 1.7–1.8, with indicator 2.1 sliding to Level 1 and downward pressure across the whole of Dimension 4.

5.4 Future research questions

This report leaves open five lines that the evidence and time limitations did not allow to resolve. First: what is the emigration rate specific to doctorates in computer science and artificial intelligence, today sealed as a gap for lack of a Tier-1 source? Second: what effective share of public software spending corresponds to providers of national origin, a figure that neither COMPR.AR nor the AGN segments? Third: what are the rates of judicial confirmation and of effective collection of the administrative fines of the AAIP and the competition authority? Fourth: what operational impact will the new architecture of Decree 941/2025 (National Cybersecurity Centre, Federal Cyberintelligence Agency) have once it produces measurable activity? Fifth: how will Argentine participation in international technical standards evolve if the URL_BLOCKED items from ITU and 3GPP documentary databases, which the verifier could not access, are recovered?

References (by Dimension)

The references are grouped by dimension and list, in ascending order, each evidence identifier actually cited in the body of the report. The complete library is kept in evidence_base_UNGS_2026.json. Corpus access date: 2026-05-29.

Dimension 1 — Data ownership

• ¹⁶² Law No. 25326 on Personal Data Protection (art. 12; 2000 fine scale). Regulation, Tier-1. Source: infoleg.gob.ar.
• ¹⁶³ Decree 1558/2001, implementing Law No. 25326 (in force, designates the enforcement authority). Regulation, Tier-1. Source: infoleg.gob.ar.
• ¹⁶⁴ Agencia de Acceso a la Información Pública (AAIP) — regulator with the National Directorate for the Protection of Personal Data. Regulation, Tier-1. Source: argentina.gob.ar/aaip.
• ¹⁶⁵ Data-protection modernisation bill (Message 87/2023), loss of parliamentary status. Policy, Tier-1. Source: HCDN.
• ¹⁶⁶ AAIP Resolution 47/2018 — security measures without geographic restriction. Regulation, Tier-1. Source: argentina.gob.ar/aaip.
• ¹⁶⁷ Official AAIP guidance on adequacy; United States absent; EU adequacy reaffirmed January 2024. Report, Tier-1. Source: argentina.gob.ar/aaip.
• ¹⁶⁸ Law No. 27699 — ratification of Convention 108+ (2022). Regulation, Tier-1. Source: infoleg.gob.ar.
• ¹⁶⁹ USTR Fact Sheet on the US–Argentina Framework Agreement (13 Nov. 2025). Policy, Tier-1. Source: ustr.gov.
• ¹⁷⁰ AAIP 2022 annual figures (491 case files, 52 sanctions, ~USD 30,621). Data, Tier-1. Source: argentina.gob.ar/aaip.
• ¹⁷¹ Gap — absence of breach notification, DPIA, DPO, and extraterritorial clause in the text in force. Gap, Tier-1.
• ¹⁷² BCRA Communication A 7724 — prudential regime for third-party control. Regulation, Tier-1. Source: bcra.gob.ar.
• ¹⁷³ ARSAT’s Tier III data centre — residual sovereign capacity. Report, Tier-1. Source: arsat.com.ar.
• ¹⁷⁴ Executive reform bill (2023) — preserves the transfer model. Policy, Tier-2.
• ¹⁷⁵ Reform bill 1948-D-2025 — continuity of the non-localising approach. Policy, Tier-1. Source: HCDN.
• ¹⁷⁶ Installed domestic IT capacity (~32 MW). Data, Tier-3.
• ¹⁷⁷ OpenAI/Sur Energy 500 MW project under the RIGI. CaseStudy, Tier-2.
• ¹⁷⁸ AWS Local Zone Buenos Aires — presence under foreign jurisdiction. Report, Tier-2.
• ¹⁷⁹ RIGI/Super RIGI — incentives for foreign-controlled infrastructure. Policy, Tier-1.
• ¹⁸⁰ Partial privatisation (49%) of ARSAT. Policy, Tier-1.
• ¹⁸¹ Cross-border personal-data regime (Law No. 25326 art. 12) based on transfers. Regulation, Tier-1.
• ¹⁸² BCRA Communication A 8401 — update of the sectoral regime. Regulation, Tier-1.
• ¹⁸³ Decree 1558/2001 — the regulator’s adequacy-assessment power. Regulation, Tier-1.
• ¹⁸⁴ Disposition 60-E/2016 — model contractual clauses. Regulation, Tier-1.
• ¹⁸⁵ AAIP Resolution 34/2019 — adequacy list; US absent. Regulation, Tier-1.
• ¹⁸⁶ AAIP Resolution 198/2023 — model transfer clauses. Regulation, Tier-1.
• ¹⁸⁷ Joint Statement of the US–Argentina Framework (13 Nov. 2025). Policy, Tier-3. Source: whitehouse.gov.
• ¹⁸⁸ Signing of the Agreement on Reciprocal Trade and Investment (5 Feb. 2026). Policy, Tier-1. Source: cancilleria.gob.ar.
• ¹⁸⁹ EU adequacy maintained since 2003, revalidated January 2024. Policy, Tier-2.
• ¹⁹⁰ Historical operation of US Big Tech via contractual clauses. Report, Tier-2.
• ¹⁹¹ Gap — absence of transfer-enforcement statistics. Gap, Tier-1.
• ¹⁹² Decree 117/2016 — open-data programme on a transparency logic. Regulation, Tier-1.
• ¹⁹³ Law No. 27275 on access to public information. Regulation, Tier-1.
• ¹⁹⁴ Decree 780/2024 — restriction of the scope of active transparency. Regulation, Tier-1.
• ¹⁹⁵gob.ar portal — 1,235 datasets from 42 agencies. Data, Tier-1.
• ¹⁹⁶ PAIS tax — consumption tax repealed in December 2024. CaseStudy, Tier-1.
• ¹⁹⁷ CNDC — digital-markets study group without sanctioning power. CaseStudy, Tier-1.
• ¹⁹⁸ CNDC — eleven concentrated markets, none a digital-native platform. CaseStudy, Tier-1.
• ¹⁹⁹ Civic-tech ecosystem reusing public data. CaseStudy, Tier-2.
• ²⁰⁰ Gap — absence of an operative B2G mandate. Gap, Tier-1.
• ²⁰¹ Gap — absence of recognition of data as a factor of production. Gap, Tier-1.
• ²⁰² Gap — OECD Pillar One and Pillar Two not implemented. Gap, Tier-1.
• ²⁰³ Gap — absence of institutional data trusts. Gap, Tier-2.

Dimension 2 — Digital infrastructure

• ²⁰⁴ Compre Argentino (Law No. 27437) — public-procurement preference. Regulation, Tier-1.
• ²⁰⁵ Tierra del Fuego regime (Law No. 19640) — assembly (~93% of phones, AC, TV). Report, Tier-2.
• ²⁰⁶ Decree 333/2025 — mobile-phone tariff reduction 8%→0% by January 2026. Regulation, Tier-1.
• ²⁰⁷ RIGI — enclave model without a technology-transfer obligation. Policy, Tier-1.
• ²⁰⁸ Knowledge Economy (Law No. 27506) — benefits to software/services. Regulation, Tier-1.
• ²⁰⁹ Design-only semiconductor capacity (INTI/IDME), no wafer plant. Report, Tier-2.
• ²¹⁰ Mirgor Group — suspension of ~360 workers. CaseStudy, Tier-2.
• ²¹¹ CTI Guidelines 2025–2027 — omission of microelectronics/semiconductors. Policy, Tier-1.
• ²¹² Desktop OS share (Windows 81.64%; Linux 2.21%). Data, Tier-3.
• ²¹³ Mobile market >99.97% foreign. Data, Tier-3.
• ²¹⁴ State Huayra GNU/Linux distribution (EDUCAR). CaseStudy, Tier-2.
• ²¹⁵ Suspension of Conectar Igualdad / Educ.ar (‘construction mode’). CaseStudy, Tier-1.
• ²¹⁶ Decree 963/2024 — intervention of EDUC.AR S.E. Regulation, Tier-1.
• ²¹⁷ National Public Cloud (ARSAT) on open-source code. Report, Tier-1.
• ²¹⁸ ARSAT runs its NOC on Red Hat OpenShift (foreign control plane). CaseStudy, Tier-2.
• ²¹⁹ ONTI Public Software initiative. Policy, Tier-1.
• ²²⁰ ONTI Disposition 2/2019 — code sharing under open licences. Regulation, Tier-1.
• ²²¹ Santa Fe provincial free-software law (Law No. 12360). Regulation, Tier-2.
• ²²² Database market dominated by Oracle/SAP/Microsoft/IBM. Data, Tier-3.
• ²²³ Official argob repositories (43 repositories). Data, Tier-1.
• ²²⁴ Mi Argentina — state platform, 21 million registered users. CaseStudy, Tier-1.
• ²²⁵ Software/IT-services exports USD 2,674M (2024), 46.9% to the US. Data, Tier-3.
• ²²⁶ Law No. 27506 Knowledge Economy (promotion). Regulation, Tier-1.
• ²²⁷ Mercado Libre — national-download leader 2024 (11.7M). Data, Tier-3.
• ²²⁸ Mercado Pago — 50M+ active users LATAM, USD 8,600M revenue. Data, Tier-3.
• ²²⁹ Digital banking — 88% across three domestic neobanks. Data, Tier-3.
• ²³⁰ Foreign horizontal consumer categories (WhatsApp 93%, Instagram 86.7%, TikTok 58.4%). Data, Tier-3.
• ²³¹ Search — Google 94.01%. Data, Tier-3.
• ²³² Auth0→Okta acquisition. CaseStudy, Tier-3.
• ²³³ Gap — ERP/CRM without auditable domestic share. Gap, Tier-2.
• ²³⁴ar (Disposition 1/2021). Regulation, Tier-1.
• ²³⁵ar — 438 incidents in 2024 (61% state sector). Data, Tier-1.
• ²³⁶ Administrative Decision 641/2021 — minimum security requirements and 48h notification. Regulation, Tier-1.
• ²³⁷ Decree 941/2025 — National Cybersecurity Centre and Federal Cyberintelligence Agency. Regulation, Tier-1.
• ²³⁸ Leak of the national driver’s-licence database (~5.7–6M, 1.25 TB, April 2024). CaseStudy, Tier-2.
• ²³⁹ Defacement of Mi Argentina/SUBE (Dec. 2024), no 2FA on central sites. CaseStudy, Tier-2.
• ²⁴⁰ Recurring RENAPER incidents. CaseStudy, Tier-2.
• ²⁴¹ Gap — absence of sovereign cryptographic research and a security industry. Gap, Tier-1.
• ²⁴² Gap — absence of documented sovereign offensive/red-team capacity. Gap, Tier-1.

Dimension 3 — Digital governance

• ²⁴³ Law No. 26388 on cybercrime (2008). Regulation, Tier-1.
• ²⁴⁴ Law No. 25506 on electronic signature (2001). Regulation, Tier-1.
• ²⁴⁵ DNU 302/2024 — repeal of art. 15 of Law No. 27078. Regulation, Tier-1.
• ²⁴⁶ AI governance — non-binding AAIP programme. Policy, Tier-1.
• ²⁴⁷ ‘Low-regulation hub’ positioning for AI. Analysis, Tier-2.
• ²⁴⁸ Ministry of Deregulation — 543 measures / 2,519 norms / 15,144 articles (verified). Data, Tier-1.
• ²⁴⁹ Absence of a platform statute; intermediary-liability bill without enactment. Policy, Tier-2.
• ²⁵⁰ Cybersecurity by DNC dispositions, without a parliamentary statute. Regulation, Tier-1.
• ²⁵¹ Discontinuation of the national AI strategy. Policy, Tier-2.
• ²⁵² AAIP statutory fine scale (ARS 1,000–100,000). Regulation, Tier-1.
• ²⁵³ AAIP Resolution 126/2024 — tiering of sanctions. Regulation, Tier-1.
• ²⁵⁴ Shelving of the CNDC investigation against WhatsApp/Meta (2 Jul. 2025). CaseStudy, Tier-2.
• ²⁵⁵ Largest sanction against a Big Tech firm (Google, ARS 280,000, 2020). CaseStudy, Tier-2.
• ²⁵⁶ CNDC 2024 — 89 merger decisions, one procedural fine, zero conduct sanctions. Data, Tier-1.
• ²⁵⁷ IRAM — sole representative before ISO and (with CEA/AEA) IEC; COPANT/AMN. Report, Tier-2.
• ²⁵⁸ UTN Santa Fe — editors of five Y-series Recommendations of the ITU-T’s SG20. CaseStudy, Tier-2.
• ²⁵⁹ Verified absence of an Argentine vice-chair in the ITU-T’s SG20 (2025-2028). Data, Tier-2.
• ²⁶⁰ ISO/IEC 27002:2022 — Argentine editor (IRAM SC 27). CaseStudy, Tier-2.
• ²⁶¹ CITEL — chair of the Steering Committee (2018) and rapporteurships. CaseStudy, Tier-2.
• ²⁶² Verified absence of an Argentine organisation among the 329 members of the W3C. Data, Tier-2.
• ²⁶³ US–Argentina Framework Agreement with data adequacy. Policy, Tier-2.
• ²⁶⁴ Participation in the OEWG without co-sponsorship of substantive resolutions. Report, Tier-2.
• ²⁶⁵ Election of Beatriz Anchorena to the chairmanship of the Convention 108 Committee. CaseStudy, Tier-2.
• ²⁶⁶ Data bill with extraterritorial scope / anti-CLOUD Act (1948-D-2025). Policy, Tier-1.

Dimension 4 — Digital capacity

• ²⁶⁷ R&D investment 0.216% of GDP (2024), -31.3% real, 55.4% below Law No. 27614. Data, Tier-3.
• ²⁶⁸ Suspension of the progressivity articles of Law No. 27614. Regulation, Tier-1.
• ²⁶⁹ Clementina XXI — sovereign HPC, 15.3 PFLOPs, TOP500 #82. Data, Tier-2.
• ²⁷⁰ QUANTEC — CNEA-CONICET superconducting-qubit programme (4-6 qubits). Report, Tier-1.
• ²⁷¹ MinCyT quantum-infrastructure call. Policy, Tier-1.
• ²⁷² CONICET — #1 LatAm / #20 worldwide among governmental research bodies. Data, Tier-2.
• ²⁷³ Argentine output at top-tier venues: low, dependent on foreign co-authorship. Analysis, Tier-3.
• ²⁷⁴ CONICET doctoral scholarships cut ~30% (950 in 2024). Data, Tier-2.
• ²⁷⁵ S&T investment ~0.2% of GDP (2002 level). Data, Tier-2.
• ²⁷⁶ University pipeline (~6,500 engineering graduates/year; UTN 42.75%). Data, Tier-2.
• ²⁷⁷ Brain drain (top-30 emitter; ~30,000 scientists/engineers in the US). Data, Tier-2.
• ²⁷⁸ Remote-work model for foreign clients. Analysis, Tier-2.
• ²⁷⁹ RAICES — diaspora repatriation policy (Law No. 26421). Policy, Tier-1.
• ²⁸⁰ No Argentine university in the global CS top 500 (UBA #555). Data, Tier-3.
• ²⁸¹ Software industry USD 22,221M (2024), 158,179 jobs. Data, Tier-3.
• ²⁸² SBC mix 2022 (software 33%, services 30%, architecture 22%, R&D 8%); USD 8,047M. Data, Tier-2.
• ²⁸³ Global software share 0.6% (2011) → 0.3% (2021). Data, Tier-2.
• ²⁸⁴ Auth0 — acquired by Okta (~USD 6,500M, 2021). CaseStudy, Tier-3.
• ²⁸⁵ Venture capital USD 1,337M (2021) → USD 412M (2024). Data, Tier-2.
• ²⁸⁶ OpenAI/Sur Energy data centre under the RIGI. CaseStudy, Tier-2.
• ²⁸⁷ The sector tends more towards development than research. Analysis, Tier-2.
• ²⁸⁸ >140,000 formal software employees (exceeds automotive+oil+mining). Data, Tier-2.
• ²⁸⁹ Law No. 27738 — National CTI Plan 2030. Regulation, Tier-1. Source: boletinoficial.gob.ar.
• ²⁹⁰ Strategic Guidelines 2025–2027. Policy, Tier-1.
• ²⁹¹ Inter-ministerial AI roundtable ‘without its own budget allocation’. Regulation, Tier-1.
• ²⁹² IDB loan of USD 35M as the only funding dedicated to AI. Policy, Tier-2.
• ²⁹³ Digital Agenda 2030 (Decree 996/2018). Regulation, Tier-1.
• ²⁹⁴ DNU 70/2023 — economic emergency, 366 norms repealed/modified. Regulation, Tier-1.
• ²⁹⁵ MinCyT — create/downgrade/restore/downgrade cycle. Report, Tier-2.
• ²⁹⁶ S&T budget function -50.6% cumulative real 2024-2026. Data, Tier-1.
• ²⁹⁷ Conectar Igualdad — cancellation/relaunch across four administrations. CaseStudy, Tier-2.
• ²⁹⁸ ‘Low-regulation hub’ positioning. Policy, Tier-2.
• ²⁹⁹ Fundar — the ‘Achilles’ heel’ of the AI strategy (university stock without investment). Analysis, Tier-2.
• ³⁰⁰ Budget carryover for two consecutive years. Report, Tier-2.

Appendix A — Inventory of Cited Evidence

This report cites 120 distinct evidence identifiers from the UNGS_2026 corpus (out of a total of 241 integrated pieces of evidence). All cited identifiers exist and are traceable in evidence_base_UNGS_2026.json. The following table summarises the composition of the cited evidence by type and source tier; the detail by identifier appears in the preceding References section.

Table A.1. Composition of cited evidence by type (approximate count).

Table A.2. Distribution by source tier.

Table A.3. Count of integrated evidence by indicator (full corpus, from evidence_index_UNGS_2026.json).

Appendix B — Documented Gaps

The UNGS_2026 corpus records 31 gaps under a strict policy (gap_policy_strict): confirmed absences of evidence after three rounds of search in Tier-1 sources, treated as evidence of a structural absence. They are enumerated by dimension.

Dimension 1 (9 gaps)

• 1 — GDPR-era modernisation absent: no regulated breach notification, mandatory DPIA, DPO figure, or extraterritorial clause in the text in force.
• 2 — No localisation-enforcement actions (2024–2026): a structural absence, there is no general mandate to enforce.
• 3 — No quantitative cross-border transfer-enforcement statistics published by the AAIP.
• 4 (×6) — Antitrust over data monopolies non-existent; open-data outcome audit pending; operative B2G mandate absent; institutional data trusts absent; OECD Pillar One/Two not implemented; recognition of data as a factor of production absent.

Dimension 2 (9 gaps)

• 1 (×2) — No Tier-1 data on domestic-vs-imported hardware share in public procurement; no active strategic hardware-stockpile programme.
• 2 (×3) — No Tier-1 quantification of public spending on foreign proprietary-provider licences; no documented event of sanctions/export controls on foundational software; no domestic capacity in kernels, hypervisors, or cryptographic libraries at scale.
• 3 (×2) — No auditable ERP/CRM/SCM breakdown by provider origin; no official metrics of the domestic-vs-foreign share in public spending on application software.
• 4 (×2) — No sustained domestic academic cryptographic publication at top-tier venues; no state red-team programme with public outputs.

Dimension 3 (9 gaps)

• 1 — No binding national framework for coordinated vulnerability disclosure.
• 2 (×2) — No systematic data on judicial confirmation/revocation or decision times; no quantification of case-to-decision time or fine-collection rate.
• 3 (×3) — No surfaceable direct Argentine authorship of an IETF RFC; no declared Argentine SEPs or participation in post-quantum standardisation; no documented official technical positions on disputed standards (‘New IP’, AI security, quantum communication).
• 4 (×3) — Argentina absent from the AI-safety declarations (Bletchley, Seoul, Paris); absent from the 65 initial signatories of the Convention on Cybercrime; no signature of the China-led Global Data Security Initiative.

Dimension 4 (4 gaps)

• 1 — No Tier-1 source with systematic annual counts of Argentine publications at top-tier AI venues.
• 2 — No disaggregated brain-drain rate in computer-science/AI subfields or directional flow of postgraduate students.
• 3 — No quantitative comparison of gross value added per worker vs. the OECD (PDF not retrievable).
• 4 — No Tier-1 dashboard of digital KPIs in the Presidency, JGM, or Economy tracking the CTI Plan 2030.

Appendix C — Authorship, Cooperation and Traceability

This Argentina assessment is a product of academic cooperation developed under the Global South Academic Forum, with the following division of roles:

• Global South Insights (GSI) — DSI Assessment Team. Design and specification of the Digital Sovereignty Index methodological framework (the 4×4 analytical structure: four dimensions, sixteen indicators, a 1–5 scale, seven evidence types, seven principles, and the decision tree), coordination of the international assessment, and compilation of the annual global index.
• National University of General Sarmiento (UNGS) — University Programme on Digital Sovereignty. Implementation of the Argentina assessment as an associate university: evidence collection from national sources, local application of the assessment pipeline in accordance with the DSI specifications, and drafting of the analysis in Argentine academic Spanish.
• Global South Academic Forum (GSAF). Institutional framework of the cooperation.
• Artificial-intelligence assistance. Evidence processing, verification, and drafting were assisted by the Claude model (Anthropic) — Co-authored-by: Claude.

The application of the specifications to the Argentina assessment — what national evidence is sufficient, what evidentiary weight corresponds to each local regulatory action, and how the analysis is written in Spanish — constitutes UNGS’s substantive contribution to the global index, in line with the methodology established by GSI.

Corpus traceability. Run: UNGS_2026. Phase-gate results: Phase 1 (collection, 373 pieces of evidence) → verification (91 removed) → integration (41 duplicates removed, 241 integrated + 31 gaps) → Phase 4 (assessment, 16 indicators) → Phase 5 (generation of this report). The evidence base (evidence_base_UNGS_2026.json) and the indexes (evidence_index_UNGS_2026.json) constitute the audit trail; each [AR-EV-NNN] citation in the report is verifiable against a corpus URL. Report generation date: 29 May 2026. The 2025 assessment is preserved as a comparative baseline.

Note

¹ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

² AR-EV-0212: ‘Argentina’s software industry reached USD 22,221 million in revenue in 2024 (+13.1% interannual)…’ Data. https://www.itsitio.com/ar/software/software-argentino-bate-records/. Accessed 2026-05-29.; AR-EV-0101: ‘El segmento de digital banking argentino está concentrado en tres jugadores domésticos: Ualá (6…’ Data. https://fintechnews.am/fintech-argentina/52228/argentinas-top-3-digital-banks-capture-nearly-90-market-share/. Accessed 2026-05-29.

³ AR-EV-0076: ‘Huayra GNU/Linux es el sistema operativo libre desarrollado en EDUCAR Sociedad del Estado, descrito…’ CaseStudy. https://huayra.educar.gob.ar/. Accessed 2026-05-29.; AR-EV-0079: ‘ARSAT desplegó la etapa 1 de la Nube Pública Nacional el 1° de abril de 2021, construida sobre…’ CaseStudy. https://www.canal-ar.com.ar/29335-ARSAT-lanzo-la-Nube-Publica-Nacional-y-ofrece-infraestructura-y-servicios-a-demanda.html. Accessed 2026-05-29.; AR-EV-0093: ‘Mi Argentina, la plataforma de identidad digital ciudadana, supera los 21 millones de personas…’ CaseStudy. https://www.argentina.gob.ar/noticias/se-renueva-mi-argentina-con-mas-y-mejores-servicios-para-la-ciudadania. Accessed 2026-05-29.

⁴ AR-EV-0031: ‘El 13 de noviembre de 2025, los presidentes Donald J. Trump y Javier Milei suscribieron el Joint…’ Policy. https://www.whitehouse.gov/briefings-statements/2025/11/joint-statement-on-framework-for-a-united-states-argentina-agreement-on-reciprocal-trade-and-investment/. Accessed 2026-05-29.; AR-EV-0032: ‘El 5 de febrero de 2026 en Washington D.C., la República Argentina y los Estados Unidos…’ Policy. https://www.cancilleria.gob.ar/es/destacados/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones-reciprocos. Accessed 2026-05-29.

⁵ AR-EV-0054: ‘No se identifica fuente Tier-1 que documente la existencia de un mandato general operativo de…’ Gap. Accessed 2026-05-29.; AR-EV-0055: ‘No se identifica fuente Tier-1 que documente reconocimiento estatal explícito de los datos como…’ Gap. Accessed 2026-05-29.; AR-EV-0057: ‘No se identifica fuente Tier-1 que documente la implementación por parte de Argentina de mecanismos…’ Gap. Accessed 2026-05-29.

⁶ AR-EV-0064: ‘El Instituto Nacional de Tecnología Industrial (INTI), a través de su área de Micro y…’ CaseStudy. https://www.inti.gob.ar/areas/desarrollo-tecnologico-e-innovacion/areas-de-conocimiento/micro-y-nanotecnologias. Accessed 2026-05-29.; AR-EV-0080: ‘ARSAT desplegó Red Hat OpenShift AI para apoyar operaciones de centro de operaciones de red (NOC)…’ CaseStudy. https://www.redhat.com/en/success-stories/arsat. Accessed 2026-05-29.; AR-EV-0200: ‘Argentina is in the top 30 nations with highly-skilled emigrants according to OECD data, with…’ Data. https://www.untref.edu.ar/mundountref/argentina-se-convirtio-en-un-polo-de-emigracion. Accessed 2026-05-29.

⁷ AR-EV-0133: ‘The Ministerio de Desregulación y Transformación del Estado (created July 2024 under Federico…’ Data. https://www.argentina.gob.ar/desregulacion. Accessed 2026-05-29.

⁸ AR-EV-0235: ‘La Función Ciencia y Tecnología del Presupuesto Nacional cayó un 11,4% adicional en el primer…’ Data. https://ciicti.org/el-2026-llego-con-mas-recortes-presupuestarios-a-la-ciencia-argentina/. Accessed 2026-05-29.

⁹ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

¹⁰ AR-EV-0001: ‘El artículo 12 de la Law No. 25326 prohíbe la transferencia de datos personales de cualquier tipo con…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/60000-64999/64790/texact.htm. Accessed 2026-05-29.

¹¹ AR-EV-0002: ‘El Decree 1558/2001, promulgado el 29 de noviembre de 2001 y publicado en el Boletín Oficial el 3…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/verNorma.do?id=70368. Accessed 2026-05-29.

¹² AR-EV-0003: ‘La AAIP se autodefine en su sitio oficial como garante de la protección de datos personales y la…’ Regulation. https://www.argentina.gob.ar/aaip/datospersonales. Accessed 2026-05-29.

¹³ AR-EV-0005: ‘La AAIP aprobó por Resolución 47/2018 (publicada 25-07-2018, vigente) las Medidas de Seguridad…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/310000-314999/312662/norma.htm. Accessed 2026-05-29.; AR-EV-0028: ‘La Resolución AAIP 198/2023, publicada el 18 de octubre de 2023 y firmada por la directora Beatriz…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/296189/20231018. Accessed 2026-05-29.; AR-EV-0141: ‘La Resolución AAIP 126/2024, publicada en el Boletín Oficial el 24 de mayo de 2024 y en vigor desde…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/395000-399999/399750/norma.htm. Accessed 2026-05-29.

¹⁴ AR-EV-0010: ‘Según el Informe Anual 2022 de la AAIP, la autoridad inició 491 expedientes por presuntas…’ Data. https://iapp.org/news/a/la-autoridad-de-proteccion-de-datos-de-argentina-publica-su-informe-anual-2022. Accessed 2026-05-29.

¹⁵ AR-EV-0007: ‘La AAIP publica como guía oficial vigente que los países considerados con legislación adecuada son…’ Report. https://www.argentina.gob.ar/aaip/datospersonales/transferencias-internacionales. Accessed 2026-05-29.

¹⁶ AR-EV-0008: ‘La Law No. 27699, sancionada el 9 de noviembre de 2022 y publicada en el Boletín Oficial el 30 de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/375000-379999/375738/norma.htm. Accessed 2026-05-29.

¹⁷ AR-EV-0004: ‘El Proyecto de Ley de Protección de Datos Personales presentado por el Poder Ejecutivo Nacional en…’ Policy. https://www.argentina.gob.ar/aaip/datospersonales/proyecto-ley-datos-personales. Accessed 2026-05-29.

¹⁸ AR-EV-0011: ‘El régimen vigente de la Law No. 25326 no contempla obligaciones operativas de notificación reglada de…’ Gap. Accessed 2026-05-29.

¹⁹ AR-EV-0141: ‘La Resolución AAIP 126/2024, publicada en el Boletín Oficial el 24 de mayo de 2024 y en vigor desde…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/395000-399999/399750/norma.htm. Accessed 2026-05-29.

²⁰ AR-EV-0010: ‘Según el Informe Anual 2022 de la AAIP, la autoridad inició 491 expedientes por presuntas…’ Data. https://iapp.org/news/a/la-autoridad-de-proteccion-de-datos-de-argentina-publica-su-informe-anual-2022. Accessed 2026-05-29.

²¹ AR-EV-0145: ‘El 19 de diciembre de 2025 la AAIP inició una investigación de oficio ante una presunta filtración…’ CaseStudy. https://www.argentina.gob.ar/noticias/la-aaip-inicio-una-investigacion-de-oficio-ante-presunta-filtracion-masiva-de-datos. Accessed 2026-05-29.

²² AR-EV-0021: ‘El régimen argentino de transferencias internacionales de datos personales se rige por el artículo…’ Regulation. https://www.argentina.gob.ar/transferencias-internacionales. Accessed 2026-05-29.; AR-EV-0005: ‘La AAIP aprobó por Resolución 47/2018 (publicada 25-07-2018, vigente) las Medidas de Seguridad…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/310000-314999/312662/norma.htm. Accessed 2026-05-29.

²³ AR-EV-0012: ‘La Comunicación A 7724 del BCRA, vigente desde el 6 de septiembre de 2023, establece requisitos…’ Regulation. https://www.grantthornton.com.ar/en/insights/articles/2023/communication-a7724-bcra/. Accessed 2026-05-29.; AR-EV-0023: ‘El BCRA emitió la Comunicación A 8401 (13/02/2026) — más reciente que la A 7724 — disponible en el…’ Regulation. https://www.bcra.gob.ar/archivos/Pdfs/comytexord/A8401.pdf. Accessed 2026-05-29.

²⁴ AR-EV-0014: ‘El Poder Ejecutivo Nacional presentó al Congreso el 30 de junio de 2023 un proyecto de ley para…’ Policy. https://iapp.org/news/a/se-presento-ante-el-congreso-nacional-argentino-un-nuevo-proyecto-de-ley-para-reemplazar-la-actual-ley-de-proteccion-de-datos-personales. Accessed 2026-05-29.; AR-EV-0015: ‘El proyecto de ley 1948-D-2025, ingresado a la Cámara de Diputados en 2025, propone reemplazar la…’ Policy. https://www4.hcdn.gob.ar/dependencias/dsecretaria/Periodo2025/PDF2025/TP2025/1948-D-2025.pdf. Accessed 2026-05-29.

²⁵ AR-EV-0013: ‘ARSAT opera el Centro Nacional de Datos en Benavídez (Buenos Aires), única instalación del país con…’ Report. https://www.arsat.com.ar/datacenter/. Accessed 2026-05-29.

²⁶ AR-EV-0020: ‘El gobierno anunció en octubre de 2024 un plan de privatización parcial de ARSAT (hasta el 49% del…’ Policy. https://www.infobae.com/economia/2024/10/08/el-gobierno-buscara-privatizar-el-49-de-la-estatal-arsat-que-podria-salir-a-la-bolsa-en-2025/. Accessed 2026-05-29.

²⁷ AR-EV-0016: ‘Argentina tiene 13 data centers comerciales identificados por CABASE con capacidad superior a 1 MW…’ Data. https://www.telesemana.com/blog/2026/05/06/argentina-busca-atraer-14-data-centers-y-ampliar-su-infraestructura-digital-para-la-era-de-la-ia/. Accessed 2026-05-29.

²⁸ AR-EV-0018: ‘AWS anunció en marzo de 2022 Local Zones en seis ciudades latinoamericanas, incluida Buenos Aires…’ Report. https://aws.amazon.com/blogs/publicsector/aws-announces-local-zones-latin-america/. Accessed 2026-05-29.; AR-EV-0017: ‘El 10 de octubre de 2025 Sur Energy (Argentina) y OpenAI (Estados Unidos) firmaron una carta de…’ CaseStudy. https://chequeado.com/investigaciones/mega-data-centers-en-la-patagonia-promesas-millonarias-y-alerta-por-la-falta-de-regulacion/. Accessed 2026-05-29.

²⁹ AR-EV-0019: ‘El Súper RIGI (Message 181/2026 al HCDN) propone exigir inversiones mínimas de US$ 1.000 millones…’ Policy. https://www.cronista.com/economia-politica/rigi-y-super-rigi-que-cambia-que-se-amplifica-y-que-se-elimina/. Accessed 2026-05-29.

³⁰ AR-EV-0001: ‘El artículo 12 de la Law No. 25326 prohíbe la transferencia de datos personales de cualquier tipo con…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/60000-64999/64790/texact.htm. Accessed 2026-05-29.

³¹ AR-EV-0025: ‘El Decreto Reglamentario 1558/2001 (anexo I, art. 12) faculta a la Dirección Nacional de Protección…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/decreto-1558-2001-70368. Accessed 2026-05-29.

³² AR-EV-0026: ‘La Disposición DNPDP 60-E/2016, dictada el 16 de noviembre de 2016, aprueba dos conjuntos de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/265000-269999/267922/norma.htm. Accessed 2026-05-29.

³³ AR-EV-0027: ‘La Resolución AAIP 34/2019, del 22 de febrero de 2019 y firmada por Eduardo Andrés Bertoni…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/202373/20190226. Accessed 2026-05-29.

³⁴ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

³⁵ AR-EV-0041: ‘No se identificó fuente Tier-1 que documente estadísticas cuantitativas específicas del régimen de…’ Gap. Accessed 2026-05-29.

³⁶ AR-EV-0031: ‘El 13 de noviembre de 2025, los presidentes Donald J. Trump y Javier Milei suscribieron el Joint…’ Policy. https://www.whitehouse.gov/briefings-statements/2025/11/joint-statement-on-framework-for-a-united-states-argentina-agreement-on-reciprocal-trade-and-investment/. Accessed 2026-05-29.; AR-EV-0009: ‘El United States Trade Representative (USTR) publicó el 13 de noviembre de 2025 el Fact Sheet del…’ Policy. https://ustr.gov/about/policy-offices/press-office/fact-sheets/2025/november/fact-sheet-united-states-and-argentina-agree-framework-agreement-reciprocal-trade-and-investment. Accessed 2026-05-29.

³⁷ AR-EV-0032: ‘El 5 de febrero de 2026 en Washington D.C., la República Argentina y los Estados Unidos…’ Policy. https://www.cancilleria.gob.ar/es/destacados/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones-reciprocos. Accessed 2026-05-29.

³⁸ AR-EV-0040: ‘Microsoft, en su documentación oficial de cumplimiento publicada en learn.microsoft.com, declara…’ Report. https://learn.microsoft.com/en-us/compliance/regulatory/offering-pdpa-argentina. Accessed 2026-05-29.

³⁹ AR-EV-0042: ‘El Decree 117/2016, suscrito el 12 de enero de 2016, instruye a los ministerios, secretarías y…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/decreto-117-2016-257755. Accessed 2026-05-29.; AR-EV-0043: ‘La Law No. 27275 de Derecho de Acceso a la Información Pública, sancionada el 14 de septiembre de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/265000-269999/265949/norma.htm. Accessed 2026-05-29.; AR-EV-0045: ‘El portal nacional datos.gob.ar registra 1.235 datasets publicados por 42 organizaciones del sector…’ Data. https://datos.gob.ar/. Accessed 2026-05-29.

⁴⁰ AR-EV-0053: ‘Organizaciones civiles argentinas — LA NACION Data junto con ACIJ, Directorio Legislativo y Poder…’ CaseStudy. https://www.lanacion.com.ar/sociedad/periodismo-de-datos-una-iniciativa-y-un-equipo-para-agregar-valor-e-innovar-nid2312192/. Accessed 2026-05-29.

⁴¹ AR-EV-0055: ‘No se identifica fuente Tier-1 que documente reconocimiento estatal explícito de los datos como…’ Gap. Accessed 2026-05-29.

⁴² AR-EV-0054: ‘No se identifica fuente Tier-1 que documente la existencia de un mandato general operativo de…’ Gap. Accessed 2026-05-29.

⁴³ AR-EV-0047: ‘El impuesto PAIS, que añadía una alícuota del 8% sobre suscripciones a servicios digitales del…’ CaseStudy. https://chequeado.com/el-explicador/fin-del-impuesto-pais-que-impacto-tendra-en-las-compras-de-bienes-y-servicios-en-el-exterior-en-el-turismo-y-en-las-importaciones/. Accessed 2026-05-29.

⁴⁴ AR-EV-0057: ‘No se identifica fuente Tier-1 que documente la implementación por parte de Argentina de mecanismos…’ Gap. Accessed 2026-05-29.

⁴⁵ AR-EV-0048: ‘La Comisión Nacional de Defensa de la Competencia (CNDC) creó un Grupo de Investigación y Trabajo…’ CaseStudy. https://www.argentina.gob.ar/noticias/la-cndc-creo-el-grupo-de-investigacion-y-trabajo-sobre-mercados-digitales. Accessed 2026-05-29.; AR-EV-0049: ‘La CNDC investiga 11 mercados de alta concentración: aluminio, acero, petroquímica, comunicaciones…’ CaseStudy. https://www.casarosada.gob.ar/35904-once-mercados-con-altaconcentraci. Accessed 2026-05-29.

⁴⁶ AR-EV-0058: ‘No se identifica fuente Tier-1 que documente la existencia operativa de data trusts, data…’ Gap. Accessed 2026-05-29.

⁴⁷ AR-EV-0044: ‘El Decree 780/2024, firmado el 30 de agosto de 2024 (BO 02-09-2024), reglamentó modificaciones al…’ Regulation. https://www.boletinoficial.gov.ar/detalleAviso/primera/313139/20240902. Accessed 2026-05-29.

⁴⁸ AR-EV-0059: ‘La Law No. 27437 de Compre Argentino y Desarrollo de Proveedores, promulgada en abril de 2018 y…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/310000-314999/310020/norma.htm. Accessed 2026-05-29.; AR-EV-0063: ‘La Law No. 27506 del Régimen de Promoción de la Economía del Conocimiento (publicada en el Boletín…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/320000-324999/324101/norma.htm. Accessed 2026-05-29.

⁴⁹ AR-EV-0060: ‘La Law No. 19640, sancionada en 1972, estableció un régimen aduanero y fiscal especial para Tierra del…’ Regulation. https://prodyambiente.tierradelfuego.gob.ar/regimen-de-promocion-economica-y-fiscal-ley-19-640-2/. Accessed 2026-05-29.

⁵⁰ AR-EV-0062: ‘Argentina no exhibe acuerdos bilaterales de transferencia tecnológica vigentes con jurisdicciones…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/400000-404999/403230/norma.htm. Accessed 2026-05-29.

⁵¹ AR-EV-0063: ‘La Law No. 27506 del Régimen de Promoción de la Economía del Conocimiento (publicada en el Boletín…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/320000-324999/324101/norma.htm. Accessed 2026-05-29.

⁵² AR-EV-0068: ‘Los Lineamientos Estratégicos de Innovación, Ciencia y Tecnología 2025-2027, aprobados por…’ Policy. https://www.argentina.gob.ar/ciencia/plan-nacional-cti/plan-cti. Accessed 2026-05-29.

⁵³ AR-EV-0064: ‘El Instituto Nacional de Tecnología Industrial (INTI), a través de su área de Micro y…’ CaseStudy. https://www.inti.gob.ar/areas/desarrollo-tecnologico-e-innovacion/areas-de-conocimiento/micro-y-nanotecnologias. Accessed 2026-05-29.

⁵⁴ AR-EV-0061: ‘El Decree 333/2025, publicado en el Boletín Oficial el 20 de mayo de 2025, reduce a 8% el Derecho…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/325601/20250520. Accessed 2026-05-29.

⁵⁵ AR-EV-0066: ‘El Grupo Mirgor adquirió en 2021 la operación de Brightstar en Tierra del Fuego, sumando a IATEC y…’ CaseStudy. https://mirgor.com/mirgor-adquiere-brightstar-tierra-del-fuego/. Accessed 2026-05-29.

⁵⁶ AR-EV-0081: ‘La iniciativa de Software Público de la Subsecretaría de Gobierno Digital (ONTI, dependiente de…’ Policy. https://argentina.gob.ar/jefatura/innovacion-publica/ssetic/onti/software-publico. Accessed 2026-05-29.; AR-EV-0082: ‘La Disposición ONTI 2/2019 aprobó el Código de Buenas Prácticas para el desarrollo de software…’ Policy. https://www.boletinoficial.gob.ar/detalleAviso/primera/206660/20190430. Accessed 2026-05-29.; AR-EV-0083: ‘La Provincia de Santa Fe sancionó la Law No. 12360 el 15 de diciembre de 2004, reglamentada por…’ Regulation. https://www.santafe.gob.ar/index.php/web/content/view/full/3601. Accessed 2026-05-29.

⁵⁷ AR-EV-0076: ‘Huayra GNU/Linux es el sistema operativo libre desarrollado en EDUCAR Sociedad del Estado, descrito…’ CaseStudy. https://huayra.educar.gob.ar/. Accessed 2026-05-29.

⁵⁸ AR-EV-0079: ‘ARSAT desplegó la etapa 1 de la Nube Pública Nacional el 1° de abril de 2021, construida sobre…’ CaseStudy. https://www.canal-ar.com.ar/29335-ARSAT-lanzo-la-Nube-Publica-Nacional-y-ofrece-infraestructura-y-servicios-a-demanda.html. Accessed 2026-05-29.

⁵⁹ AR-EV-0086: ‘La organización oficial ‘argob’ en GitHub aloja 43 repositorios; los más populares corresponden a…’ Data. https://github.com/argob. Accessed 2026-05-29.

⁶⁰ AR-EV-0074: ‘El sistema operativo de escritorio dominante en Argentina al mes de abril de 2026 es Windows con…’ Data. https://gs.statcounter.com/os-market-share/desktop/argentina. Accessed 2026-05-29.

⁶¹ AR-EV-0075: ‘El mercado de sistemas operativos móviles en Argentina al mes de abril de 2026 está dominado por…’ Data. https://gs.statcounter.com/os-market-share/mobile/argentina. Accessed 2026-05-29.

⁶² AR-EV-0084: ‘El mercado latinoamericano de sistemas de gestión de bases de datos está dominado por Oracle…’ Data. https://www.informesdeexpertos.com/informes/mercado-latinoamericano-de-sistemas-de-gestion-de-bases-de-datos. Accessed 2026-05-29.

⁶³ AR-EV-0080: ‘ARSAT desplegó Red Hat OpenShift AI para apoyar operaciones de centro de operaciones de red (NOC)…’ CaseStudy. https://www.redhat.com/en/success-stories/arsat. Accessed 2026-05-29.

⁶⁴ AR-EV-0077: ‘In January 2024 the Milei government suspended access to Conectar Igualdad and Educ.ar —…’ CaseStudy. https://www.ambito.com/politica/el-gobierno-bloqueo-las-plataformas-conectar-igualdad-y-educar-n5931668. Accessed 2026-05-29.; AR-EV-0078: ‘El Decree 963/2024, publicado en el Boletín Oficial el 31 de octubre de 2024, designa a Gastón…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/316281/20241031. Accessed 2026-05-29.

⁶⁵ AR-EV-0098: ‘Mercado Libre lideró el ranking de aplicaciones más descargadas en Argentina en 2024 con 11,7…’ CaseStudy. https://mobiletime.la/noticias/23/01/2025/apps-mas-descargadas-2024/. Accessed 2026-05-29.

⁶⁶ AR-EV-0099: ‘Mercado Pago superó los 50 millones de usuarios activos mensuales en LATAM en 2024 y reportó USD…’ Data. https://investor.mercadolibre.com/. Accessed 2026-05-29.

⁶⁷ AR-EV-0101: ‘El segmento de digital banking argentino está concentrado en tres jugadores domésticos: Ualá (6…’ Data. https://fintechnews.am/fintech-argentina/52228/argentinas-top-3-digital-banks-capture-nearly-90-market-share/. Accessed 2026-05-29.

⁶⁸ AR-EV-0093: ‘Mi Argentina, la plataforma de identidad digital ciudadana, supera los 21 millones de personas…’ CaseStudy. https://www.argentina.gob.ar/noticias/se-renueva-mi-argentina-con-mas-y-mejores-servicios-para-la-ciudadania. Accessed 2026-05-29.

⁶⁹ AR-EV-0102: ‘WhatsApp (Meta) tiene una penetración del 93% entre usuarios mayores de 16 años en Argentina, e…’ Data. https://www.infobae.com/tecno/2025/04/04/radiografia-digital-que-hacen-los-argentinos-en-internet-y-en-que-redes-sociales-pasan-mas-tiempo/. Accessed 2026-05-29.

⁷⁰ AR-EV-0103: ‘Google posee el 94,01% del mercado de búsquedas en Argentina a abril de 2026 (Bing 4,13%, Yahoo…’ Data. https://gs.statcounter.com/search-engine-market-share/all/argentina. Accessed 2026-05-29.

⁷¹ AR-EV-0107: ‘No se identificó fuente Tier-1 que documente cifras consolidadas y auditables de participación de…’ Gap. Accessed 2026-05-29.

⁷² AR-EV-0096: ‘El sector argentino de software y servicios informáticos exportó USD 2.674 millones en 2024, un…’ Data. https://cessi.org.ar/2025/05/21/el-software-argentino-genero-mas-de-6-000-empleos-y-alcanzo-un-record-de-exportaciones/. Accessed 2026-05-29.; AR-EV-0097: ‘Argentina’s Law No. 27506 (Régimen de Promoción de la Economía del Conocimiento), in force since 1…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/ley-27506-324101/actualizacion. Accessed 2026-05-29.

⁷³ AR-EV-0104: ‘Auth0, empresa argentina de autenticación digital fundada en 2013, fue adquirida en 2021 por Okta…’ CaseStudy. https://www.infobae.com/economia/2021/06/23/otra-tech-argentina-se-convirtio-en-unicornio-y-es-el-sexto-local-que-hace-y-quien-es-el-millennial-autodidacta-que-la-fundo/. Accessed 2026-05-29.

⁷⁴ AR-EV-0108: ‘La Disposición 1/2021 de la Dirección Nacional de Ciberseguridad crea el Centro Nacional de…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/241077/20210222. Accessed 2026-05-29.

⁷⁵ AR-EV-0109: ‘Durante 2024, el CERT.ar registró 438 incidentes de ciberseguridad, una cifra 15% superior a los…’ Data. https://www.argentina.gob.ar/jefatura/innovacion-ciencia-y-tecnologia/ciberseguridad/informes-de-la-direccion-nacional-de. Accessed 2026-05-29.

⁷⁶ AR-EV-0112: ‘La Decisión Administrativa 641/2021 aprueba los Requisitos Mínimos de Seguridad de la Información…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/350000-354999/351345/norma.htm. Accessed 2026-05-29.

⁷⁷ AR-EV-0114: ‘Por Decree 941/2025 del Poder Ejecutivo (publicado el 2 de enero de 2026 en el Boletín Oficial) se…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/337032/20260102. Accessed 2026-05-29.

⁷⁸ AR-EV-0109: ‘Durante 2024, el CERT.ar registró 438 incidentes de ciberseguridad, una cifra 15% superior a los…’ Data. https://www.argentina.gob.ar/jefatura/innovacion-ciencia-y-tecnologia/ciberseguridad/informes-de-la-direccion-nacional-de. Accessed 2026-05-29.

⁷⁹ AR-EV-0120: ‘No se identificó fuente Tier-1 que documente investigación criptográfica argentina con publicación…’ Gap. Accessed 2026-05-29.

⁸⁰ AR-EV-0121: ‘No se identificó capacidad documentada de ciberseguridad ofensiva soberana (red team gubernamental…’ Gap. Accessed 2026-05-29.

⁸¹ AR-EV-0116: ‘En abril de 2024 se difundió en Telegram una base con datos de aproximadamente 5,7-6 millones de…’ CaseStudy. https://www.lanacion.com.ar/seguridad/la-venden-a-us-3700-hackearon-la-base-de-datos-nacional-de-licencias-de-conducir-y-muestran-las-de-nid16042024/. Accessed 2026-05-29.

⁸² AR-EV-0117: ‘El 25-26 de diciembre de 2024 los sitios oficiales Mi Argentina y la plataforma de la tarjeta SUBE…’ CaseStudy. https://www.infobae.com/politica/2024/12/26/lo-hicimos-por-diversion-los-hackers-que-atacaron-los-sitios-del-gobierno-dijeron-que-no-tenian-segundo-factor-de-autenticacion/. Accessed 2026-05-29.

⁸³ AR-EV-0119: ‘El RENAPER detectó en 2021 el uso indebido de una clave otorgada a un organismo público (Ministerio…’ CaseStudy. https://www.argentina.gob.ar/noticias/el-renaper-detecto-el-uso-indebido-de-una-clave-otorgada-un-organismo-publico-y-formalizo. Accessed 2026-05-29.

⁸⁴ AR-EV-0122: ‘La Law No. 26388 de Delitos Informáticos, sancionada el 4 de junio de 2008, incorporó al Código Penal…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/ley-26388-141790/texto. Accessed 2026-05-29.; AR-EV-0125: ‘Law No. 25506 (2001) establishes the legal validity of digital and electronic signatures in Argentina…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/70000-74999/70749/norma.htm. Accessed 2026-05-29.; AR-EV-0126: ‘Article 15 of Law No. 27078 — which had designated TIC services as ‘essential and strategic public…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/235000-239999/239771/texact.htm. Accessed 2026-05-29.

⁸⁵ AR-EV-0131: ‘Resolución AAIP 161/2023 created the ‘Programa de Transparencia y Protección de Datos Personales en…’ Policy. https://www.boletinoficial.gob.ar/detalleAviso/primera/293363/20230904. Accessed 2026-05-29.; AR-EV-0134: ‘Argentina lacks a horizontal platform-regulation statute. The intermediary-liability bill…’ CaseStudy. https://rest.hcdn.gob.ar/web/proyectos/290487/adjuntos/104934. Accessed 2026-05-29.; AR-EV-0135: ‘Argentina’s cybersecurity-incident response framework rests on dispositions of the Dirección…’ Regulation. https://www.argentina.gob.ar/jefatura/innovacion-publica/direccion-nacional-ciberseguridad/normativa. Accessed 2026-05-29.

⁸⁶ AR-EV-0004: ‘El Proyecto de Ley de Protección de Datos Personales presentado por el Poder Ejecutivo Nacional en…’ Policy. https://www.argentina.gob.ar/aaip/datospersonales/proyecto-ley-datos-personales. Accessed 2026-05-29.; AR-EV-0178: ‘A Personal Data Protection bill (HCDN 1948-D-2025) introduced in the Argentine Chamber of Deputies…’ Analysis. https://iapp.org/news/a/novedades-legislativas-en-argentina-sobre-protecci-n-de-datos-personales-e-inteligencia-artificial. Accessed 2026-05-29.

⁸⁷ AR-EV-0133: ‘The Ministerio de Desregulación y Transformación del Estado (created July 2024 under Federico…’ Data. https://www.argentina.gob.ar/desregulacion. Accessed 2026-05-29.

⁸⁸ AR-EV-0126: ‘Article 15 of Law No. 27078 — which had designated TIC services as ‘essential and strategic public…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/235000-239999/239771/texact.htm. Accessed 2026-05-29.

⁸⁹ AR-EV-0139: ‘The Argentina national AI ecosystem framework — the Plan Nacional de Inteligencia Artificial…’ Report. https://oecd-opsi.org/wp-content/uploads/2021/02/Argentina-National-AI-Strategy.pdf. Accessed 2026-05-29.

⁹⁰ AR-EV-0132: ‘President Javier Milei has publicly positioned Argentina to compete as a ‘low-regulation AI hub’…’ CaseStudy. https://chequeado.com/el-explicador/argentina-polo-de-inteligencia-artificial-que-propone-el-gobierno-de-javier-milei-y-que-chances-hay-de-que-suceda/. Accessed 2026-05-29.

⁹¹ AR-EV-0140: ‘La Resolución AAIP 126/2024, en vigor desde el 1 de junio de 2024, aprueba el régimen sancionatorio…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/308122/20240524. Accessed 2026-05-29.

⁹² AR-EV-0144: ‘La AAIP sancionó a Google Argentina SRL y Google LLC mediante la Resolución 69/2020 por…’ CaseStudy. https://www.argentina.gob.ar/noticias/sancion-google-por-negar-el-derecho-de-acceso. Accessed 2026-05-29.

⁹³ AR-EV-0148: ‘En 2024 la CNDC emitió 89 decisiones en control de concentraciones y una única multa por…’ Data. https://legalblogs.wolterskluwer.com/competition-blog/main-developments-in-competition-law-and-policy-2024-argentina/. Accessed 2026-05-29.

⁹⁴ AR-EV-0142: ‘La Comisión Nacional de Defensa de la Competencia (CNDC) archivó el 2 de julio de 2025 la…’ CaseStudy. https://www.lanacion.com.ar/tecnologia/la-cndc-archivo-la-investigacion-contra-whatsapp-y-meta-por-presunto-abuso-de-posicion-dominante-nid08072025/. Accessed 2026-05-29.

⁹⁵ AR-EV-0158: ‘IRAM (Instituto Argentino de Normalización y Certificación), founded in 1935, is Argentina’s sole…’ Report. https://www.iram.org.ar/en/who-we-are/. Accessed 2026-05-29.

⁹⁶ AR-EV-0162: ‘Verónica Marinelli, coordinator of IRAM’s Subcommittee on Information Security, Cybersecurity and…’ CaseStudy. https://www.iram.org.ar/novedades/novedades-en-seguridad-de-la-informacion/. Accessed 2026-05-29.

⁹⁷ AR-EV-0160: ‘Editors from Universidad Tecnológica Nacional (UTN, Santa Fe Regional Faculty) serve as editor or…’ CaseStudy. https://uit.frsf.utn.edu.ar/. Accessed 2026-05-29.

⁹⁸ AR-EV-0161: ‘The official ITU-T Study Group 20 management roster for the 2025-2028 study period (period 18)…’ Data. https://www.itu.int/net4/ITU-T/lists/mgmt.aspx?Group=20&Period=18. Accessed 2026-05-29.

⁹⁹ AR-EV-0168: ‘No organisation domiciled in Argentina appears among the 329 (as of May 2026) Member organisations…’ Gap. https://www.w3.org/membership/list/. Accessed 2026-05-29.

¹⁰⁰ AR-EV-0163: ‘Argentina was elected President of CITEL’s Steering Committee (COM/CITEL) at the VII CITEL Assembly…’ Report. https://www.argentina.gob.ar/jefatura/innovacion-publica/ssetic/citel. Accessed 2026-05-29.

¹⁰¹ AR-EV-0171: ‘In November 2024 Beatriz Anchorena, head of Argentina’s Access to Public Information Agency (AAIP)…’ CaseStudy. https://www.argentina.gob.ar/noticias/beatriz-anchorena-titular-de-la-aaip-fue-electa-presidenta-del-comite-del-convenio-108-del. Accessed 2026-05-29.

¹⁰² AR-EV-0170: ‘Argentina participated in the second cycle of the UN Open-Ended Working Group (OEWG) on Security of…’ Report. https://www.argentina.gob.ar/noticias/argentina-participo-en-naciones-unidas-de-un-grupo-de-trabajo-sobre-tic-y-seguridad. Accessed 2026-05-29.

¹⁰³ AR-EV-0178: ‘A Personal Data Protection bill (HCDN 1948-D-2025) introduced in the Argentine Chamber of Deputies…’ Analysis. https://iapp.org/news/a/novedades-legislativas-en-argentina-sobre-protecci-n-de-datos-personales-e-inteligencia-artificial. Accessed 2026-05-29.; AR-EV-0169: ‘On 5 February 2026 the Argentine Foreign Ministry announced the signature of the United…’ Policy. https://www.cancilleria.gob.ar/es/actualidad/noticias/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones. Accessed 2026-05-29.

¹⁰⁴ AR-EV-0191: ‘En el Ranking Scimago Institutions 2024, CONICET figura como la principal institución gubernamental…’ Report. https://www.scimagoir.com/rankings.php?country=ARG. Accessed 2026-05-29.

¹⁰⁵ AR-EV-0187: ‘El proyecto QUANTEC del Grupo de Circuitos Cuánticos del Centro Atómico Bariloche (CNEA-CONICET)…’ CaseStudy. https://www.argentina.gob.ar/noticias/cientificos-del-centro-atomico-bariloche-buscan-crear-un-procesador-cuantico-con-circuitos. Accessed 2026-05-29.

¹⁰⁶ AR-EV-0186: ‘Clementina XXI, supercomputadora adquirida por Argentina vía Iniciativa Nacional de Supercómputo…’ CaseStudy. https://www.argentina.gob.ar/noticias/argentina-pone-en-funcionamiento-la-supercomputadora-clementina-xxi. Accessed 2026-05-29.

¹⁰⁷ AR-EV-0188: ‘La convocatoria 2023 de Proyectos de Fortalecimiento de Infraestructura Experimental en CyT…’ Policy. https://www.argentina.gob.ar/ciencia/financiamiento/fort-exper-cytcuanticas-2023. Accessed 2026-05-29.

¹⁰⁸ AR-EV-0193: ‘Existen grupos argentinos publicando trabajos de aprendizaje automático y visión por computadora…’ Analysis. https://scholar.google.com/citations?user=ArqlkTUAAAAJ&hl=en. Accessed 2026-05-29.

¹⁰⁹ AR-EV-0187: ‘El proyecto QUANTEC del Grupo de Circuitos Cuánticos del Centro Atómico Bariloche (CNEA-CONICET)…’ CaseStudy. https://www.argentina.gob.ar/noticias/cientificos-del-centro-atomico-bariloche-buscan-crear-un-procesador-cuantico-con-circuitos. Accessed 2026-05-29.

¹¹⁰ AR-EV-0181: ‘Argentina’s R&D investment fell to 0.216% of GDP in 2024, the lowest historical figure on record…’ Data. https://periferia.com.ar/indicios/la-inversion-en-ciencia-y-tecnologia-llego-a-su-mayor-deterioro-historico-en-2024/. Accessed 2026-05-29.

¹¹¹ AR-EV-0182: ‘Law No. 27614 (Ley de Financiamiento del Sistema Nacional de Ciencia, Tecnología e Innovación…’ Regulation. https://www.iade.org.ar/noticias/ley-de-financiamiento-del-sistema-nacional-de-ciencia-tecnologia-e-innovacion-en-argentina. Accessed 2026-05-29.

¹¹² AR-EV-0198: ‘Universidad Tecnológica Nacional (UTN) produces 42.75% of Argentina’s engineering graduates…’ Data. https://frba.utn.edu.ar/dia-de-la-ingenieria-la-utn-forma-mas-del-40-de-los-ingenieros-que-se-graduan-en-el-pais/. Accessed 2026-05-29.

¹¹³ AR-EV-0198: ‘Universidad Tecnológica Nacional (UTN) produces 42.75% of Argentina’s engineering graduates…’ Data. https://frba.utn.edu.ar/dia-de-la-ingenieria-la-utn-forma-mas-del-40-de-los-ingenieros-que-se-graduan-en-el-pais/. Accessed 2026-05-29.

¹¹⁴ AR-EV-0203: ‘The RAICES Programme (Red de Argentinos Investigadores y Científicos en el Exterior), created in…’ Policy. https://www.argentina.gob.ar/ciencia/seppcti/raices. Accessed 2026-05-29.

¹¹⁵ AR-EV-0207: ‘In the EduRank Latin America Computer Science ranking, UBA is #1 in Argentina and #555 worldwide…’ Data. https://edurank.org/cs/la/. Accessed 2026-05-29.

¹¹⁶ AR-EV-0200: ‘Argentina is in the top 30 nations with highly-skilled emigrants according to OECD data, with…’ Data. https://www.untref.edu.ar/mundountref/argentina-se-convirtio-en-un-polo-de-emigracion. Accessed 2026-05-29.; AR-EV-0202: ‘Argentine remote workers for foreign employers earn between USD 2,500 and USD 5,000 per month on…’ Data. https://www.infobae.com/economia/2024/09/15/los-argentinos-que-trabajan-para-el-exterior-ganan-entre-2500-y-5000-dolares-por-mes/. Accessed 2026-05-29.

¹¹⁷ AR-EV-0197: ‘Argentina’s 2025 budget projects Science and Technology investment at approximately 0.2% of GDP —…’ Data. https://periferia.com.ar/indicios/el-presupuesto-2025-deja-la-inversion-en-ciencia-y-tecnologia-al-nivel-del-2002/. Accessed 2026-05-29.; AR-EV-0196: ‘In 2024 CONICET cut doctoral scholarship allocations by approximately 30%, awarded 950 scholarships…’ Policy. https://www.scidev.net/america-latina/news/mas-becas-en-un-clima-incierto-para-hacer-ciencia-en-argentina/. Accessed 2026-05-29.

¹¹⁸ AR-EV-0212: ‘Argentina’s software industry reached USD 22,221 million in revenue in 2024 (+13.1% interannual)…’ Data. https://www.itsitio.com/ar/software/software-argentino-bate-records/. Accessed 2026-05-29.

¹¹⁹ AR-EV-0222: ‘Argentina’s software industry employs more than 140,000 people formally — exceeding employment in…’ Report. https://fund.ar/publicacion/introduccion-a-la-industria-del-software/. Accessed 2026-05-29.

¹²⁰ AR-EV-0096: ‘El sector argentino de software y servicios informáticos exportó USD 2.674 millones en 2024, un…’ Data. https://cessi.org.ar/2025/05/21/el-software-argentino-genero-mas-de-6-000-empleos-y-alcanzo-un-record-de-exportaciones/. Accessed 2026-05-29.; AR-EV-0214: ‘In 2022 Argentine SBC exports were USD 8,047 million, with software making up 33%, professional…’ Data. https://argendata.fund.ar/topico/servicios-basados-en-el-conocimiento/. Accessed 2026-05-29.

¹²¹ AR-EV-0101: ‘El segmento de digital banking argentino está concentrado en tres jugadores domésticos: Ualá (6…’ Data. https://fintechnews.am/fintech-argentina/52228/argentinas-top-3-digital-banks-capture-nearly-90-market-share/. Accessed 2026-05-29.

¹²² AR-EV-0218: ‘Argentine startups raised USD 412 million across 62 funding rounds in 2024 (46 seed rounds at USD…’ Data. https://www.lanacion.com.ar/economia/negocios/los-emprendedores-argentinos-levantaron-mas-de-us412-millones-en-2024-nid11062025/. Accessed 2026-05-29.

¹²³ AR-EV-0217: ‘Auth0 — co-founded in 2013 by Argentine engineers Eugenio Pace (ITBA) and Matías Woloski…’ CaseStudy. https://www.roadshow.com.ar/como-nacio-auth0-el-unicornio-argentino-que-se-vendio-en-us-6500-millones/. Accessed 2026-05-29.

¹²⁴ AR-EV-0214: ‘In 2022 Argentine SBC exports were USD 8,047 million, with software making up 33%, professional…’ Data. https://argendata.fund.ar/topico/servicios-basados-en-el-conocimiento/. Accessed 2026-05-29.

¹²⁵ AR-EV-0220: ‘Within Argentina’s R&D ecosystem the software industry accounts for 14% of total business R&D…’ Data. https://www.argentina.gob.ar/noticias/el-potencial-de-id-en-sectores-productivos-de-la-economia-del-conocimiento-software-y-ag-0. Accessed 2026-05-29.

¹²⁶ AR-EV-0217: ‘Auth0 — co-founded in 2013 by Argentine engineers Eugenio Pace (ITBA) and Matías Woloski…’ CaseStudy. https://www.roadshow.com.ar/como-nacio-auth0-el-unicornio-argentino-que-se-vendio-en-us-6500-millones/. Accessed 2026-05-29.

¹²⁷ AR-EV-0215: ‘Argentina has been losing global software-export market share — from 0.6% of global sales in 2011…’ Analysis. https://www.lanacion.com.ar/economia/despertar-el-potencial-de-la-industria-del-software-una-estrategia-para-el-futuro-nid14082024/. Accessed 2026-05-29.

¹²⁸ AR-EV-0218: ‘Argentine startups raised USD 412 million across 62 funding rounds in 2024 (46 seed rounds at USD…’ Data. https://www.lanacion.com.ar/economia/negocios/los-emprendedores-argentinos-levantaron-mas-de-us412-millones-en-2024-nid11062025/. Accessed 2026-05-29.

¹²⁹ AR-EV-0219: ‘Law No. 27742 ‘Bases y Puntos de Partida para la Libertad de los Argentinos’ (sanctioned July 2024)…’ Policy. https://chequeado.com/el-explicador/openai-invertira-us-25-000-millones-en-un-data-center-para-ia-en-la-argentina-las-claves-del-anuncio/. Accessed 2026-05-29.

¹³⁰ AR-EV-0225: ‘La Law No. 27738, sancionada el 10 de octubre de 2023 y publicada en el Boletín Oficial el 23 de…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/296574/20231023. Accessed 2026-05-29.

¹³¹ AR-EV-0230: ‘La Agenda Digital 2030 fue presentada por el gobierno de Mauricio Macri el 5 de noviembre de 2018…’ Policy. https://www.argentina.gob.ar/noticias/el-gobierno-presento-la-nueva-agenda-digital-2030. Accessed 2026-05-29.

¹³² AR-EV-0226: ‘La Resolución 282/2025 de la Secretaría de Innovación, Ciencia y Tecnología (Jefatura de Gabinete)…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/333751/20251031. Accessed 2026-05-29.

¹³³ AR-EV-0227: ‘La Decisión Administrativa 899/2024, publicada el 24 de septiembre de 2024, crea la Mesa…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/314465/20240924. Accessed 2026-05-29.

¹³⁴ AR-EV-0227: ‘La Decisión Administrativa 899/2024, publicada el 24 de septiembre de 2024, crea la Mesa…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/314465/20240924. Accessed 2026-05-29.

¹³⁵ AR-EV-0229: ‘El Banco Interamericano de Desarrollo aprobó en 2023 un préstamo por USD 35 millones a Argentina…’ CaseStudy. https://www.argentina.gob.ar/noticias/nuevo-programa-de-35-millones-de-dolares-para-el-desarrollo-de-la-inteligencia-artificial. Accessed 2026-05-29.

¹³⁶ AR-EV-0235: ‘La Función Ciencia y Tecnología del Presupuesto Nacional cayó un 11,4% adicional en el primer…’ Data. https://ciicti.org/el-2026-llego-con-mas-recortes-presupuestarios-a-la-ciencia-argentina/. Accessed 2026-05-29.

¹³⁷ AR-EV-0240: ‘El Poder Legislativo no sancionó la Ley de Presupuesto Nacional 2025: el Decree 425/2025 y la…’ Data. https://chequeado.com/el-explicador/presupuesto-2025-las-5-claves-para-entender-la-prorroga-definida-por-el-gobierno-de-javier-milei/. Accessed 2026-05-29.

¹³⁸ AR-EV-0236: ‘El programa Conectar Igualdad —creado en 2010 por Decree 459/10, suspendido durante la…’ CaseStudy. https://palabrasdelderecho.com.ar/articulo/5007/Prorrogaron-la-vigencia-del-Programa-Conectar-Igualdad-por-dos-meses. Accessed 2026-05-29.

¹³⁹ AR-EV-0234: ‘El Ministerio de Ciencia, Tecnología e Innovación fue creado por Decree 21/2007 bajo la…’ CaseStudy. https://es.wikipedia.org/wiki/Ministerio_de_Ciencia,Tecnolog%C3%ADa_e_Innovaci%C3%B3n(Argentina). Accessed 2026-05-29.

¹⁴⁰ AR-EV-0232: ‘El Decreto de Necesidad y Urgencia 70/2023, emitido el 20 de diciembre de 2023, declaró la…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/301122/20231221. Accessed 2026-05-29.

¹⁴¹ AR-EV-0237: ‘El gobierno argentino articula públicamente la ambición de convertir al país en ‘uno de los cuatro…’ Policy. https://www.telesemana.com/blog/2024/12/02/argentina-trabaja-en-desregulacion-energia-y-analisis-de-marcos-normativos-para-convertirse-en-el-hub-de-la-inteligencia-artificial-de-sudamerica/. Accessed 2026-05-29.

¹⁴² AR-EV-0238: ‘La fundación Fundar argumenta que la estrategia de IA del gobierno Milei tiene un ‘talón de…’ Analysis. https://fund.ar/publicacion/la-estrategia-de-milei-en-inteligencia-artificial-tiene-un-talon-de-aquiles/. Accessed 2026-05-29.

¹⁴³ AR-EV-0031: ‘El 13 de noviembre de 2025, los presidentes Donald J. Trump y Javier Milei suscribieron el Joint…’ Policy. https://www.whitehouse.gov/briefings-statements/2025/11/joint-statement-on-framework-for-a-united-states-argentina-agreement-on-reciprocal-trade-and-investment/. Accessed 2026-05-29.; AR-EV-0032: ‘El 5 de febrero de 2026 en Washington D.C., la República Argentina y los Estados Unidos…’ Policy. https://www.cancilleria.gob.ar/es/destacados/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones-reciprocos. Accessed 2026-05-29.

¹⁴⁴ AR-EV-0133: ‘The Ministerio de Desregulación y Transformación del Estado (created July 2024 under Federico…’ Data. https://www.argentina.gob.ar/desregulacion. Accessed 2026-05-29.

¹⁴⁵ AR-EV-0235: ‘La Función Ciencia y Tecnología del Presupuesto Nacional cayó un 11,4% adicional en el primer…’ Data. https://ciicti.org/el-2026-llego-con-mas-recortes-presupuestarios-a-la-ciencia-argentina/. Accessed 2026-05-29.; AR-EV-0182: ‘Law No. 27614 (Ley de Financiamiento del Sistema Nacional de Ciencia, Tecnología e Innovación…’ Regulation. https://www.iade.org.ar/noticias/ley-de-financiamiento-del-sistema-nacional-de-ciencia-tecnologia-e-innovacion-en-argentina. Accessed 2026-05-29.

¹⁴⁶ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

¹⁴⁷ AR-EV-0007: ‘La AAIP publica como guía oficial vigente que los países considerados con legislación adecuada son…’ Report. https://www.argentina.gob.ar/aaip/datospersonales/transferencias-internacionales. Accessed 2026-05-29.

¹⁴⁸ AR-EV-0018: ‘AWS anunció en marzo de 2022 Local Zones en seis ciudades latinoamericanas, incluida Buenos Aires…’ Report. https://aws.amazon.com/blogs/publicsector/aws-announces-local-zones-latin-america/. Accessed 2026-05-29.; AR-EV-0219: ‘Law No. 27742 ‘Bases y Puntos de Partida para la Libertad de los Argentinos’ (sanctioned July 2024)…’ Policy. https://chequeado.com/el-explicador/openai-invertira-us-25-000-millones-en-un-data-center-para-ia-en-la-argentina-las-claves-del-anuncio/. Accessed 2026-05-29.

¹⁴⁹ AR-EV-0104: ‘Auth0, empresa argentina de autenticación digital fundada en 2013, fue adquirida en 2021 por Okta…’ CaseStudy. https://www.infobae.com/economia/2021/06/23/otra-tech-argentina-se-convirtio-en-unicornio-y-es-el-sexto-local-que-hace-y-quien-es-el-millennial-autodidacta-que-la-fundo/. Accessed 2026-05-29.; AR-EV-0217: ‘Auth0 — co-founded in 2013 by Argentine engineers Eugenio Pace (ITBA) and Matías Woloski…’ CaseStudy. https://www.roadshow.com.ar/como-nacio-auth0-el-unicornio-argentino-que-se-vendio-en-us-6500-millones/. Accessed 2026-05-29.

¹⁵⁰ AR-EV-0200: ‘Argentina is in the top 30 nations with highly-skilled emigrants according to OECD data, with…’ Data. https://www.untref.edu.ar/mundountref/argentina-se-convirtio-en-un-polo-de-emigracion. Accessed 2026-05-29.

¹⁵¹ AR-EV-0181: ‘Argentina’s R&D investment fell to 0.216% of GDP in 2024, the lowest historical figure on record…’ Data. https://periferia.com.ar/indicios/la-inversion-en-ciencia-y-tecnologia-llego-a-su-mayor-deterioro-historico-en-2024/. Accessed 2026-05-29.

¹⁵² AR-EV-0212: ‘Argentina’s software industry reached USD 22,221 million in revenue in 2024 (+13.1% interannual)…’ Data. https://www.itsitio.com/ar/software/software-argentino-bate-records/. Accessed 2026-05-29.; AR-EV-0001: ‘El artículo 12 de la Law No. 25326 prohíbe la transferencia de datos personales de cualquier tipo con…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/60000-64999/64790/texact.htm. Accessed 2026-05-29.

¹⁵³ AR-EV-0031: ‘El 13 de noviembre de 2025, los presidentes Donald J. Trump y Javier Milei suscribieron el Joint…’ Policy. https://www.whitehouse.gov/briefings-statements/2025/11/joint-statement-on-framework-for-a-united-states-argentina-agreement-on-reciprocal-trade-and-investment/. Accessed 2026-05-29.; AR-EV-0055: ‘No se identifica fuente Tier-1 que documente reconocimiento estatal explícito de los datos como…’ Gap. Accessed 2026-05-29.

¹⁵⁴ AR-EV-0064: ‘El Instituto Nacional de Tecnología Industrial (INTI), a través de su área de Micro y…’ CaseStudy. https://www.inti.gob.ar/areas/desarrollo-tecnologico-e-innovacion/areas-de-conocimiento/micro-y-nanotecnologias. Accessed 2026-05-29.; AR-EV-0080: ‘ARSAT desplegó Red Hat OpenShift AI para apoyar operaciones de centro de operaciones de red (NOC)…’ CaseStudy. https://www.redhat.com/en/success-stories/arsat. Accessed 2026-05-29.; AR-EV-0200: ‘Argentina is in the top 30 nations with highly-skilled emigrants according to OECD data, with…’ Data. https://www.untref.edu.ar/mundountref/argentina-se-convirtio-en-un-polo-de-emigracion. Accessed 2026-05-29.

¹⁵⁵ AR-EV-0133: ‘The Ministerio de Desregulación y Transformación del Estado (created July 2024 under Federico…’ Data. https://www.argentina.gob.ar/desregulacion. Accessed 2026-05-29.; AR-EV-0235: ‘La Función Ciencia y Tecnología del Presupuesto Nacional cayó un 11,4% adicional en el primer…’ Data. https://ciicti.org/el-2026-llego-con-mas-recortes-presupuestarios-a-la-ciencia-argentina/. Accessed 2026-05-29.

¹⁵⁶ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

¹⁵⁷ AR-EV-0004: ‘El Proyecto de Ley de Protección de Datos Personales presentado por el Poder Ejecutivo Nacional en…’ Policy. https://www.argentina.gob.ar/aaip/datospersonales/proyecto-ley-datos-personales. Accessed 2026-05-29.; AR-EV-0141: ‘La Resolución AAIP 126/2024, publicada en el Boletín Oficial el 24 de mayo de 2024 y en vigor desde…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/395000-399999/399750/norma.htm. Accessed 2026-05-29.

¹⁵⁸ AR-EV-0032: ‘El 5 de febrero de 2026 en Washington D.C., la República Argentina y los Estados Unidos…’ Policy. https://www.cancilleria.gob.ar/es/destacados/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones-reciprocos. Accessed 2026-05-29.

¹⁵⁹ AR-EV-0227: ‘La Decisión Administrativa 899/2024, publicada el 24 de septiembre de 2024, crea la Mesa…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/314465/20240924. Accessed 2026-05-29.; AR-EV-0182: ‘Law No. 27614 (Ley de Financiamiento del Sistema Nacional de Ciencia, Tecnología e Innovación…’ Regulation. https://www.iade.org.ar/noticias/ley-de-financiamiento-del-sistema-nacional-de-ciencia-tecnologia-e-innovacion-en-argentina. Accessed 2026-05-29.; AR-EV-0240: ‘El Poder Legislativo no sancionó la Ley de Presupuesto Nacional 2025: el Decree 425/2025 y la…’ Data. https://chequeado.com/el-explicador/presupuesto-2025-las-5-claves-para-entender-la-prorroga-definida-por-el-gobierno-de-javier-milei/. Accessed 2026-05-29.

¹⁶⁰ AR-EV-0097: ‘Argentina’s Law No. 27506 (Régimen de Promoción de la Economía del Conocimiento), in force since 1…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/ley-27506-324101/actualizacion. Accessed 2026-05-29.; AR-EV-0217: ‘Auth0 — co-founded in 2013 by Argentine engineers Eugenio Pace (ITBA) and Matías Woloski…’ CaseStudy. https://www.roadshow.com.ar/como-nacio-auth0-el-unicornio-argentino-que-se-vendio-en-us-6500-millones/. Accessed 2026-05-29.

¹⁶¹ AR-EV-0196: ‘In 2024 CONICET cut doctoral scholarship allocations by approximately 30%, awarded 950 scholarships…’ Policy. https://www.scidev.net/america-latina/news/mas-becas-en-un-clima-incierto-para-hacer-ciencia-en-argentina/. Accessed 2026-05-29.; AR-EV-0186: ‘Clementina XXI, supercomputadora adquirida por Argentina vía Iniciativa Nacional de Supercómputo…’ CaseStudy. https://www.argentina.gob.ar/noticias/argentina-pone-en-funcionamiento-la-supercomputadora-clementina-xxi. Accessed 2026-05-29.; AR-EV-0187: ‘El proyecto QUANTEC del Grupo de Circuitos Cuánticos del Centro Atómico Bariloche (CNEA-CONICET)…’ CaseStudy. https://www.argentina.gob.ar/noticias/cientificos-del-centro-atomico-bariloche-buscan-crear-un-procesador-cuantico-con-circuitos. Accessed 2026-05-29.

¹⁶² AR-EV-0001: ‘El artículo 12 de la Law No. 25326 prohíbe la transferencia de datos personales de cualquier tipo con…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/60000-64999/64790/texact.htm. Accessed 2026-05-29.

¹⁶³ AR-EV-0002: ‘El Decree 1558/2001, promulgado el 29 de noviembre de 2001 y publicado en el Boletín Oficial el 3…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/verNorma.do?id=70368. Accessed 2026-05-29.

¹⁶⁴ AR-EV-0003: ‘La AAIP se autodefine en su sitio oficial como garante de la protección de datos personales y la…’ Regulation. https://www.argentina.gob.ar/aaip/datospersonales. Accessed 2026-05-29.

¹⁶⁵ AR-EV-0004: ‘El Proyecto de Ley de Protección de Datos Personales presentado por el Poder Ejecutivo Nacional en…’ Policy. https://www.argentina.gob.ar/aaip/datospersonales/proyecto-ley-datos-personales. Accessed 2026-05-29.

¹⁶⁶ AR-EV-0005: ‘La AAIP aprobó por Resolución 47/2018 (publicada 25-07-2018, vigente) las Medidas de Seguridad…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/310000-314999/312662/norma.htm. Accessed 2026-05-29.

¹⁶⁷ AR-EV-0007: ‘La AAIP publica como guía oficial vigente que los países considerados con legislación adecuada son…’ Report. https://www.argentina.gob.ar/aaip/datospersonales/transferencias-internacionales. Accessed 2026-05-29.

¹⁶⁸ AR-EV-0008: ‘La Law No. 27699, sancionada el 9 de noviembre de 2022 y publicada en el Boletín Oficial el 30 de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/375000-379999/375738/norma.htm. Accessed 2026-05-29.

¹⁶⁹ AR-EV-0009: ‘El United States Trade Representative (USTR) publicó el 13 de noviembre de 2025 el Fact Sheet del…’ Policy. https://ustr.gov/about/policy-offices/press-office/fact-sheets/2025/november/fact-sheet-united-states-and-argentina-agree-framework-agreement-reciprocal-trade-and-investment. Accessed 2026-05-29.

¹⁷⁰ AR-EV-0010: ‘Según el Informe Anual 2022 de la AAIP, la autoridad inició 491 expedientes por presuntas…’ Data. https://iapp.org/news/a/la-autoridad-de-proteccion-de-datos-de-argentina-publica-su-informe-anual-2022. Accessed 2026-05-29.

¹⁷¹ AR-EV-0011: ‘El régimen vigente de la Law No. 25326 no contempla obligaciones operativas de notificación reglada de…’ Gap. Accessed 2026-05-29.

¹⁷² AR-EV-0012: ‘La Comunicación A 7724 del BCRA, vigente desde el 6 de septiembre de 2023, establece requisitos…’ Regulation. https://www.grantthornton.com.ar/en/insights/articles/2023/communication-a7724-bcra/. Accessed 2026-05-29.

¹⁷³ AR-EV-0013: ‘ARSAT opera el Centro Nacional de Datos en Benavídez (Buenos Aires), única instalación del país con…’ Report. https://www.arsat.com.ar/datacenter/. Accessed 2026-05-29.

¹⁷⁴ AR-EV-0014: ‘El Poder Ejecutivo Nacional presentó al Congreso el 30 de junio de 2023 un proyecto de ley para…’ Policy. https://iapp.org/news/a/se-presento-ante-el-congreso-nacional-argentino-un-nuevo-proyecto-de-ley-para-reemplazar-la-actual-ley-de-proteccion-de-datos-personales. Accessed 2026-05-29.

¹⁷⁵ AR-EV-0015: ‘El proyecto de ley 1948-D-2025, ingresado a la Cámara de Diputados en 2025, propone reemplazar la…’ Policy. https://www4.hcdn.gob.ar/dependencias/dsecretaria/Periodo2025/PDF2025/TP2025/1948-D-2025.pdf. Accessed 2026-05-29.

¹⁷⁶ AR-EV-0016: ‘Argentina tiene 13 data centers comerciales identificados por CABASE con capacidad superior a 1 MW…’ Data. https://www.telesemana.com/blog/2026/05/06/argentina-busca-atraer-14-data-centers-y-ampliar-su-infraestructura-digital-para-la-era-de-la-ia/. Accessed 2026-05-29.

¹⁷⁷ AR-EV-0017: ‘El 10 de octubre de 2025 Sur Energy (Argentina) y OpenAI (Estados Unidos) firmaron una carta de…’ CaseStudy. https://chequeado.com/investigaciones/mega-data-centers-en-la-patagonia-promesas-millonarias-y-alerta-por-la-falta-de-regulacion/. Accessed 2026-05-29.

¹⁷⁸ AR-EV-0018: ‘AWS anunció en marzo de 2022 Local Zones en seis ciudades latinoamericanas, incluida Buenos Aires…’ Report. https://aws.amazon.com/blogs/publicsector/aws-announces-local-zones-latin-america/. Accessed 2026-05-29.

¹⁷⁹ AR-EV-0019: ‘El Súper RIGI (Message 181/2026 al HCDN) propone exigir inversiones mínimas de US$ 1.000 millones…’ Policy. https://www.cronista.com/economia-politica/rigi-y-super-rigi-que-cambia-que-se-amplifica-y-que-se-elimina/. Accessed 2026-05-29.

¹⁸⁰ AR-EV-0020: ‘El gobierno anunció en octubre de 2024 un plan de privatización parcial de ARSAT (hasta el 49% del…’ Policy. https://www.infobae.com/economia/2024/10/08/el-gobierno-buscara-privatizar-el-49-de-la-estatal-arsat-que-podria-salir-a-la-bolsa-en-2025/. Accessed 2026-05-29.

¹⁸¹ AR-EV-0021: ‘El régimen argentino de transferencias internacionales de datos personales se rige por el artículo…’ Regulation. https://www.argentina.gob.ar/transferencias-internacionales. Accessed 2026-05-29.

¹⁸² AR-EV-0023: ‘El BCRA emitió la Comunicación A 8401 (13/02/2026) — más reciente que la A 7724 — disponible en el…’ Regulation. https://www.bcra.gob.ar/archivos/Pdfs/comytexord/A8401.pdf. Accessed 2026-05-29.

¹⁸³ AR-EV-0025: ‘El Decreto Reglamentario 1558/2001 (anexo I, art. 12) faculta a la Dirección Nacional de Protección…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/decreto-1558-2001-70368. Accessed 2026-05-29.

¹⁸⁴ AR-EV-0026: ‘La Disposición DNPDP 60-E/2016, dictada el 16 de noviembre de 2016, aprueba dos conjuntos de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/265000-269999/267922/norma.htm. Accessed 2026-05-29.

¹⁸⁵ AR-EV-0027: ‘La Resolución AAIP 34/2019, del 22 de febrero de 2019 y firmada por Eduardo Andrés Bertoni…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/202373/20190226. Accessed 2026-05-29.

¹⁸⁶ AR-EV-0028: ‘La Resolución AAIP 198/2023, publicada el 18 de octubre de 2023 y firmada por la directora Beatriz…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/296189/20231018. Accessed 2026-05-29.

¹⁸⁷ AR-EV-0031: ‘El 13 de noviembre de 2025, los presidentes Donald J. Trump y Javier Milei suscribieron el Joint…’ Policy. https://www.whitehouse.gov/briefings-statements/2025/11/joint-statement-on-framework-for-a-united-states-argentina-agreement-on-reciprocal-trade-and-investment/. Accessed 2026-05-29.

¹⁸⁸ AR-EV-0032: ‘El 5 de febrero de 2026 en Washington D.C., la República Argentina y los Estados Unidos…’ Policy. https://www.cancilleria.gob.ar/es/destacados/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones-reciprocos. Accessed 2026-05-29.

¹⁸⁹ AR-EV-0035: ‘En enero de 2024 la Comisión Europea publicó el primer informe de revisión de las decisiones de…’ Policy. https://www.argentina.gob.ar/noticias/argentina-logro-la-nueva-adecuacion-por-parte-de-la-union-europea-para-el-flujo. Accessed 2026-05-29.

¹⁹⁰ AR-EV-0040: ‘Microsoft, en su documentación oficial de cumplimiento publicada en learn.microsoft.com, declara…’ Report. https://learn.microsoft.com/en-us/compliance/regulatory/offering-pdpa-argentina. Accessed 2026-05-29.

¹⁹¹ AR-EV-0041: ‘No se identificó fuente Tier-1 que documente estadísticas cuantitativas específicas del régimen de…’ Gap. Accessed 2026-05-29.

¹⁹² AR-EV-0042: ‘El Decree 117/2016, suscrito el 12 de enero de 2016, instruye a los ministerios, secretarías y…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/decreto-117-2016-257755. Accessed 2026-05-29.

¹⁹³ AR-EV-0043: ‘La Law No. 27275 de Derecho de Acceso a la Información Pública, sancionada el 14 de septiembre de…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/265000-269999/265949/norma.htm. Accessed 2026-05-29.

¹⁹⁴ AR-EV-0044: ‘El Decree 780/2024, firmado el 30 de agosto de 2024 (BO 02-09-2024), reglamentó modificaciones al…’ Regulation. https://www.boletinoficial.gov.ar/detalleAviso/primera/313139/20240902. Accessed 2026-05-29.

¹⁹⁵ AR-EV-0045: ‘El portal nacional datos.gob.ar registra 1.235 datasets publicados por 42 organizaciones del sector…’ Data. https://datos.gob.ar/. Accessed 2026-05-29.

¹⁹⁶ AR-EV-0047: ‘El impuesto PAIS, que añadía una alícuota del 8% sobre suscripciones a servicios digitales del…’ CaseStudy. https://chequeado.com/el-explicador/fin-del-impuesto-pais-que-impacto-tendra-en-las-compras-de-bienes-y-servicios-en-el-exterior-en-el-turismo-y-en-las-importaciones/. Accessed 2026-05-29.

¹⁹⁷ AR-EV-0048: ‘La Comisión Nacional de Defensa de la Competencia (CNDC) creó un Grupo de Investigación y Trabajo…’ CaseStudy. https://www.argentina.gob.ar/noticias/la-cndc-creo-el-grupo-de-investigacion-y-trabajo-sobre-mercados-digitales. Accessed 2026-05-29.

¹⁹⁸ AR-EV-0049: ‘La CNDC investiga 11 mercados de alta concentración: aluminio, acero, petroquímica, comunicaciones…’ CaseStudy. https://www.casarosada.gob.ar/35904-once-mercados-con-altaconcentraci. Accessed 2026-05-29.

¹⁹⁹ AR-EV-0053: ‘Organizaciones civiles argentinas — LA NACION Data junto con ACIJ, Directorio Legislativo y Poder…’ CaseStudy. https://www.lanacion.com.ar/sociedad/periodismo-de-datos-una-iniciativa-y-un-equipo-para-agregar-valor-e-innovar-nid2312192/. Accessed 2026-05-29.

²⁰⁰ AR-EV-0054: ‘No se identifica fuente Tier-1 que documente la existencia de un mandato general operativo de…’ Gap. Accessed 2026-05-29.

²⁰¹ AR-EV-0055: ‘No se identifica fuente Tier-1 que documente reconocimiento estatal explícito de los datos como…’ Gap. Accessed 2026-05-29.

²⁰² AR-EV-0057: ‘No se identifica fuente Tier-1 que documente la implementación por parte de Argentina de mecanismos…’ Gap. Accessed 2026-05-29.

²⁰³ AR-EV-0058: ‘No se identifica fuente Tier-1 que documente la existencia operativa de data trusts, data…’ Gap. Accessed 2026-05-29.

²⁰⁴ AR-EV-0059: ‘La Law No. 27437 de Compre Argentino y Desarrollo de Proveedores, promulgada en abril de 2018 y…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/310000-314999/310020/norma.htm. Accessed 2026-05-29.

²⁰⁵ AR-EV-0060: ‘La Law No. 19640, sancionada en 1972, estableció un régimen aduanero y fiscal especial para Tierra del…’ Regulation. https://prodyambiente.tierradelfuego.gob.ar/regimen-de-promocion-economica-y-fiscal-ley-19-640-2/. Accessed 2026-05-29.

²⁰⁶ AR-EV-0061: ‘El Decree 333/2025, publicado en el Boletín Oficial el 20 de mayo de 2025, reduce a 8% el Derecho…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/325601/20250520. Accessed 2026-05-29.

²⁰⁷ AR-EV-0062: ‘Argentina no exhibe acuerdos bilaterales de transferencia tecnológica vigentes con jurisdicciones…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/400000-404999/403230/norma.htm. Accessed 2026-05-29.

²⁰⁸ AR-EV-0063: ‘La Law No. 27506 del Régimen de Promoción de la Economía del Conocimiento (publicada en el Boletín…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/320000-324999/324101/norma.htm. Accessed 2026-05-29.

²⁰⁹ AR-EV-0064: ‘El Instituto Nacional de Tecnología Industrial (INTI), a través de su área de Micro y…’ CaseStudy. https://www.inti.gob.ar/areas/desarrollo-tecnologico-e-innovacion/areas-de-conocimiento/micro-y-nanotecnologias. Accessed 2026-05-29.

²¹⁰ AR-EV-0066: ‘El Grupo Mirgor adquirió en 2021 la operación de Brightstar en Tierra del Fuego, sumando a IATEC y…’ CaseStudy. https://mirgor.com/mirgor-adquiere-brightstar-tierra-del-fuego/. Accessed 2026-05-29.

²¹¹ AR-EV-0068: ‘Los Lineamientos Estratégicos de Innovación, Ciencia y Tecnología 2025-2027, aprobados por…’ Policy. https://www.argentina.gob.ar/ciencia/plan-nacional-cti/plan-cti. Accessed 2026-05-29.

²¹² AR-EV-0074: ‘El sistema operativo de escritorio dominante en Argentina al mes de abril de 2026 es Windows con…’ Data. https://gs.statcounter.com/os-market-share/desktop/argentina. Accessed 2026-05-29.

²¹³ AR-EV-0075: ‘El mercado de sistemas operativos móviles en Argentina al mes de abril de 2026 está dominado por…’ Data. https://gs.statcounter.com/os-market-share/mobile/argentina. Accessed 2026-05-29.

²¹⁴ AR-EV-0076: ‘Huayra GNU/Linux es el sistema operativo libre desarrollado en EDUCAR Sociedad del Estado, descrito…’ CaseStudy. https://huayra.educar.gob.ar/. Accessed 2026-05-29.

²¹⁵ AR-EV-0077: ‘In January 2024 the Milei government suspended access to Conectar Igualdad and Educ.ar —…’ CaseStudy. https://www.ambito.com/politica/el-gobierno-bloqueo-las-plataformas-conectar-igualdad-y-educar-n5931668. Accessed 2026-05-29.

²¹⁶ AR-EV-0078: ‘El Decree 963/2024, publicado en el Boletín Oficial el 31 de octubre de 2024, designa a Gastón…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/316281/20241031. Accessed 2026-05-29.

²¹⁷ AR-EV-0079: ‘ARSAT desplegó la etapa 1 de la Nube Pública Nacional el 1° de abril de 2021, construida sobre…’ CaseStudy. https://www.canal-ar.com.ar/29335-ARSAT-lanzo-la-Nube-Publica-Nacional-y-ofrece-infraestructura-y-servicios-a-demanda.html. Accessed 2026-05-29.

²¹⁸ AR-EV-0080: ‘ARSAT desplegó Red Hat OpenShift AI para apoyar operaciones de centro de operaciones de red (NOC)…’ CaseStudy. https://www.redhat.com/en/success-stories/arsat. Accessed 2026-05-29.

²¹⁹ AR-EV-0081: ‘La iniciativa de Software Público de la Subsecretaría de Gobierno Digital (ONTI, dependiente de…’ Policy. https://argentina.gob.ar/jefatura/innovacion-publica/ssetic/onti/software-publico. Accessed 2026-05-29.

²²⁰ AR-EV-0082: ‘La Disposición ONTI 2/2019 aprobó el Código de Buenas Prácticas para el desarrollo de software…’ Policy. https://www.boletinoficial.gob.ar/detalleAviso/primera/206660/20190430. Accessed 2026-05-29.

²²¹ AR-EV-0083: ‘La Provincia de Santa Fe sancionó la Law No. 12360 el 15 de diciembre de 2004, reglamentada por…’ Regulation. https://www.santafe.gob.ar/index.php/web/content/view/full/3601. Accessed 2026-05-29.

²²² AR-EV-0084: ‘El mercado latinoamericano de sistemas de gestión de bases de datos está dominado por Oracle…’ Data. https://www.informesdeexpertos.com/informes/mercado-latinoamericano-de-sistemas-de-gestion-de-bases-de-datos. Accessed 2026-05-29.

²²³ AR-EV-0086: ‘La organización oficial argob en GitHub aloja 43 repositorios; los más populares corresponden a…’ Data. https://github.com/argob. Accessed 2026-05-29.

²²⁴ AR-EV-0093: ‘Mi Argentina, la plataforma de identidad digital ciudadana, supera los 21 millones de personas…’ CaseStudy. https://www.argentina.gob.ar/noticias/se-renueva-mi-argentina-con-mas-y-mejores-servicios-para-la-ciudadania. Accessed 2026-05-29.

²²⁵ AR-EV-0096: ‘El sector argentino de software y servicios informáticos exportó USD 2.674 millones en 2024, un…’ Data. https://cessi.org.ar/2025/05/21/el-software-argentino-genero-mas-de-6-000-empleos-y-alcanzo-un-record-de-exportaciones/. Accessed 2026-05-29.

²²⁶ AR-EV-0097: ‘Argentina Law No. 27506 (Régimen de Promoción de la Economía del Conocimiento), in force since 1…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/ley-27506-324101/actualizacion. Accessed 2026-05-29.

²²⁷ AR-EV-0098: ‘Mercado Libre lideró el ranking de aplicaciones más descargadas en Argentina en 2024 con 11,7…’ CaseStudy. https://mobiletime.la/noticias/23/01/2025/apps-mas-descargadas-2024/. Accessed 2026-05-29.

²²⁸ AR-EV-0099: ‘Mercado Pago superó los 50 millones de usuarios activos mensuales en LATAM en 2024 y reportó USD…’ Data. https://investor.mercadolibre.com/. Accessed 2026-05-29.

²²⁹ AR-EV-0101: ‘El segmento de digital banking argentino está concentrado en tres jugadores domésticos: Ualá (6…’ Data. https://fintechnews.am/fintech-argentina/52228/argentinas-top-3-digital-banks-capture-nearly-90-market-share/. Accessed 2026-05-29.

²³⁰ AR-EV-0102: ‘WhatsApp (Meta) tiene una penetración del 93% entre usuarios mayores de 16 años en Argentina, e…’ Data. https://www.infobae.com/tecno/2025/04/04/radiografia-digital-que-hacen-los-argentinos-en-internet-y-en-que-redes-sociales-pasan-mas-tiempo/. Accessed 2026-05-29.

²³¹ AR-EV-0103: ‘Google posee el 94,01% del mercado de búsquedas en Argentina a abril de 2026 (Bing 4,13%, Yahoo…’ Data. https://gs.statcounter.com/search-engine-market-share/all/argentina. Accessed 2026-05-29.

²³² AR-EV-0104: ‘Auth0, empresa argentina de autenticación digital fundada en 2013, fue adquirida en 2021 por Okta…’ CaseStudy. https://www.infobae.com/economia/2021/06/23/otra-tech-argentina-se-convirtio-en-unicornio-y-es-el-sexto-local-que-hace-y-quien-es-el-millennial-autodidacta-que-la-fundo/. Accessed 2026-05-29.

²³³ AR-EV-0107: ‘No se identificó fuente Tier-1 que documente cifras consolidadas y auditables de participación de…’ Gap. Accessed 2026-05-29.

²³⁴ AR-EV-0108: ‘La Disposición 1/2021 de la Dirección Nacional de Ciberseguridad crea el Centro Nacional de…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/241077/20210222. Accessed 2026-05-29.

²³⁵ AR-EV-0109: ‘Durante 2024, el CERT.ar registró 438 incidentes de ciberseguridad, una cifra 15% superior a los…’ Data. https://www.argentina.gob.ar/jefatura/innovacion-ciencia-y-tecnologia/ciberseguridad/informes-de-la-direccion-nacional-de. Accessed 2026-05-29.

²³⁶ AR-EV-0112: ‘La Decisión Administrativa 641/2021 aprueba los Requisitos Mínimos de Seguridad de la Información…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/350000-354999/351345/norma.htm. Accessed 2026-05-29.

²³⁷ AR-EV-0114: ‘Por Decree 941/2025 del Poder Ejecutivo (publicado el 2 de enero de 2026 en el Boletín Oficial) se…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/337032/20260102. Accessed 2026-05-29.

²³⁸ AR-EV-0116: ‘En abril de 2024 se difundió en Telegram una base con datos de aproximadamente 5,7-6 millones de…’ CaseStudy. https://www.lanacion.com.ar/seguridad/la-venden-a-us-3700-hackearon-la-base-de-datos-nacional-de-licencias-de-conducir-y-muestran-las-de-nid16042024/. Accessed 2026-05-29.

²³⁹ AR-EV-0117: ‘El 25-26 de diciembre de 2024 los sitios oficiales Mi Argentina y la plataforma de la tarjeta SUBE…’ CaseStudy. https://www.infobae.com/politica/2024/12/26/lo-hicimos-por-diversion-los-hackers-que-atacaron-los-sitios-del-gobierno-dijeron-que-no-tenian-segundo-factor-de-autenticacion/. Accessed 2026-05-29.

²⁴⁰ AR-EV-0119: ‘El RENAPER detectó en 2021 el uso indebido de una clave otorgada a un organismo público (Ministerio…’ CaseStudy. https://www.argentina.gob.ar/noticias/el-renaper-detecto-el-uso-indebido-de-una-clave-otorgada-un-organismo-publico-y-formalizo. Accessed 2026-05-29.

²⁴¹ AR-EV-0120: ‘No se identificó fuente Tier-1 que documente investigación criptográfica argentina con publicación…’ Gap. Accessed 2026-05-29.

²⁴² AR-EV-0121: ‘No se identificó capacidad documentada de ciberseguridad ofensiva soberana (red team gubernamental…’ Gap. Accessed 2026-05-29.

²⁴³ AR-EV-0122: ‘La Law No. 26388 de Delitos Informáticos, sancionada el 4 de junio de 2008, incorporó al Código Penal…’ Regulation. https://www.argentina.gob.ar/normativa/nacional/ley-26388-141790/texto. Accessed 2026-05-29.

²⁴⁴ AR-EV-0125: ‘Law No. 25506 (2001) establishes the legal validity of digital and electronic signatures in Argentina…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/70000-74999/70749/norma.htm. Accessed 2026-05-29.

²⁴⁵ AR-EV-0126: ‘Article 15 of Law No. 27078 — which had designated TIC services as essential and strategic public…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/235000-239999/239771/texact.htm. Accessed 2026-05-29.

²⁴⁶ AR-EV-0131: ‘Resolución AAIP 161/2023 created the Programa de Transparencia y Protección de Datos Personales en…’ Policy. https://www.boletinoficial.gob.ar/detalleAviso/primera/293363/20230904. Accessed 2026-05-29.

²⁴⁷ AR-EV-0132: ‘President Javier Milei has publicly positioned Argentina to compete as a low-regulation AI hub…’ CaseStudy. https://chequeado.com/el-explicador/argentina-polo-de-inteligencia-artificial-que-propone-el-gobierno-de-javier-milei-y-que-chances-hay-de-que-suceda/. Accessed 2026-05-29.

²⁴⁸ AR-EV-0133: ‘The Ministerio de Desregulación y Transformación del Estado (created July 2024 under Federico…’ Data. https://www.argentina.gob.ar/desregulacion. Accessed 2026-05-29.

²⁴⁹ AR-EV-0134: ‘Argentina lacks a horizontal platform-regulation statute. The intermediary-liability bill…’ CaseStudy. https://rest.hcdn.gob.ar/web/proyectos/290487/adjuntos/104934. Accessed 2026-05-29.

²⁵⁰ AR-EV-0135: ‘Argentina cybersecurity-incident response framework rests on dispositions of the Dirección…’ Regulation. https://www.argentina.gob.ar/jefatura/innovacion-publica/direccion-nacional-ciberseguridad/normativa. Accessed 2026-05-29.

²⁵¹ AR-EV-0139: ‘The Argentina national AI ecosystem framework — the Plan Nacional de Inteligencia Artificial…’ Report. https://oecd-opsi.org/wp-content/uploads/2021/02/Argentina-National-AI-Strategy.pdf. Accessed 2026-05-29.

²⁵² AR-EV-0140: ‘La Resolución AAIP 126/2024, en vigor desde el 1 de junio de 2024, aprueba el régimen sancionatorio…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/308122/20240524. Accessed 2026-05-29.

²⁵³ AR-EV-0141: ‘La Resolución AAIP 126/2024, publicada en el Boletín Oficial el 24 de mayo de 2024 y en vigor desde…’ Regulation. https://servicios.infoleg.gob.ar/infolegInternet/anexos/395000-399999/399750/norma.htm. Accessed 2026-05-29.

²⁵⁴ AR-EV-0142: ‘La Comisión Nacional de Defensa de la Competencia (CNDC) archivó el 2 de julio de 2025 la…’ CaseStudy. https://www.lanacion.com.ar/tecnologia/la-cndc-archivo-la-investigacion-contra-whatsapp-y-meta-por-presunto-abuso-de-posicion-dominante-nid08072025/. Accessed 2026-05-29.

²⁵⁵ AR-EV-0144: ‘La AAIP sancionó a Google Argentina SRL y Google LLC mediante la Resolución 69/2020 por…’ CaseStudy. https://www.argentina.gob.ar/noticias/sancion-google-por-negar-el-derecho-de-acceso. Accessed 2026-05-29.

²⁵⁶ AR-EV-0148: ‘En 2024 la CNDC emitió 89 decisiones en control de concentraciones y una única multa por…’ Data. https://legalblogs.wolterskluwer.com/competition-blog/main-developments-in-competition-law-and-policy-2024-argentina/. Accessed 2026-05-29.

²⁵⁷ AR-EV-0158: ‘IRAM (Instituto Argentino de Normalización y Certificación), founded in 1935, is Argentina sole…’ Report. https://www.iram.org.ar/en/who-we-are/. Accessed 2026-05-29.

²⁵⁸ AR-EV-0160: ‘Editors from Universidad Tecnológica Nacional (UTN, Santa Fe Regional Faculty) serve as editor or…’ CaseStudy. https://uit.frsf.utn.edu.ar/. Accessed 2026-05-29.

²⁵⁹ AR-EV-0161: ‘The official ITU-T Study Group 20 management roster for the 2025-2028 study period (period 18)…’ Data. https://www.itu.int/net4/ITU-T/lists/mgmt.aspx?Group=20&Period=18. Accessed 2026-05-29.

²⁶⁰ AR-EV-0162: ‘Verónica Marinelli, coordinator of IRAM Subcommittee on Information Security, Cybersecurity and…’ CaseStudy. https://www.iram.org.ar/novedades/novedades-en-seguridad-de-la-informacion/. Accessed 2026-05-29.

²⁶¹ AR-EV-0163: ‘Argentina was elected President of CITEL Steering Committee (COM/CITEL) at the VII CITEL Assembly…’ Report. https://www.argentina.gob.ar/jefatura/innovacion-publica/ssetic/citel. Accessed 2026-05-29.

²⁶² AR-EV-0168: ‘No organisation domiciled in Argentina appears among the 329 (as of May 2026) Member organisations…’ Gap. https://www.w3.org/membership/list/. Accessed 2026-05-29.

²⁶³ AR-EV-0169: ‘On 5 February 2026 the Argentine Foreign Ministry announced the signature of the United…’ Policy. https://www.cancilleria.gob.ar/es/actualidad/noticias/argentina-y-estados-unidos-firmaron-un-acuerdo-sobre-comercio-e-inversiones. Accessed 2026-05-29.

²⁶⁴ AR-EV-0170: ‘Argentina participated in the second cycle of the UN Open-Ended Working Group (OEWG) on Security of…’ Report. https://www.argentina.gob.ar/noticias/argentina-participo-en-naciones-unidas-de-un-grupo-de-trabajo-sobre-tic-y-seguridad. Accessed 2026-05-29.

²⁶⁵ AR-EV-0171: ‘In November 2024 Beatriz Anchorena, head of Argentina Access to Public Information Agency (AAIP)…’ CaseStudy. https://www.argentina.gob.ar/noticias/beatriz-anchorena-titular-de-la-aaip-fue-electa-presidenta-del-comite-del-convenio-108-del. Accessed 2026-05-29.

²⁶⁶ AR-EV-0178: ‘A Personal Data Protection bill (HCDN 1948-D-2025) introduced in the Argentine Chamber of Deputies…’ Analysis. https://iapp.org/news/a/novedades-legislativas-en-argentina-sobre-protecci-n-de-datos-personales-e-inteligencia-artificial. Accessed 2026-05-29.

²⁶⁷ AR-EV-0181: ‘Argentina R&D investment fell to 0.216% of GDP in 2024, the lowest historical figure on record…’ Data. https://periferia.com.ar/indicios/la-inversion-en-ciencia-y-tecnologia-llego-a-su-mayor-deterioro-historico-en-2024/. Accessed 2026-05-29.

²⁶⁸ AR-EV-0182: ‘Law No. 27614 (Ley de Financiamiento del Sistema Nacional de Ciencia, Tecnología e Innovación…’ Regulation. https://www.iade.org.ar/noticias/ley-de-financiamiento-del-sistema-nacional-de-ciencia-tecnologia-e-innovacion-en-argentina. Accessed 2026-05-29.

²⁶⁹ AR-EV-0186: ‘Clementina XXI, supercomputadora adquirida por Argentina vía Iniciativa Nacional de Supercómputo…’ CaseStudy. https://www.argentina.gob.ar/noticias/argentina-pone-en-funcionamiento-la-supercomputadora-clementina-xxi. Accessed 2026-05-29.

²⁷⁰ AR-EV-0187: ‘El proyecto QUANTEC del Grupo de Circuitos Cuánticos del Centro Atómico Bariloche (CNEA-CONICET)…’ CaseStudy. https://www.argentina.gob.ar/noticias/cientificos-del-centro-atomico-bariloche-buscan-crear-un-procesador-cuantico-con-circuitos. Accessed 2026-05-29.

²⁷¹ AR-EV-0188: ‘La convocatoria 2023 de Proyectos de Fortalecimiento de Infraestructura Experimental en CyT…’ Policy. https://www.argentina.gob.ar/ciencia/financiamiento/fort-exper-cytcuanticas-2023. Accessed 2026-05-29.

²⁷² AR-EV-0191: ‘En el Ranking Scimago Institutions 2024, CONICET figura como la principal institución gubernamental…’ Report. https://www.scimagoir.com/rankings.php?country=ARG. Accessed 2026-05-29.

²⁷³ AR-EV-0193: ‘Existen grupos argentinos publicando trabajos de aprendizaje automático y visión por computadora…’ Analysis. https://scholar.google.com/citations?user=ArqlkTUAAAAJ&hl=en. Accessed 2026-05-29.

²⁷⁴ AR-EV-0196: ‘In 2024 CONICET cut doctoral scholarship allocations by approximately 30%, awarded 950 scholarships…’ Policy. https://www.scidev.net/america-latina/news/mas-becas-en-un-clima-incierto-para-hacer-ciencia-en-argentina/. Accessed 2026-05-29.

²⁷⁵ AR-EV-0197: ‘Argentina 2025 budget projects Science and Technology investment at approximately 0.2% of GDP —…’ Data. https://periferia.com.ar/indicios/el-presupuesto-2025-deja-la-inversion-en-ciencia-y-tecnologia-al-nivel-del-2002/. Accessed 2026-05-29.

²⁷⁶ AR-EV-0198: ‘Universidad Tecnológica Nacional (UTN) produces 42.75% of Argentina engineering graduates…’ Data. https://frba.utn.edu.ar/dia-de-la-ingenieria-la-utn-forma-mas-del-40-de-los-ingenieros-que-se-graduan-en-el-pais/. Accessed 2026-05-29.

²⁷⁷ AR-EV-0200: ‘Argentina is in the top 30 nations with highly-skilled emigrants according to OECD data, with…’ Data. https://www.untref.edu.ar/mundountref/argentina-se-convirtio-en-un-polo-de-emigracion. Accessed 2026-05-29.

²⁷⁸ AR-EV-0202: ‘Argentine remote workers for foreign employers earn between USD 2,500 and USD 5,000 per month on…’ Data. https://www.infobae.com/economia/2024/09/15/los-argentinos-que-trabajan-para-el-exterior-ganan-entre-2500-y-5000-dolares-por-mes/. Accessed 2026-05-29.

²⁷⁹ AR-EV-0203: ‘The RAICES Programme (Red de Argentinos Investigadores y Científicos en el Exterior), created in…’ Policy. https://www.argentina.gob.ar/ciencia/seppcti/raices. Accessed 2026-05-29.

²⁸⁰ AR-EV-0207: ‘In the EduRank Latin America Computer Science ranking, UBA is #1 in Argentina and #555 worldwide…’ Data. https://edurank.org/cs/la/. Accessed 2026-05-29.

²⁸¹ AR-EV-0212: ‘Argentina software industry reached USD 22,221 million in revenue in 2024 (+13.1% interannual)…’ Data. https://www.itsitio.com/ar/software/software-argentino-bate-records/. Accessed 2026-05-29.

²⁸² AR-EV-0214: ‘In 2022 Argentine SBC exports were USD 8,047 million, with software making up 33%, professional…’ Data. https://argendata.fund.ar/topico/servicios-basados-en-el-conocimiento/. Accessed 2026-05-29.

²⁸³ AR-EV-0215: ‘Argentina has been losing global software-export market share — from 0.6% of global sales in 2011…’ Analysis. https://www.lanacion.com.ar/economia/despertar-el-potencial-de-la-industria-del-software-una-estrategia-para-el-futuro-nid14082024/. Accessed 2026-05-29.

²⁸⁴ AR-EV-0217: ‘Auth0 — co-founded in 2013 by Argentine engineers Eugenio Pace (ITBA) and Matías Woloski…’ CaseStudy. https://www.roadshow.com.ar/como-nacio-auth0-el-unicornio-argentino-que-se-vendio-en-us-6500-millones/. Accessed 2026-05-29.

²⁸⁵ AR-EV-0218: ‘Argentine startups raised USD 412 million across 62 funding rounds in 2024 (46 seed rounds at USD…’ Data. https://www.lanacion.com.ar/economia/negocios/los-emprendedores-argentinos-levantaron-mas-de-us412-millones-en-2024-nid11062025/. Accessed 2026-05-29.

²⁸⁶ AR-EV-0219: ‘Law No. 27742 Bases y Puntos de Partida para la Libertad de los Argentinos (sanctioned July 2024)…’ Policy. https://chequeado.com/el-explicador/openai-invertira-us-25-000-millones-en-un-data-center-para-ia-en-la-argentina-las-claves-del-anuncio/. Accessed 2026-05-29.

²⁸⁷ AR-EV-0220: ‘Within Argentina R&D ecosystem the software industry accounts for 14% of total business R&D…’ Data. https://www.argentina.gob.ar/noticias/el-potencial-de-id-en-sectores-productivos-de-la-economia-del-conocimiento-software-y-ag-0. Accessed 2026-05-29.

²⁸⁸ AR-EV-0222: ‘Argentina software industry employs more than 140,000 people formally — exceeding employment in…’ Report. https://fund.ar/publicacion/introduccion-a-la-industria-del-software/. Accessed 2026-05-29.

²⁸⁹ AR-EV-0225: ‘La Law No. 27738, sancionada el 10 de octubre de 2023 y publicada en el Boletín Oficial el 23 de…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/296574/20231023. Accessed 2026-05-29.

²⁹⁰ AR-EV-0226: ‘La Resolución 282/2025 de la Secretaría de Innovación, Ciencia y Tecnología (Jefatura de Gabinete)…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/333751/20251031. Accessed 2026-05-29.

²⁹¹ AR-EV-0227: ‘La Decisión Administrativa 899/2024, publicada el 24 de septiembre de 2024, crea la Mesa…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/314465/20240924. Accessed 2026-05-29.

²⁹² AR-EV-0229: ‘El Banco Interamericano de Desarrollo aprobó en 2023 un préstamo por USD 35 millones a Argentina…’ CaseStudy. https://www.argentina.gob.ar/noticias/nuevo-programa-de-35-millones-de-dolares-para-el-desarrollo-de-la-inteligencia-artificial. Accessed 2026-05-29.

²⁹³ AR-EV-0230: ‘La Agenda Digital 2030 fue presentada por el gobierno de Mauricio Macri el 5 de noviembre de 2018…’ Policy. https://www.argentina.gob.ar/noticias/el-gobierno-presento-la-nueva-agenda-digital-2030. Accessed 2026-05-29.

²⁹⁴ AR-EV-0232: ‘El Decreto de Necesidad y Urgencia 70/2023, emitido el 20 de diciembre de 2023, declaró la…’ Regulation. https://www.boletinoficial.gob.ar/detalleAviso/primera/301122/20231221. Accessed 2026-05-29.

²⁹⁵ AR-EV-0234: ‘El Ministerio de Ciencia, Tecnología e Innovación fue creado por Decree 21/2007 bajo la…’ CaseStudy. https://es.wikipedia.org/wiki/Ministerio_de_Ciencia,_Tecnolog%C3%ADa_e_Innovaci%C3%B3n_(Argentina). Accessed 2026-05-29.

²⁹⁶ AR-EV-0235: ‘La Función Ciencia y Tecnología del Presupuesto Nacional cayó un 11,4% adicional en el primer…’ Data. https://ciicti.org/el-2026-llego-con-mas-recortes-presupuestarios-a-la-ciencia-argentina/. Accessed 2026-05-29.

²⁹⁷ AR-EV-0236: ‘El programa Conectar Igualdad —creado en 2010 por Decree 459/10, suspendido durante la…’ CaseStudy. https://palabrasdelderecho.com.ar/articulo/5007/Prorrogaron-la-vigencia-del-Programa-Conectar-Igualdad-por-dos-meses. Accessed 2026-05-29.

²⁹⁸ AR-EV-0237: ‘El gobierno argentino articula públicamente la ambición de convertir al país en uno de los cuatro…’ Policy. https://www.telesemana.com/blog/2024/12/02/argentina-trabaja-en-desregulacion-energia-y-analisis-de-marcos-normativos-para-convertirse-en-el-hub-de-la-inteligencia-artificial-de-sudamerica/. Accessed 2026-05-29.

²⁹⁹ AR-EV-0238: ‘La fundación Fundar argumenta que la estrategia de IA del gobierno Milei tiene un talón de…’ Analysis. https://fund.ar/publicacion/la-estrategia-de-milei-en-inteligencia-artificial-tiene-un-talon-de-aquiles/. Accessed 2026-05-29.

³⁰⁰ AR-EV-0240: ‘El Poder Legislativo no sancionó la Ley de Presupuesto Nacional 2025: el Decree 425/2025 y la…’ Data. https://chequeado.com/el-explicador/presupuesto-2025-las-5-claves-para-entender-la-prorroga-definida-por-el-gobierno-de-javier-milei/. Accessed 2026-05-29.

Pablo Martínez Pablo Martínez serves as Coordinator of this report. He is a senior full-stack developer and the lead of the SUDOCU project at the National University of General Sarmiento (UNGS).

Germán Pinazo Germán Pinazo is the President and a professor at the National University of General Sarmiento (UNGS), whose research focuses on political economy and economic development.

This study was written by Neville Roy Singham, chair of Tricontinental: Institute for Social Research’s advisory board. The author acknowledges with gratitude the crucial support of the Tricontinental team, spanning multifaceted research, comprehensive statistical analysis, technical infrastructure, and the production of this publication. An earlier version of this study was published in Guancha (观察者网), whose editors provided valuable advice for further research and analysis. The author takes full responsibility for any errors or omissions in this work.

As we commemorate the 80th anniversary of the victory in the World Anti-Fascist War (WAFW), the Western powers spin their familiar tale: US industrial might and British resolve saved the world from fascism. This is a lie. The truth burns in the numbers: while the Western powers calculated their economic advantage, the Soviet and Chinese peoples paid in blood. Fascism was defeated not by Anglo-American capital but by socialist leadership and mass heroism – a brilliant strategy from Moscow and Yan’an, unbreakable resilience from workers and peasants who refused to surrender, and a sacrifice that saved humanity from slavery.

The real war began not in 1939, when Adolf Hitler invaded Poland, but in 1931, when Japan invaded Northeast China (东北).¹ For ten years, China fought mainly alone except for Soviet aid, which included planes and pilots. Britain, France, and the United States sent only minimal aid to China from 1937 to 1941. Washington and London would rather count profits.

Throughout the same decade, the Soviet Union raced against time, force-marching industrialisation while knowing invasion was imminent. Josef Stalin’s February 1931 speech to industrial managers predicted with terrible precision: ‘We are fifty or a hundred years behind the advanced countries. We must make good this distance in ten years. Either we do it, or we shall go under’.² Ten years later – June 1941 – the Wehrmacht invaded. The USSR had exactly one decade to prepare for a war everyone knew was coming. The preparation was not enough to prevent the initial catastrophe, but it was exactly enough to enable recovery.

The Atlantic powers’ initial strategy until just before their entry into the war was simple and cynical: let fascism and communism destroy each other.

1. The West’s Deliberate Delay: A Strategy of Treachery

The timeline of Western betrayal speaks for itself. From 1931 to 1941, as Japan carved up China, Western banks maintained their offices in Tokyo, Western oil fuelled Japanese warships, and Western scrap metal became Japanese bullets.³ When full-scale invasion erupted in 1937 – the Rape of Nanjing, the terror bombing of Chinese cities – the Allied imperialists’ response was to sell more oil to Japan. The US provided 80% of Japan’s petroleum until 1941.⁴

This was not isolation but calculated provision – fascism executing what the failed White Encirclement could not accomplish. By 1941, 250 US corporations operated in Nazi Germany.⁵ Thomas Watson of IBM automated the Holocaust while maintaining personal friendships with both US President Franklin D. Roosevelt and Secretary of State Cordell Hull.⁶ General Motors’ German subsidiary Opel produced Wehrmacht trucks until 1944, with GM later claiming a $22.7 million tax write-off for its ‘abandoned’ Nazi operations.⁷ The US continued strategically to be economically, politically, and militarily committed to the destruction of the Soviet Union.

Western historiography attributes this late US entry to ‘isolationism’. This ahistorical view ignores documented precedent: during the White Encirclement of 1919, the US deployed 11,500 troops to Russia – 4,500 to Arkhangelsk and 7,000 to Vladivostok – alongside British, French, and Japanese forces, fighting the Red Army directly with over 500 US casualties.⁸ US President Woodrow Wilson also provided more than $50 million in military support to White armies. When direct military intervention failed to nip socialism in the bud, the strategy shifted. US policymakers consistently favoured right-wing autocrats who promised stability and anti-Bolshevism over democratic movements. This policy produced open support for European fascism. In 1933, President Roosevelt stated that he was ‘deeply impressed by what [Benito Mussolini] has accomplished and by his evidenced honest purpose of restoring Italy’.⁹

The first British strategy, even when it entered the war, was to let Hitler and Stalin exhaust each other. When Germany invaded Poland in September 1939, Britain and France, while declaring war on Germany, did nothing – the ‘Phoney War’ lasted eight months while they hoped Hitler would turn east. Winston Churchill’s anti-communist hatred defined his career. In 1919, he sought to ‘strangle Bolshevism in its cradle’.¹⁰ By 1945, with Hitler barely dead, he planned Operation Unthinkable – using Wehrmacht forces to attack the Soviet Union.¹¹

Churchill’s genocidal impulses targeted communists and colonised peoples equally. His racial violence was extensive: celebrating killing ‘savages’ at Omdurman (1898), supporting concentration camps that killed forty-eight thousand Africans and Boers, and advocating poison gas for Iraqi ‘uncivilised tribes’ (1920). By 1942, as Bengal starved, he told Leo Amery, the secretary of state for India: ‘I hate Indians. They are a beastly people with a beastly religion’. When Amery begged for famine relief, Churchill replied that Indians ‘breed like rabbits’.¹² Three million Indians died while Britain exported Bengal’s rice. After Churchill’s India tirade, Leo Amery wrote in his diary: ‘I couldn’t help telling him that I didn’t see much difference between his outlook and Hitler’s’.¹³ Today, Britain venerates this man, who differed from Hitler only in his victory.

The US entered the war only when it was directly attacked at Pearl Harbor (Hawaiʻi) – a decade into Japan’s war against China. The Second Front, promised for 1942, was not delivered until June 1944 – 730 days late, after the battles at Stalingrad (1942–1943) and Kursk (1943) had already broken the Wehrmacht’s spine.¹⁴ By D-Day, the Red Army had already destroyed the myth of German invincibility and Nazi defeat was already determined. The US and Britain had to invade continental Europe in 1944, by which time the Soviet Union had already guaranteed the defeat of Germany, to ensure that the socialist USSR did not liberate the entire continent, threatening capitalism in Western as well as Eastern Europe.

US priorities were clear: better a fascist Europe than a socialist one. Better Japanese domination of Asia than Chinese liberation and the expansion of socialism. The metropolitan powers’ hatred of communism and love of their colonies outweighed their anti-fascist principles.

2. When Inter-Imperialist Rivalries Mattered

The Western strategy towards Nazi Germany followed a logic established in 1917. When British intervention failed to overthrow the Bolsheviks, geopolitical theorist Halford Mackinder – appointed high commissioner to organise support for the White Army – recommended that German rearmament, though dangerous to British interests, was essential as a bulwark against Bolshevik control of Eastern Europe. The Treaty of Versailles (1919), as economist Thorstein Veblen observed, was fundamentally ‘a compact for the reduction of Soviet Russia’ – a goal that, while ‘not written into the text of the Treaty’, was nonetheless ‘the parchment upon which the text was written’.¹⁵ This remained Western strategy through 1945: contain and destroy the USSR, even if it meant enabling fascism.

At Munich in 1938, British Prime Minister Neville Chamberlain formalised this strategy with Hitler: Germany would receive a ‘free hand’ in Eastern Europe to attack the USSR in exchange for respecting British imperial interests. Yet inter-imperialist rivalry imposed limits. Britain wanted Hitler to destroy the Soviet Union but feared that unchecked German expansion would threaten the British Empire itself – the contradiction explains both the collusion and Britain’s eventual war declaration.

When Britain sent negotiators to Moscow by slow merchant ship, Admiral Reginald Drax arrived without written authority – the message was unmistakable: no real alliance with communists.¹⁶ Foreign Secretary Halifax praised Hitler in a 1937 meeting as a ‘bulwark against Bolshevism’, while a 1939 government-endorsed pamphlet by Lord Lloyd of Dolobran identified Hitler’s ‘final apostasy’ not as invading Poland but as signing the German-Soviet pact—‘the betrayal of Europe’.¹⁷ Facing isolation, Stalin signed the Molotov-Ribbentrop Pact in August 1939 – not from choice but from necessity created by Western collusion with Hitler.

In the following twenty-two months (September 1939–mid-June 1941), the Soviet Union more than tripled its army from 1.6 to 5.3 million, doubled its tank production from 2,794 units in 1940 to 6,590 in 1941 (including 1,225 T-34s), and moved entire industries eastward. US attachés reported massive industrial transfers to the Urals by late 1940, before the invasion. The USSR pushed its borders 200–300 kilometres west, trading space for time. Stalin knew war was coming.¹⁸

In May 1940, Churchill became prime minister as France and Britain’s army fled Dunkirk. Foreign Secretary Viscount Halifax proposed negotiating peace through Mussolini – Germany could have Europe if Britain kept its empire.¹⁹ Churchill opposed this plan, not from principle but out of arithmetic. If Germany were allowed to conquer Europe, its strength would mean it could later overturn any peace agreement and defeat Britain. To take only one example, the Caucasus produced 25.4 million tonnes of oil annually – 80% of Soviet output. Germany had 3.1 months of oil reserves.²⁰ If Germany’s Chancellor Adolf Hitler seized Soviet resources, Britain faced certain defeat.

By continuing the war, Churchill forced Germany to maintain forty-nine divisions in Western Europe and Norway – 24% of total Wehrmacht strength that could not be deployed against the USSR.²¹ While significant, this did not prevent the assembly of history’s largest invasion force.

Germany launched Operation Barbarossa with 153 German divisions totalling over 3 million troops. The Imperial War Museum, Britain’s unrepentant national museum, calculates that 80% of the German Army was committed to this invasion.²² Additionally, 36 Axis-allied divisions joined the assault – 16 Finnish, 15 Romanian, 3 Italian, and 2 Slovak – bringing the total to 189 divisions. This force of nearly 4 million troops represented the overwhelming concentration of Axis military power. The Eastern Front was not another theatre of war but the primary site of fascist aggression, where the Wehrmacht deployed its best units, most experienced commanders, and maximum strength.

This was the largest military invasion in human history. Yet the Soviet Union defeated this unprecedented assault through its own strategic depth, mass mobilisation, and industrial relocation.

Facing extremely powerful adversaries, Stalin and Mao Zedong took into account how to exploit inter-imperialist rivalries that became so intense by the 1940s. These inter-imperialist contradictions – contingent moments when empire’s internal conflicts accidentally serve revolutionary forces – are usually brief and unreliable. They emerge unpredictably from capitalism’s internal contradictions, must be recognised and leveraged when they appear, but never mistaken for a strategic alliance.

3. Economic Power in 1941: The Myth of Western Might

In 1941, world GDP totalled approximately $4.5–$5 trillion (in 1990 international dollars). Those with the greatest capacity to fight fascism deliberately chose not to do so.

As documented by economic historian Mark Harrison in his book The Economics of World War II (1998), the Anglo-American imperial core commanded approximately 30.2% of world GDP. The US alone controlled $1,094 billion – roughly 22–24% of global output – while maintaining comfortable neutrality a decade into the WAFW. The British Empire added $344 billion (7–8% of world GDP), extracted from 427 million colonial subjects. In total, this camp (the US and its territories and the British Empire as defined by the British in 1941) controlled 28.6% of the world’s population. The US remained neutral until it was attacked. Britain declared war but prioritised empire.

Sources: Population data mainly from Maddison (2010); GDP data mainly from Harrison (1998), p. 10, table 1.3; USSR population for 1941 from Statista (2025); China and world-total GDP are corroborated estimates by Tricontinental: Institute for Social Research. See appendix for full methodology.

The US dedicated just 11% of its GNP to military spending before Pearl Harbor. The US military in December 1941 fielded only 1.62 million troops from a population of 133.9 million – just 1.2% of its population was under arms. By contrast, Germany had 7.3 million troops from a population of 70.2 million (10.4%), and the Soviet Union had 7.1 million from a population of 195.4 million (3.6%) by year’s end. Britain, despite declaring war in 1939, had reached 53% of national expenditure on military efforts, but much of this went to protecting empire, not fighting fascism directly. In North Africa, British forces fought to maintain colonial control, not liberate populations. Churchill’s quote: ‘I have not become the King’s First Minister to liquidate the British Empire’. ²³

Sources: Troops data from Harrison (1998), p. 14, table 1.5; population from Maddison (2010) and Statista (2025). See appendix for full methodology.

The fascist-imperialist Axis had weaponised its economies. Germany devoted 52% of GNP to military spending in 1941, reaching 70% by 1943, and fielded 3 million troops for the Barbarossa invasion (1941). Other Axis powers fielded an additional 500,000 to 700,000 troops (Romania, Finland, Hungary, Italy, and Slovakia), thus allowing Hitler to claim that this was a pan-European operation. It was and remains the largest military invasion in human history. Japan maintained 1.7 million soldiers in China with a military burden of 27% of GDP after a decade of continuous warfare.

The Axis, led by Germany, Italy, and Japan, also included pact signatories Hungary, Romania, Slovakia, Bulgaria, and Croatia, with Finland as a co-belligerent. The Axis powers and the territories they controlled commanded approximately 20.1% of world GDP. This figure was composed of contributions from Germany proper ($412 billion), the annexed territory of Austria ($29 billion), Japan ($196 billion), Italy ($144 billion), the heavily industrialised occupied territory of France ($130 billion), and the other members (approximately $47 billion). In addition to this, ‘neutral’ collaborators, including Switzerland, Sweden, Spain, and Portugal, contributed a separate 2.6% of world GDP to the Axis economic sphere.

The socialist camp – the Soviet Union and Chinese Communist base areas that would tie down 60% of Japanese forces – represented approximately 8% of world GDP with $359 billion. By mid-1941, with German armies deep in Soviet territory, even this was shrinking. Yet the Soviets had mobilised 28% of GNP for military expenditure. The Red Army expanded the army’s peacetime strength from 1.5 million on 1 January 1938 to over 5 million in June 1941.²⁴

China’s tragedy was written in numbers. Controlling 23% of the world’s population (490–525 million people), China generated only around 5% of world GDP after its century of humiliation and a decade of Japanese devastation. Official data from the Kuomintang (KMT) government is scarce. In 1937, the year of full escalation of Japanese aggression, the estimate for KMT troops was 1.7 million; by 1941, the US military estimated 3.8 million troops. A scholarly monograph on Chinese military history estimated that there were 6 million KMT troops in the summer of 1941.²⁵ The people’s army, led by the Communist Party of China (CPC), grew from 56,000 in 1937 to around 440,000 in 1941 and 1.3 million in 1945.²⁶ With little domestic arms production, military capacity depended on foreign supplies, especially from the Soviet Union. China had people but few weapons, courage but little industry, resistance but scant resources.

The pattern of foreign aid exposed priorities. Between October 1937 and June 1941, while the US watched, the Soviet Union provided China with over $250 million in credits, 1,235 aircraft, thousands of artillery pieces, tens of thousands of machine guns, as well as ammunition and supplies.²⁷ The Soviets sent more than 2,000 pilots – 200 of whom died defending Chinese cities – and military advisers.²⁸ While the USSR was fighting for survival, it still managed to send aid that represented 0.07% of Soviet GDP annually. Soviet pilots flew combat missions over Nanjing, Wuhan, and Chongqing. Before Pearl Harbor, the US provided almost nothing despite commanding 22–24% of world GDP.

Even after entering the war, China received just $632 million in Lend-Lease aid (1941–1945) while Britain, along with its two white settler states (Australia and New Zealand), received $25.8 billion of the $30.3 billion assigned by the US to the ‘British Empire’.

Sources: Lend-Lease aid numbers from US Department of State (1945), p. 14, table 2, and pp. 42–43, table 25; population data from Maddison (2010); China death data from Bian (2012), pp. 401–405; India death data from Sen (1977), p. 36. See appendix for full methodology.
*‘British India’ here refers to India and today’s Pakistan and Bangladesh. The Lend-Lease aid and population numbers for British India and Ceylon (now Sri Lanka) are included here.
*‘White settler states’ refers to Australia and New Zealand.

Chart 1: Per capita aid: whites received $442.3 per person; non-whites (China, British India, and Ceylon) received $4.4 – a 101:1 ratio

Chart 2: Per death valuation: white deaths ‘valued’ at $52,913; non-white (China, British India) deaths at $155 – a 341:1 ratio

The British Empire in 1945 (as defined by the US in the Lend-Lease Programme) consisted of 58.3 million whites and 443.1 million non-white subjects. The mathematics was simple: the US directed 85.1% of the British Empire’s Lend-Lease aid to whites, who comprised only 11.6% of the Empire’s population.

From 1945 to 1948, the US provided at least $1.4 billion to Chiang Kai-shek’s government, with over half being military aid – double the $700 million in military aid given during the WAFW – excluding substantial surplus property sales.²⁹ Additional aid continued through 1949 when the Nationalists lost the civil war. The formula: minimal help against Japan, maximum support against communism.

Poignant observations were made by two articles in Historical Review published by the China Academy of Social Sciences in August 2025:

First: Overall, in the early stages of the full-scale War of Resistance, the Soviet Union’s vital assistance to a China engaged in an arduous struggle was like ‘offering fuel in snowy weather’.

Second: After the end of the Anti-Japanese War, the US actively aided and supported the Kuomintang reactionaries in launching a civil war and signed the seemingly reciprocal but actually unequal ‘Sino-American Treaty of Friendship, Commerce, and Navigation’ with the Nationalist government, aiming to maintain influence over China through economic control and military intervention.

The economic arithmetic was clear: the Anglo-Americans had the money but would not fight. The fascists had militarised everything. The socialists had little but gave all.

Source: Harrison (1998), p. 21, table 1.8. See appendix for a verbatim transcript of the source data.

4. China’s Fourteen-Year Resistance: The Forgotten Foundation of Victory

China’s fourteen-year resistance against Japanese imperialism tied down the bulk of Japanese land forces throughout the war. Chinese forces prevented over half a million Japanese soldiers from attacking the Soviet Far East or sweeping through the Pacific.³⁰ As the war progressed, increasing numbers of KMT soldiers defected to the Communist forces, strengthening the guerrilla resistance. Every Chinese soldier who held a position with obsolete weapons and an empty stomach prevented a Japanese soldier from fighting elsewhere. China’s military weakness made its resistance more heroic, not less.

The Red Army soldiers who fled Ruijin, site of the first Chinese Soviet Republic, crossed frozen mountains in straw sandals in 1935 while KMT bombers with US engines hunted them from above.³¹ Blood froze in their footprints. Toes turned black and fell off. Those who survived became the core of guerrilla forces that by 1940 tied down 60% of Japanese troops.

The following numbers shatter every myth about who won this war:

Sources: USSR data from Andreev et al. (1993); China data from Bian (2012), pp. 401–405; India data from Sen (1977), p. 36. See appendix for full methodology.

The deployment patterns expose the truth: socialist forces were desperately engaged in existential struggle while capitalist forces carefully husbanded their strength for post-war advantage.

5. The Blood Price: Who Really Defeated Fascism

The global struggle against fascism killed 85 million human beings.

That is 3.8% of humanity: dead.

Sources: USSR death data from Andreev et al. (1993); China death data from Bian (2012), pp. 401–405; French Indochina population from Budge (2014) and death data from The National WWII Museum New Orleans (n.d.); other population data from Maddison (2010). See appendix for full methodology.

Who paid this price reveals who saved the world. The arithmetic will destroy every lie that the late arrivals have said about this war, not as statistics but as accusations. Every number is a crime – every percentage a verdict.

59.8% socialists dead, 13.1% colonised peoples dead – only 1% Anglo-Americans dead.

This was not their war. It was their profit.

Sources: USSR data from Andreev et al. (1993); China data from Bian (2012), pp. 401–405 and p. 442. See appendix for full methodology.

But even these deaths tell only half the horror. The wounded – those who survived maimed, traumatised, broken – vanished from Western history. We restore them here: thirteen to eighteen million Soviets wounded – ignored. Each lived with pain that Washington and London never felt. Every Western soldier wounded became a casualty worthy of pensions, medals, remembrance. The eleven to twenty-six million wounded Chinese vanished from history as if they never existed, never suffered, never mattered.

The arithmetic convicts: socialist forces suffered 59.8% of all WAFW deaths with less than 15% of world GDP. In Korea, 99% of deaths were Korean or Chinese. In Vietnam, 99% of the deaths were Southeast Asian. The pattern screams across three wars, across five decades, and across continents – those with nothing saved humanity while those with everything preserved their strength for the post-war plunder.

6. The Soviet Union Destroyed Fascism in Europe

The Red Army eliminated or decisively defeated the Wehrmacht’s strength in battles that decided humanity’s fate: Moscow, Stalingrad, Kursk, and Berlin. The price: 27 million Soviet deaths.³² That’s 13.8% of the Soviet population based on a population of 196.0 million in 1940. That is 1.2% of the entire world’s population wiped out because they stood between fascism and the rest of us.

These were not abstract statistics. Whole villages where no men between the ages of eighteen and fifty survived. The Soviet Union inflicted 9 million of Germany’s 11.1 million military casualties. This victory was partly possible because China’s resistance prevented Japan from attacking the Soviet Far East during 1941–1942 when Moscow hung by a thread. As President Vladimir Putin acknowledged in 2025, China’s resistance was ‘one of the crucial factors that prevented Japan from stabbing the Soviet Union in the back during the darkest months’.

Among Soviet deaths were 1.3 million Jews murdered in the Holocaust’s eastern killing fields, 3.3 million prisoners of war deliberately starved in German camps, and millions of civilians killed in accordance with Generalplan Ost (Master Plan for the East) and other Nazi racial policies targeting ‘subhuman’ Slavs.³³

7. China’s Demographic Catastrophe

At least 23.6 million deaths were documented from 1937 to 1945 alone – 20.6 million direct deaths from combat and massacres, plus 3 million from the 1942 Henan famine caused by the Japanese disruption. Before that, from 1931 to mid-1937, the Japanese invasion also resulted in an estimated 450,000 deaths. The total documented deaths from 1931 to 1945: 24.05 million. With wounded included, total casualties reached 35 million. However, even this staggering figure understates the catastrophe. When including the 15 million who were never born because of the war’s destruction, China’s total population loss exceeded 50 million. The West acknowledges perhaps 15–20 million dead, ignores the wounded entirely, and erases the demographic hole that took generations to fill.³⁴

The forced-labour system added another dimension to this genocide: from 1935 to 1945, 20% of the 11.5 million forced labourers in Northeast China died (2.3 million deaths). Among the 38,935 forced labourers shipped to Japan, 17.5% were killed in the emperor’s homeland, according to Chinese Academy of Social Sciences historian Bian Xiuyue.³⁵ This research documents the genocide in precise terms, not with vague estimates.

The Western insistence on counting only deaths performs a double erasure. When 35 million Chinese were killed or wounded, focusing only on the West’s understated count of 20 million or fewer deaths erases at least 11 million wounded people whose lives were destroyed by Japanese aggression.

China’s 2015 government survey, involving 600,000 participants, documented systematic extermination through multiple methods. The Nanjing Massacre: 300,000 killed in six weeks and an estimated 20,000–80,000 rapes.³⁶ Japan’s ‘Three Alls’ campaign – ‘Kill all, burn all, loot all’ – turned entire provinces into graveyards. Even regular POW camps revealed a national chauvinism extermination policy: Japan killed 99.9% of Chinese prisoners but only 27.1% of Western POWs.³⁷

8. The Colonial Holocaust: Eleven Million Erased

While the imperial powers preserved their strength, their colonies bled. A total of 11.2 million colonial subjects died – more than ten times the total Anglo-American war death toll.

The Bengal Famine of 1943 killed 3 million Indians through British policy. While Bengalis starved, Britain exported rice from Bengal and denied relief ships.³⁸ Churchill told his private secretary that ‘the Hindus were a foul race protected by their mere pullulation from the doom that is their due’. He wished that Air Chief Marshal Arthur Harris, head of the British Bomber Command, could ‘send some of his surplus bombers to destroy them’.³⁹

The Dutch East Indies lost 3.4 million people – 4.7% of the population. Both colonial powers killed them – the Dutch through centuries of extraction that left them defenceless, the Japanese through forced labour, starvation, and systematic violence.

In Java alone, 1.8 million excess deaths occurred between 1944 and 1945. The rōmusha forced-labour system sent 300,000 Indonesians overseas; only 77,000 returned.⁴⁰ On the Sumatra Railway alone, 17,000 of 22,000 Javanese labourers died – a mortality rate of 77%.

French Indochina: 1.5 million deaths – 6.5% of the population. The 1944–1945 famine killed 1–2 million Vietnamese through the combined extraction of Japanese requisitions and continued French colonial administration.

Burma: 270,000 to perhaps as high as 1 million dead under Japanese occupation while Britain fled, destroying oil fields but abandoning the Indian labourers and Burmese civilians who had no means of escape. The Thailand-Burma Railway (402 kilometres) killed 215 people per kilometre of track laid: 31 Western POW deaths per kilometre, 184 Asian labourer deaths per kilometre – a six-fold racial calculus.⁴¹ The shorter Kra Isthmus Railway (90 kilometres) had an even higher mortality rate of 537 deaths per kilometre (Huff, 2020), constructed entirely by Asian workers whose deaths went largely undocumented by Japanese authorities. Of an estimated 260,000–270,000 total workers on both railways, approximately 90,000–140,000 Asian labourers perished, including significant numbers among the more than 100,000 Malays and Tamils conscripted from British territories.

Malaya and Singapore: up to 150,000. Philippines: 765,000.⁴² Portuguese Timor: 14% to 19% of its population – the highest death rate of any territory in South Asia.⁴³

The colonial arithmetic: killed by fascist occupation while colonial masters hoarded resources. Indians starved; Britain had grain. Indonesians died; Dutch extraction had built nothing to save them. Vietnamese perished; France maintained its extraction apparatus even under Japanese rule.

Eleven million colonial deaths. Museums memorialise the 12,000 US and Filipino soldiers who died in the Bataan Death March.⁴⁴ The rōmusha who built the Burma Railway – 90,000–100,000 dead – have no museum nor movie like Bridge on the River Kwai (1957).

9. Africa: Two Million Erased

Africa became the Allies’ emergency reserve when France fell, and the Western colonies in Asia were lost to Japan. Britain, France, and Belgium extracted maximum resources from African colonies while fighting a war supposedly for freedom. Between 1.6 and 2 million Africans died – from fascist invasion, forced labour, combat service, and systematic starvation. Colonial authorities, who tracked copper production down to the metric tonne, never counted African deaths.

Ethiopia: The First Battlefield

The WAFW began in Africa in 1935 when Italy invaded Ethiopia. A 1945 Ethiopian government memorandum documented 760,300 deaths: 275,000 battle deaths, 300,000 from hunger among refugees, 75,000 patriots killed during occupation, 35,000 in concentration camps, 30,000 in the February 1937 Addis Ababa massacre, 24,000 executions, 17,800 civilians killed by air strikes. Despite signing the Geneva Protocol, Italy used 300–500 tonnes of mustard gas and dropped 4,336 aerial bombs filled with sulphur mustard and 540 bombs containing diphenylchlorarsine on Ethiopia. Soviet analysts calculated that these chemical weapons caused 30% of Ethiopian combat deaths. At Ametsegna Washa cave in 1939, Italian forces gassed and machine-gunned over 5,500 Ethiopians.

Ethiopian women fought as armed combatants (arbegna) against Italian occupation – the Ethiopian government’s official Book of Honour, 1935–1941 documented their sacrifice, recording one-third of its names as women patriots who took up arms against fascism, though Western histories erase them entirely.⁴⁵ These women learned to use rifles and grenades, endured aerial bombardment and mustard gas attacks, and in some cases took command of troops. By March 1948, the UN War Crimes Commission identified 1,200 Italian war criminals from the Ethiopian campaign. Prosecutions: zero.⁴⁶ Badoglio, who was implicated in the Italian genocide in Libya (1929–1934), went back to Italy to become Mussolini’s last prime minister.⁴⁷ The Italian field marshal who authorised the systematic use of chemical weapons that killed tens of thousands of Ethiopians became the Anglo-Americans’ ‘valuable asset’ against communism.

When the Bonomi government appeared ready to arrest Badoglio, Prime Minister Churchill sent a ‘Personal and Top Secret’ telegram on 8 December 1944 to Sir Noel Charles, the British ambassador in Rome, stating: ‘You are responsible for the Marshal’s safety and sanctuary in the British Embassy or in some equally safe place to which he can be removed’.

Combat Service

Nearly one million Africans served. France deployed 100,000 African soldiers against Germany in 1940 – 17,500 killed. Morocco sent 90,000 troops to France. In Burma, 90,000 African soldiers constituted 9% of imperial forces. The 82nd West African Division suffered 2,085 casualties – the highest in the XV Corps.

Military apartheid structured everything. African privates received one-third of white soldiers’ pay, and corporal punishment remained legal for Africans until 1946. Officers were so rare among the 500,000 African soldiers that each was known by name. The racial discrimination extended beyond institutional policy into brutal violence: in 1940, the Nazis massacred 3,000 Black French soldiers and Hitler kept African POWs in captivity while releasing white prisoners.

Extraction Mathematics

Africa supplied 98% of Allied industrial diamonds, 90% of cobalt, 50% of gold production, and 39% of chromite. The British conscripted 100,000 men for Nigerian tin mines between 1942 and 1944. Death rate from disease on the Tente Dam: 10%.⁴⁸ Production increase: 6%. In Belgian-occupied Congo, mandatory labour reached 120 days annually. French West Africa: 38,153 men in forced-labour armies. Entire villages fled – 6,000 from Forécariah to Sierra Leone.

The Shinkolobwe mine provided uranium for the atom bombs used on Hiroshima and Nagasaki. The ore: 75% uranium oxide versus 0.2% considered marketable in North America. Congolese miners handled radioactive ore bare-handed. Their names: never recorded. Their deaths: never counted.⁴⁹

Forced crop substitution created famine. Mozambique: 800,000 in forced cotton cultivation. Cape Verde: 24,643 dead from wartime famine. Nigeria: Groundnut exports rose, while millet production was abandoned. Starvation followed export ledgers.

The Betrayal

1 December 1944, Thiaroye, Senegal: French officers massacred West African veterans demanding back pay. Official count: 35 dead. Military archives: 70 dead. Current historical research: 300–400 dead. The archives contain falsified documents and remain classified eighty years later, deemed ‘sensitive’.

Victory in Europe Day, 8 May 1945: French forces began killing Algerians in Sétif and Guelma. Algeria counts 45,000 dead.⁵⁰ France admits to 1,500.

The 1945 Nigerian general strike.

Madagascar, 1947: 40,000 killed, crushing independence.

French West African railway strike, 1947–1948: 160 days, 20,000 workers on strike.

Gold Coast (now Ghana), 1948: British Superintendent Imray personally shot three veteran protest leaders.

General strikes erupted from Durban to Tunis, from Dakar to Dar es Salaam. Mombasa, 1947: 15,000 workers paralysed the city.

Witwatersrand, 1946: African miners struck despite 1,248 wounded by police.

The pattern was set: veterans demanding wages were massacred, workers demanding rights were shot, independence movements would be crushed. France would kill 1.5 million in Algeria. Britain would cage 1.5 million Kenyans. Portugal would burn Mozambique. The veterans who survived fascism now understood the enemy. Within a decade, liberation wars would erupt from Algeria to Kenya, from Angola to Mozambique – led and influenced by socialist movements and leaders who learned that the West’s six-hundred-year formula never changed: maximum extraction, maximum death, minimum acknowledgement, no accountability.

The 1935–1945 accounting the colonial powers never made: between 1.6 and 2 million Africans dead. Ethiopia alone: 760,000. Military deaths: 75,000. Forced labour and famine: hundreds of thousands. Colonial authorities documented copper down to the metric tonne: 262,394 tonnes. African deaths: ‘unrecorded’.

10. How Socialism Defeated Fascism Through Superior Strategy

Three battles proved Japan could be beaten. At Pingxingguan (平型关) in 1937, Communist forces killed over 1,000 Japanese and captured 82 vehicles – Japan’s first defeat.⁵¹ At Taierzhuang (台儿庄) in 1938, the Japanese were routed. There are varying historical estimates. One 1996 study estimates that there were 20,000 casualties among 55,000 Japanese soldiers.⁵² At Wanjialing (万家岭) on 10 October 1938, an entire Japanese division – 31,000 troops – was reduced to 1,000 survivors. It was Japan’s darkest day.

The CPC’s Hundred Regiments Offensive of 1940 – a series of coordinated strikes across northern China – shattered Japanese infrastructure. The CPC’s forces tied down 60% of Japanese forces and 95% of puppet forces – not some vague ‘bulk’ but a precise, bleeding majority.⁵³ ‘Sparrow warfare’ (麻雀战) made Japanese patrols bleed for every mile. Tunnel warfare in Ranzhuang (冉庄) in 1939: sixteen kilometres long, connecting five villages, guerrillas appearing and vanishing like ghosts.⁵⁴

The defeat of fascism was not just about sacrifice; it was a brilliant strategy that turned initial weakness into strength. Socialist leadership did not just mobilise the masses; it outthought and outfought its enemies, despite every material advantage.

Soviet innovation transformed defeat into total victory. The USSR faced an impossible equation: while constructing humanity’s first socialist society from the ruins of tsarism’s feudal system – transforming social relations of production and reproduction at an unprecedented scale – it had exactly one decade to build a military-industrial capacity for the inevitable war.

When German armies smashed through Soviet defences in June 1941, Western observers gave the USSR weeks to survive. Within six months, the USSR imposed the first major strategic defeat on Nazi Germany with the Moscow counteroffensive; within eighteen months the Red Army was decimating entire German army groups. The secret lay in combining revolutionary military doctrine with unprecedented social mobilisation. Deep battle theory envisioned rupturing enemy lines at multiple points, then exploiting with reserves to annihilate entire fronts. When the crisis arose, 1,523 factories were loaded onto 1.5 million railcars and evacuated beyond the Urals in five months under Luftwaffe bombardment.⁵⁵ Seventeen million Soviet citizens evacuated with their factories.⁵⁶ The Kirov Works was evacuated from Leningrad to Chelyabinsk, where 5,800 machines were installed and operational in less than three weeks – in roofless halls, with workers living in tents at –40°C.⁵⁷

Soviet tank production rose from 6,590 in 1941 to 24,719 in 1942 – nearly quadrupling despite catastrophic losses.⁵⁸ The Soviets produced over 100,000 tanks and self-propelled guns total, versus Germany’s 43,000 (1941–1945).⁵⁹ The T-34 so devastated Wehrmacht forces that German engineers desperately tried to copy it and failed. Even RAND Corporation admitted that it was the ‘epitome of creative design’.⁶⁰

Stalin created the State Defence Committee (GKO) on 30 June 1941, which coordinated this unprecedented evacuation. Workers laboured around the clock and built new factories around the equipment as trains arrived. By March 1942, these evacuated plants were producing at pre-war levels. The Germans had captured areas containing 40% of the population, 60% of coal, steel, and aluminium production, yet Soviet military output surpassed German production by 1942.⁶¹ Only a socialist-led society could achieve this miracle of relocation while under invasion.

This was scientific superiority.

Stalingrad demonstrated a superior battle strategy over German tactical excellence. General Georgy Zhukov let the Germans pour their best units into urban combat where tank superiority meant nothing. Every building became a fortress; every room became a battlefield. While German forces exhausted themselves in the city, Soviet reserves massed on the flanks. Operation Uranus in 1942 struck with mathematical precision, targeting the Romanian armies Germany had positioned on its flanks – weaker Axis-allied forces holding critical positions. Multiple simultaneous attacks shattered these Romanian armies and encircled the entire Sixth Army.

By the war’s end, Soviet offensives routinely destroyed entire German army groups across thousand-mile fronts. The same army that collapsed in 1941 was by 1944 conducting operations of complexity and scale that no capitalist military could match.

This was not heroism alone, but the fusion of Marxist science with mass creativity. Where capitalist armies preserved professional forces, the Soviet system mobilised everyone. By 1942, women in the Red Army numbered 800,000. By 1945, there were 246,000 women in uniform on the front line – snipers, pilots, tank crews, not just nurses.⁶² Partisan warfare tied down 500,000 German troops with locally organised forces; approximately 205,600 partisans were organised behind German lines by 1 July 1944.⁶³ Despite losing most of its prewar industrial base, the USSR outproduced Germany in every category that mattered: 112,100 combat aircraft to Germany’s 89,500.⁶⁴ Of Germany’s 3–3.5 million military deaths, 2.6–3.1 million died fighting the Red Army; of their 11.1 million total casualties, 9 million came on the Eastern Front.⁶⁵ From 1941 to 1942, Germany had to deploy 72–80% of its entire military strength along this 3,000-kilometre front – and lost them there. While the Allied imperialists faced 54 German divisions on D-Day, the Red Army was simultaneously dismantling and destroying 156½ divisions in the East.⁶⁶

Meanwhile, Chinese innovation overcame the Japanese superiority in arms. The CPC transformed China’s weakness into strength. Its Eighth Route Army and New Fourth Army tied down 60% of Japanese forces through guerrilla warfare. Its ‘comprehensive resistance’ turned every farmer into a supplier, every worker into a saboteur, every student into an organiser.

The KMT’s conventional forces engaged the remaining 40% but faced severe challenges in battle despite some notable defensive victories.

In On Protracted War (1938), Mao provided a scientific analysis: Japan was strong but small, isolated, and barbaric; China was weak but vast, progressive, and with time on its side. Mao predicted three phases – strategic defensive, strategic stalemate, strategic counteroffensive – exactly how the war unfolded. The prophecy proved exact.

The rear battlefield became Japan’s bleeding wound. Communist forces established bases throughout the occupied territories, implementing land reform to mobilise peasants and democratic governance to unite all patriotic classes against the invader. By the stalemate phase, guerrilla warfare tied down 60% of Japanese troops and 95% of puppet forces. Tunnel warfare, mobile warfare, and landmine warfare – each tactic exploited Japanese vulnerabilities. The occupiers controlled the cities and railways; the resistance controlled everything else.

The Hundred Regiments Offensive of 1940 proved the occupied zones were graveyards, not colonies. Coordinated strikes across northern China destroyed Japanese infrastructure and shattered the myth of pacification. Every blown railway, every ambushed convoy demonstrated a simple truth: superior weapons meant nothing when every village was hostile, every peasant an intelligence network, every night an opportunity for attack. The Japanese found themselves drowning in an ocean of people’s war.

This was scientific application of revolutionary theory to concrete conditions. The equation proved exact: correct political line plus mass mobilisation equals military miracles. China proved that imperialism’s technical superiority crumbles when an entire people refuse to be enslaved.

The contrast with capitalist military leadership was also stark. US and British commanders had every advantage: larger forces, uninterrupted supply lines, overwhelming air support. Yet they moved cautiously, preserving forces rather than eliminating enemies. Operation Market Garden (1944) failed. The Ardennes caught them by surprise. It took them eleven months to advance from Normandy to Berlin, a distance the Red Army covered in four months while fighting more challenging battles.⁶⁷

The US ‘production miracle’ was actually inefficiency. Manufacturing productivity fell 1.4% annually during the war. Cost-plus contracts guaranteed profit regardless of waste – corporations were paid all costs plus profit. The Truman Committee’s verdict: ‘War is waste – waste of manpower and material’.⁶⁸ The formula: maximum profit, minimum efficiency, let others bleed.⁶⁹

Socialist and colonised peoples: 73% of all deaths.

Anglo-Americans: 1%.

Sources: Author’s elaboration based on Mukerjee (2010), p. 205 and pp. 246–247; Murayama (1995); Nie, Guo, Selden, and Kleinman (2010), p. 5; Kohn and Harahan (1988), p. 88; Stone (1952), p. 312.

11. Fascism’s Anti-Communist Laboratory: The Domestic Rehearsal for Global Genocide

Before fascism turned outward to conquer nations, it perfected mass murder at home. From 1931 to 1945, fascist regimes systematically exterminated 216,000–286,000 communists and leftists across Germany, Spain, Italy, and Japan – not casualties of war but deliberate political genocide.⁷⁰ Millions more faced imprisonment, torture, and exile.

This was the rehearsal for what was to come next, watched with approval by the colonial metropoles. Better dead communists than red revolution. While fascism perfected its killing techniques on communists at home, the imperial ‘liberal democracies’ calculated their economic advantages.

Germany industrialised political murder, and its first targets were the Communists. In the November 1932 elections, the Communist Party of Germany (KPD) was a massive political force, securing nearly 6 million votes (16.9% of the total).⁷¹ This entire political world was targeted for annihilation. Following the Reichstag Fire in February 1933, the Nazi regime launched its first mass wave of terror. Conservative data indicate that at least 100,000 political opponents were arrested in 1933 alone, with 600 dying in custody; the KPD leadership’s own estimate placed these figures at 130,000 arrested and 2,500 murdered.⁷²

These early arrests filled the first concentration camps – such as Oranienburg and the notorious Dachau – which became the laboratories for industrialised extermination. The chaotic brutality of the Sturmabteilung (SA) soon gave way to the bureaucratic terror of the Schutzstaffel (SS). By the end of 1933, at least 27,000 people were held in the camps, the vast majority political prisoners – 80% were members of the KPD and 10% from the Social Democratic Party of Germany.⁷³ There, methods of dehumanisation were refined. By 1937 the red triangle marking political prisoners was the precursor for the classification of all victims, and the system of torture and forced labour became standard practice. The assault on the Communists established the blueprint for the Holocaust; over the course of the Nazi regime, approximately 150,000 Communists would be imprisoned, and between 20,000 and 30,000 would be murdered or executed.⁷⁴ The torture and murder of communists served as the laboratory where Nazis perfected techniques later deployed against Jews, Roma, and Slavs.

Spain turned political cleansing into a science. Franco murdered 150,000 to 200,000 civilians behind the lines and executed 50,000 Republicans after March 1939.⁷⁵ The prison population reached 233,000 by 1941.

The Badajoz massacre (1936): 4,000 unarmed leftists slaughtered.⁷⁶ International Brigades volunteers faced a 30% casualty rate – Nationalists often executed international prisoners.⁷⁷ In 1940, Franco refused Nazi requests to repatriate Spanish Republicans from French camps, declaring them stateless – condemning more than 10,000 to Nazi concentration camps.

Japan’s Special Higher Police arrested 65,000 under the Peace Preservation Law.⁷⁸ Torture was policy – the autopsy of proletarian writer Kobayashi Takiji in 1933 revealed systematic brutality.⁷⁹ Between 1942 and 1945, one Jinzhou court in Manchukuo alone sentenced 1,700 to death and 2,600 to life for ‘thought crimes’.

Italy had already demonstrated the pattern before 1931: squadristi carried out 2,120 acts of anti-socialist violence between 1919 and 1922, including 709 killings, while systematically attacking socialist councils and worker organisations across the Po Valley and throughout Emilia-Romagna.⁸⁰ Though these pre-1931 murders are not counted in our figures above, they established fascism’s violent blueprint. By 1943, the OVRA, Mussolini’s secret police, had compiled surveillance files on 130,000 suspected subversives.

Western leaders did not just know – they applauded.⁸¹ Churchill stated in 1937: ‘I will not pretend that, if I had to choose between Communism and Nazi-ism, I would choose Communism’. To decode this Harrow (upper-class private school) circumlocution, Churchill was announcing he preferred Hitler to Stalin while preserving the linguistic escape route of never having actually said so.

This support extended from political and media elites to industrial capital, with US industrialist Henry Ford providing a direct ideological blueprint for Nazism. Hitler called Ford his ‘inspiration’ and kept a large portrait of him in his Munich office. Ford’s antisemitic book, The International Jew: The World’s Foremost Problem (1920–1922), was translated and ‘circulated to millions throughout Germany’, promoting the core Nazi fiction of a ‘Judeo-Bolshevik’ conspiracy to control the world. Hitler copied passages from it for Mein Kampf (1925), and high-ranking German officials alleged that Ford provided some of the Nazi Party’s earliest funding. In July 1938, Hitler awarded Ford the Grand Cross of the German Eagle, the highest decoration the Third Reich could give a foreigner.⁸² Every Western handshake with fascism was signed in communist blood.

These techniques would later return in Indonesia, Chile, El Salvador – anywhere people chose socialism over subjugation.

12. The Anti-Communist Crusade: From Hidden Agenda to Open War

The Atomic Bombings: The First Act of the Cold War

The atomic bombings of Hiroshima and Nagasaki on 6 and 9 August 1945 targeted the Soviet Union more than Japan. Japan was already defeated. Admiral William Leahy, the highest-ranking US military officer and Truman’s chief of staff, wrote in his 1950 memoir: ‘The use of this barbarous weapon at Hiroshima and Nagasaki was of no material assistance in our war against Japan. The Japanese were already defeated and ready to surrender’. General Dwight Eisenhower told Secretary of War Stimson in July 1945: ‘Japan was already defeated… dropping the bomb was completely unnecessary’.

The July 1946 US Strategic Bombing Survey concluded that Japan would have surrendered by November 1945 ‘even if the atomic bombs had not been dropped, even if Russia had not entered the war, and even if no invasion had been planned or contemplated’. Historian Gar Alperovitz documents similar opposition from five additional five-star US officers.⁸³

Yet the bombs were dropped. The timing exposes the calculation. At the Yalta Conference (4–11 February 1945), the Soviet Union committed to enter the war within three months of Germany’s surrender – establishing an 8–15 August deadline. Philip Morrison, a Manhattan Project physicist, revealed in 1948 that ‘the scientists responsible for making the bomb were pushed to meet a “mysterious” deadline in which it was to be ready by “a date near August tenth”’. The Trinity test succeeded on 16 July 1945 during the Potsdam Conference. Truman issued the bombing directive on 25 July. Hiroshima: 6 August 1945. Soviet declaration of war: 8 August. Soviet invasion of Manchuria: early morning of 9 August. Nagasaki: 9 August, hours after the Soviet offensive began.

President Truman’s Potsdam diary reveals his calculations. On 17 July, after meeting Stalin: ‘He’ll be in the Jap War on August 15th. … Japs [will be finished] when that comes about’. He noted contentious issues with the Soviets, then wrote: ‘I have an ace in the hole and another one showing’. On 18 July: ‘Believe Japs will fold up before Russia comes in. I am sure they will when Manhattan appears over their homeland’. Secretary of State James Byrnes was explicit. His aide Walter Brown’s diary recorded on 24 July that Byrnes hoped that ‘after [the] atomic bomb Japan will surrender and Russia will not get in so much on the kill’. Secretary of War Stimson’s diary entries from May 1945 describe the bomb as giving Washington ‘all the cards’, a ‘royal straight flush’ in dealing with Moscow, and the ‘master card’ in US diplomacy.⁸⁴

The Soviet invasion destroyed Japan’s last strategic hope. The atomic bombing of Hiroshima did not trigger immediate surrender negotiations. The Supreme War Council did not convene an emergency meeting on 7 or 8 August. The Soviet declaration of war on 9 August forced Prime Minister Kantarõ Suzuki to call the first emergency meeting that same morning to discuss surrender. Emperor Hirohito’s 17 August rescript cited Soviet entry as ‘endangering the very foundation of the Empire’s existence’ – not the atomic bombs.

Patrick M. S. Blackett, the British Nobel Prize-winning physicist, provided the first systematic analysis in his 1949 book Fear, War, and the Bomb: Military and Political Consequences of Atomic Energy. Blackett argued that ‘the dropping of the atomic bombs was not so much the last military act of the Second World War, as the first major operation of the cold diplomatic war with Russia now in progress’.

Japan had already offered to negotiate peace terms with one condition: preservation of the emperor. A US invasion remained months away. The Soviet Union was preparing to enter the war on August 8. The US objective, Blackett explained, was to force Japanese surrender before the Soviets could advance into Manchuria and ensure that Japan surrendered to the US alone.⁸⁵

The United States killed 110,000–210,000 Japanese civilians to demonstrate atomic monopoly and secure exclusively US occupation of Japan, avoiding the four-power partition that complicated Germany. This was the first act of the Cold War, not the last act of the WAFW.

The Unbroken War: From Tokyo to Seoul

The moment fascism fell, the mask dropped. The Atlantic powers’ true strategic enemy had always been communism, not fascism. The WAFW was barely over before the killing resumed – now aimed directly at any nation choosing socialist development.

The timeline reveals the truth:

• August 1945: Japan surrenders.
• September–October 1945: Ho Chi Minh declares Vietnamese independence; the British release and rearm French troops in Saigon; and the US provides eight transport ships to ferry French troops to attempt to reconquer Vietnam.⁸⁶
• Greek Civil War (1946–1949): Britain, then the US, crush the communists; 158,000 dead.⁸⁷
• Jeju Uprising in South Korea (April 1948): US-backed forces massacre 14,000–30,000.⁸⁸
• Fall 1950: Full-scale US invasion of Korea begins.

Five years from ‘victory over fascism’ to genocidal war against socialism. No pause. No peace. The same B-29s that firebombed Tokyo were firebombing the northern half of Korea in the ‘Fatherland Liberation War’. The killing never stopped – it just changed targets.

Japan surrendered in September 1945. By 1950 – just five years later – the US was incinerating Korea to prevent reunification under socialist leadership. The war killed 4.5 million Koreans while the US lost only 54,246. This excludes the 197,653 Chinese People’s Volunteers who sacrificed their lives defending Korea from US genocide.⁸⁹

North Korea Bore the Genocidal Brunt

Western estimates show that between 1.5 and 2.5 million Koreans from the Democratic People’s Republic of Korea (DPRK) were killed – 15.6% to 26.0% of their pre-war population. No official DPRK figures are publicly available, so we cannot provide the DPRK’s own accounting. Given the record, the DPRK is unlikely to be the sole case where Western tallies do not understate deaths.

The US dropped 635,000 tonnes of bombs and 32,557 tonnes of napalm on a country the size of Pennsylvania.⁹⁰ US General Curtis LeMay stated – and these are his exact words – ‘We… burned down every town in North Korea… we killed off – what – twenty percent of the population’.⁹¹

General MacArthur said: ‘The war in Korea has already almost destroyed that nation of 20 million people. I have never seen such devastation. I have seen, I guess, as much blood and disaster as any living man, and it just curdled my stomach the last time I was there. After I looked at that wreckage and those thousands of women and children and everything, I vomited’.⁹²

Sources: Shin (2001), Halliday and Cumings (1988); The Star-Ledger (1995); Vietnam Veterans of America (2025). See appendix for full methodology.

The US obliterated eighteen of the DPRK’s twenty-two major cities – with destruction in individual cities ranging from 65% to 100%, including the complete destruction of Sinanju and 95% of Sariwon.⁹³

With napalm and firestorms, there are no wounded – flesh burns, lungs sear, and everyone in the target area dies. The conventional bombing created countless more casualties – crushed under rubble, maimed by shrapnel, orphaned, and starving.

No nation in modern history has suffered such concentrated destruction.

China sent hundreds of thousands of volunteers to The War to Resist US Aggression and Aid Korea. Among the dead was Mao Anying, Mao Zedong’s son, killed in November 1950.

General Douglas MacArthur, the same man who had abandoned the Philippines in 1942, now ordered the Air Force to destroy ‘every installation, factory, city, and village’ north of the 38th parallel. The racist extermination tactics used against Japan now targeted any nation resisting capitalism.

Vietnam: The Pattern Continues

Vietnam confirmed the pattern. As France’s colonial war failed, the US seamlessly took over. From 1955 to 1975, Vietnam lost at least 3.1 million people – taken from various reports including those of the Socialist Republic of Vietnam.

This was not a ‘discrepancy’.

This was erasure.

US bombing: 7.66 million tonnes dropped across Vietnam, Laos, and Cambodia – 3.6 times the tonnage dropped in all sectors of the WAFW. Deaths in Laos and Cambodia are not separately documented in available sources but are included in the regional devastation.

3.1 million Vietnamese. 58,000 US soldiers.

The ratio: 53:1.

The US dropped more bombs on Vietnam than on all WAFW battlefields combined. Why? Because Vietnam’s example – successful resistance by a small nation against the world’s richest – threatened to inspire others.

When we calculate population percentages, the word ‘genocide’ becomes undeniable.

In the case of the DPRK, remember that 26% died. Remember that number when they speak of ‘humanitarian intervention’.

The pattern across three wars reveals systematic extermination. When 26% of a population dies, we call it genocide – unless the US is the génocidaire.

13. Manufacturing Memory

Hollywood transformed D-Day into the turning point in the WAFW, erasing Moscow, Stalingrad, and Kursk. US textbooks portrayed Lend-Lease as charity rather than delayed support that arrived after the most decisive battles. The atomic bomb became the war winner, not the Soviet armies racing towards Japan. This served as preparation, not just propaganda. If the US public believed that they had saved the world from fascism, they could be mobilised to ‘save’ it from communism. The same corporations that had done business with Hitler now profited from containing socialism.

The Ideological Apparatus: Money and Methods

Academic complicity ran through specific institutions and individuals. The Central Intelligence Agency (CIA) pumped tens of millions of dollars into the Congress for Cultural Freedom over seventeen years, waging what they called a ‘battle for men’s minds’.⁹⁴ Irving Kristol edited Encounter, Sidney Hook attended Berlin conferences – both received CIA funding through this network.⁹⁵ Hook promoted the ‘totalitarian twins’ thesis equating Stalin with Hitler. Arthur Schlesinger Jr., attending these same conferences, would later write The Vital Center (1949), arguing that US liberalism saved democracy, erasing at a minimum forty-five million Soviet and thirty-five million Chinese total casualties. Thomas Braden, who ran the CIA’s International Organisations Division, later confessed in the Saturday Evening Post: ‘I’m glad the CIA is “immoral”’ – boasting about buying an entire generation of intellectuals.⁹⁶

Those who documented socialist sacrifice faced systematic destruction. For example, William Appleman Williams faced repeated tenure denials, despite publishing in prestigious journals, for documenting US imperial expansion in The Tragedy of American Diplomacy (1959). A survey of 2,451 social scientists conducted in the spring of 1955 revealed agents had contacted 61% of professors – not for investigation but for intimidation.⁹⁷

Parallel to this ideological suppression, the Pentagon’s overwhelming financial power created a structural dependency that fostered a new academic culture – one of service to the national security state. Throughout the 1950s, the Department of Defense (DOD) accounted for the vast majority of all federal research spending, peaking at 83.8% of the total budget. This capital was not merely granted; it was targeted. The Korean War mobilisation doubled R&D funding to $1.3 billion, establishing university-managed military laboratories like MIT’s Lincoln Laboratory and Stanford’s Applied Electronics Laboratory. By 1960, these military contracts accounted for 40% of Stanford University’s entire operating budget, institutionalising a permanent dependency in the physical sciences.⁹⁸ The influence of DOD funding extended beyond the sciences. Academic ‘freedom’ meant Pentagon priorities – the architecture of intellectual capture. The message was clear: write about US heroism or lose your career.

Harvard requires two European languages for European history PhDs. For Chinese history: fourth-year modern Chinese, second-year literary Chinese, and third-year Japanese. The Japanese requirement was not neutral – US graduate students in Chinese studies were routinely sent to Kyoto for training, required to approach Chinese history through Japanese scholarly frameworks. To document China’s suffering, Western scholars first had to master the language of its invader.

Even scholars who clear these barriers produce systematic undercounts. Rana Mitter – Oxford’s leading China specialist with full linguistic access – estimates only 15 to 20 million Chinese deaths.⁹⁹ Chinese government documentation records 24.05 million deaths between 1931 and 1945, with 35 million total casualties, including both dead and wounded.¹⁰⁰ The pattern reveals erasure beyond language: methodological choices, source selection, and what counts as credible evidence.

Encyclopaedia Britannica – for over two centuries, the gold standard of Anglo-American knowledge production – reveals imperial historiography through what it counts and what it erases. Their WWII casualty table lists 1.31 million military deaths for China but provides no entry for civilian deaths or total deaths – just blank spaces.¹⁰¹ By contrast, Poland shows 5.675 million civilian deaths and 5.8 million total. Yugoslavia: 1.2 million civilian deaths, 1.505 million total. Even defeated Germany gets entries: 0.78 million civilian deaths, 4.2 million total. China – the nation that fought longest (1931–1945) – receives blanks where more than 24 million civilian deaths belong.

Encyclopaedia Britannica’s sardonic footnote: ‘The figures for China comprise casualties of the Chinese Nationalist forces during 1937–1945, as reported in 1946, and do not include figures for local armies and communists. Estimates of 2.2 million military dead and 22 million civilian deaths appear in some compilations but are of doubtful accuracy’. The gap represents not a counting error but decades of coordinated erasure.

The Appeasement Fiction: How Collusion Became Confusion

Western historiography transformed Neville Chamberlain’s calculated collusion with Hitler into a tale of naïve ‘appeasement’ – well-meaning but misguided efforts to avoid war. This fiction serves a purpose: if Chamberlain merely misjudged Hitler’s intentions, British strategy appears as honourable failure rather than anti-communist conspiracy. The documentary record destroys this myth.

Two days before meeting Hitler, Chamberlain wrote to King George VI stating his aim: an ‘Anglo-German understanding’ with Germany and England as ‘the two pillars of European peace and buttresses against communism’, acknowledging Hitler was determined ‘to proceed further East’.¹⁰² Over three September 1938 meetings, this strategy was formalised. At Godesberg on 22–23 September, Hitler made the deal explicit. As recorded by official German translator Dr Paul Schmidt, Hitler told Chamberlain: ‘we will not stand in the way of your pursuit of your non-European interests and you may without harm let us have a free hand on the European continent in central and South-East Europe’.¹⁰³

Chamberlain did not protest. The meeting ended, Schmidt noted, ‘in a completely friendly tone’. Britain’s ambassador to Germany later wrote: ‘Nor would the world have failed to acclaim Hitler as a great German if he had known when and where to stop: even, for instance, after Munich and the Nuremberg decrees for the Jews’.¹⁰⁴

As Monthly Review editor John Bellamy Foster observed, Chamberlain’s government sought ‘not so much to “appease” Nazi Germany, as to collude with it, in the hope that Germany would turn its guns eastward, toward the USSR’.¹⁰⁵ The transformation of documented collusion into the ‘appeasement myth’ represents another deliberate erasure – this time not of socialist sacrifice but of Western complicity in enabling fascism’s eastward expansion.

The Cultural Front: Propaganda as History

The Pentagon’s collaboration with Hollywood – documented in more than 2,500 productions – ensures that people in the United States learn history through films like Saving Private Ryan (1998) rather than through scholarship.¹⁰⁶ While Soviet films such as Come and See (1985) were effectively restricted to a maximum of one hundred theatres, Pentagon-approved films reached thousands of theatres.¹⁰⁷ Every suppressed Soviet film meant millions never learned that the Red Army destroyed ten Wehrmacht soldiers for every one the Western Allies faced. When Enemy at the Gates (2001) depicted Soviet soldiers sharing rifles – pure fiction according to Russian historians – it reached more viewers than all Soviet war films combined.¹⁰⁸ The Pentagon does not need to ban truth when it can drown it in well-funded lies.

The same erasure methodology operates across all socialist casualties. Vietnam documents 3.1 million deaths from 1955 to 1975; Western historians acknowledge 2 million. Guenter Lewy deflated US military body counts by 30% while dismissing Vietnamese government figures as ‘politically inflated’. The perpetrators become the accountants of their crimes.

History in Stone: Sanitising Fascism

The anti-communist crusade required more than erasing socialist victories; it required sanitising fascism. Nearly 1,500 monuments honouring Nazi collaborators now stand across 25 countries. In Germany and Austria, there are over 110. In the US – the supposed victor – there are 36.¹⁰⁹

First, their crimes were pardoned. Then, they were put on pedestals.

14. The Formula for Impunity: Capital, Science, and the Cold War

US Capital and the Nazi War Machine

The scale of US corporate collaboration with Nazi Germany demands closer examination. By 1941, 250 US corporations had embedded capital directly into the Nazi war machine’s industrial infrastructure.

Henry Ford’s involvement went beyond ideological support. With approval from Ford’s Dearborn executives, the company’s French subsidiary produced trucks for the German military even after Pearl Harbor, prompting a US criminal investigation under the Trading with the Enemy Act that was suppressed after Edsel Ford’s death in 1943.

After the war, accountability was sidelined as Ford rehired its Nazi-era German manager – who had used slave labourers from the Buchenwald camp – as a consultant in 1950.

IBM’s collaboration was personally managed by its president, Thomas J. Watson, who travelled to Germany multiple times and accepted a special medal from Hitler in 1937. Watson oversaw the customisation of IBM’s technology specifically for Nazi requirements, establishing a German subsidiary, Dehomag, to service the Reich’s needs while maintaining direct control. IBM’s Hollerith punch card machines – the forerunner to the computer – automated the Holocaust itself. The technology allowed the Nazis to efficiently identify Jewish populations through census data, manage the logistics of train transports to the death camps, and track prisoners within the camps themselves. IBM technicians serviced the machines on-site – nearly every camp, including Auschwitz, had a Hollerith Department. The five-digit numbers tattooed on inmates’ arms corresponded directly to the IBM punch card system used to manage them. Watson only returned his Nazi medal in 1940 under public pressure, but IBM’s machines kept running in the camps until liberation.

International Telephone & Telegraph (ITT), under president Sosthenes Behn – one of the first US executives to meet with Hitler on 3 August 1933 – entered into cartel agreements with the German firm Siemens & Halske and, as late as 1943, held a 29% stake in the aircraft manufacturer Focke-Wulf – whose planes killed Allied aviators and soldiers. A 1942 US government report noted Behn’s ‘unusual ability to get along with fascist governments and particularly with Nazi Germany’. After the war, the US government compensated ITT $27 million for Allied bomb damage to its German factories – paying US corporations for facilities that had produced weapons to kill US soldiers.¹¹⁰

General Motors’ Opel subsidiary became the Wehrmacht’s primary truck manufacturer. Opel’s Rüsselsheim plant produced the Opel Blitz truck, the primary transport vehicle used by the Wehrmacht in its invasions of Poland, France, and the Soviet Union. The Brandenburg plant alone produced 130,000 Blitz trucks by 1944. GM’s chief executive for overseas operations, James D. Mooney, received the Grand Cross of the German Eagle from Hitler in 1938. Throughout the war, GM’s plants used forced and slave labour supplied by the Reich. The financial manipulation was sophisticated: unable to repatriate profits after 1941, GM declared Opel ‘abandoned’ and claimed a $22.7 million tax write-off under special legislation Roosevelt signed in October 1942 – even while Opel continued producing for the Wehrmacht. After the war, GM regained control of its valuable German facilities and resumed operations. The company profited from pre-war collaboration (1933–1941), wartime tax benefits, and post-war recovery of industrial assets.

The suppression of this history constitutes another pernicious form of erasure – this time concerning the systemic integration of US capital into the Nazi war machine. Not one US corporate executive faced prosecution for operating concentration camp factories or automating the Holocaust. Instead, they collected compensation for bomb damage and tax write-offs for their ‘losses’. This evidence refutes the claim that President Franklin Roosevelt was merely constrained by public opinion; it documents a state policy that protected these powerful corporate interests. The formula was established: profit from building fascism’s capacity for genocide, then profit from fascism’s defeat.

Recruiting the Enemy: Nazi Industrialists and Scientists

While Nazi scientists received US laboratories, Nazi industrialists received US protection. Alfred Krupp – whose slave labourers built the Wehrmacht’s arsenal – walked free in 1951, his fortune restored by US decree.¹¹¹ The Quandt dynasty, enriched by concentration camp labour, became BMW billionaires.¹¹² Hermann Josef Abs, Hitler’s banker who financed Auschwitz, became an adviser to West Germany’s Chancellor Konrad Adenauer.¹¹³ Ferdinand Porsche, who used Buchenwald slaves to build the Ferdinand (later Elefant) tank destroyers, saw his family’s empire flourish under US occupation.¹¹⁴

Operation Paperclip (1945–1959) brought more than 1,500 Nazi war criminals to the United States, including SS members who used slave labour and conducted human experiments.¹¹⁵ They received laboratories while scholars documenting Soviet sacrifice were blacklisted.

Not one Nazi industrialist – nor any of their US corporate collaborators – faced justice at Nuremberg for operating concentration camp factories.

Japanese War Crimes: The Architecture of US-Enforced Impunity

Japan’s war criminals received far greater protection. Whereas the Allies prosecuted 199 major German war criminals – 24 at Nuremberg and 177 in subsequent trials – they prosecuted only 25 Japanese war criminals at Tokyo. The disparity reveals deliberate design.

The prosecution patterns expose the design. While 5,700 Japanese war criminals faced Allied tribunals, US official Saltzman ended these in 1949, declaring ‘no further trials’. Though 920 were executed, this was foreign justice imposed by victim nations.¹¹⁶ Germany was forced to investigate 90,000 individuals and established domestic courts, prosecuting tens of thousands.¹¹⁷ Japan investigated zero domestically. Japan prosecuted zero domestically. The US occupation preserved Japan’s war-criminal bureaucracy, making self-prosecution impossible.

The organisational immunity granted to Japan exceeded even this individual protection. At Nuremberg, the Allies declared four organisations criminal: the SS, Gestapo, SD, and Nazi Party Leadership Corps. Membership alone became grounds for prosecution. For Japan, the Allies declared zero organisations criminal. Not the Kempeitai, the military police that tortured POWs. Not the Special Higher Police, which arrested 65,000 for political crimes. Not Unit 731, whose 3,607 members conducted human experiments. This wholesale organisational immunity ensured that systematic crimes could never be prosecuted as systematic.

The Tokyo Trial architecture neutered crimes against humanity as a distinct category. Unlike Nuremberg’s clear distinctions, the 5,700 Japanese ‘Class B and Class C’ prosecutions were merged into a single category, with no separate Class C indictments or verdicts issued, erasing crimes against humanity as an independent charge and avoiding precedents applicable to Western colonial rule.

The financial disparity completed the racial hierarchy: while Germany paid $86.8 billion in Holocaust reparations through 2018, with direct compensation to victims, Japan paid $2.6 billion total through state-to-state deals with mandatory waivers blocking individual compensation. The ‘comfort women’ (ianfu) – 200,000 to 400,000 enslaved – saw zero prosecutions of those responsible. Chinese POWs suffered 99.9% mortality while Western POWs faced 27% mortality under the same captors. The legal architecture did not just reflect racial hierarchy; it codified it.

From War Criminals to Japan’s Ruling Elite

Unit 731 exemplified both the depths of Japanese war crimes and the completeness of US complicity. The unit’s 3,607 members called prisoners maruta (logs) while conducting experiments on them that defied human comprehension.¹¹⁸ They performed vivisections without anaesthesia, infected prisoners with plague and cholera, froze limbs to study frostbite until they sounded like boards when struck, subjected prisoners to pressure chambers until their eyes popped out, used them as living targets for germ bombs and flamethrowers, and cut open pregnant women to observe foetal infection. Prisoners had a maximum life expectancy of one month; technicians fed them dumplings laced with typhoid, injected them with snake venom and prussic acid, replaced their blood with horse blood, then carefully documented their deaths before burning the bodies in oil-fuelled crematoria.

On 6 May 1947, MacArthur radioed Washington: Unit 731 commander Shirō Ishii would provide the ‘complete story’ if granted ‘documentary immunity’. The State-War-Navy Coordinating Committee deemed this data ‘the only known source’ of human experimentation results – research the US could not duplicate due to ‘scruples’. Fort Detrick paid 150,000–200,000 yen for the data – what General Charles Willoughby called ‘a pittance’ – and collected 8,000 pathology slides from over 200 cases of human experimentation. Fort Detrick incorporated this blood data into its biological weapons programme.

The racial calculus was explicit. The US executed two Japanese physicians at Yokohama for vivisecting US pilots – they were not even Unit 731. Yet all 3,607 Unit 731 members who killed 3,000 in experiments and 200,000 through biological weapons – overwhelmingly Chinese – received immunity.¹¹⁹ US lives: prosecution. Asian lives: immunity and payment.

When the Soviets prosecuted twelve captured Unit 731 members at Khabarovsk in 1949 – exposing the human experiments on Chinese, Korean, and Soviet prisoners in sworn testimony – Western governments, including the US, dismissed the trial as Soviet propaganda.

The career trajectories of Unit 731 personnel demonstrate how immunity became advancement. Commander Ishii became a medical consultant to the US Army. His deputies founded Green Cross Pharmaceuticals. Yoshimura Hisato, who conducted frostbite experiments, became president of Kyoto Prefectural University of Medicine and received the Order of the Rising Sun from Emperor Hirohito. These men trained the next generation of Japanese doctors. The Nuremberg Doctors’ Trial executed seven of twenty-three Nazi physicians for identical experiments. Japanese experimenters became medical educators.

The transformation of war criminals into political leadership followed the same pattern. Nobusuke Kishi administered forced labour in North China: four million enslaved, 40% mortality. At the Fushun Coal Mine, 25,000 of 40,000 workers were replaced yearly after being worked to death. MacArthur released him from Sugamo Prison on 24 December 1948 – the day after Prime Minister Hideki Tojo’s execution. The message: some war criminals hang, others rule. The CIA orchestrated Kishi’s rise: by 1957, he was prime minister, having rammed through the US-Japan Security Treaty. Nine years from war criminal to prime minister. His grandson Shinzo Abe served as prime minister for over 3,188 days, Japan’s longest tenure.¹²⁰

The financial architecture of impunity proved equally systematic. Yoshio Kodama plundered $175 million through opium trafficking – the CIA called him ‘a professional liar, gangster, charlatan, and outright thief’ yet kept him on the payroll. His stolen wealth funded the Liberal Democratic Party. Ryoichi Sasakawa, ‘the world’s wealthiest fascist’, transformed wartime loot into Japan’s gambling monopoly, funding right-wing causes globally through his Nippon Foundation.

The zaibatsu corporations – Mitsubishi, Mitsui, Nissan, Sumitomo – exploited 40,000 Chinese prisoners and hundreds of thousands of Koreans. Their executives died as honoured billionaires. Matsutaro Shoriki, a Class A war criminal, founded Nippon Television while shaping public memory for generations.

Enforcing Historical Denial

The architecture of impunity required more than protecting war criminals – it demanded enforcing historical denial. Japan has never issued a full apology to Asian victims. China, with 24 million dead, received no formal unqualified apology. Indonesia lost 3.4 million, Burma 345,000, Malaya 100,000 in Sook Ching (purge) operations, the Philippines 765,000 – all without direct acknowledgement.

The 1995 Murayama Statement was merely personal; the Diet’s resolution avoided admitting guilt.¹²¹ School textbooks minimise these crimes. Nippon Kaigi’s 40,000 members work systematically to overturn ‘the Tokyo Tribunal’s view of history’. A nation that enshrines war criminals and censors their victims cannot claim contrition.

MacArthur’s immunity for Hirohito created the foundation for all denial. The emperor who bore command responsibility for Unit 731 was guaranteed immunity before trials began. This created a legal black hole: if the supreme commander was immune, no organisation could be criminal, no chain of command could be traced. Hirohito died in 1989, never questioned about the millions killed under his command.

The Yasukuni Shrine honours 1,066 war criminals, including 14 Class A criminals. Seven prime ministers have worshipped there since 1978 – Koizumi six times. The Yushukan Museum displays the Thai-Burma Railway locomotive, celebrating Japanese engineering while erasing 90,000 Asian labourers who died building it. At Harbin’s Unit 731 Museum, victims preserve evidence perpetrators deny. Germany criminalises Holocaust denial; Japan’s establishment suppresses war crimes acknowledgement. Historians documenting atrocities face death threats. Comfort women memorials trigger diplomatic protests.

MacArthur architected impunity as policy, ensuring war criminals became Japan’s ruling elite, choosing anti-communist stability over justice for millions of Asian dead.

War criminals became cabinet ministers. Their victims became blank spaces in encyclopaedias.

15. The Memory Hole: Admitting the Real War

On 29 March 2025, US Defence Secretary Hegseth stood at Iwo Jima, celebrating yesterday’s enemy as today’s friend. Japan and America fought as rival empires, not ideological opponents. Their shared enemy was always socialism.

The historical revision accelerates. At the 2023 G7 Hiroshima Summit, the atomic bombing was recast – no longer US mass murder of civilians but a warning about Russian and Chinese nuclear threats. The victims of US nuclear weapons became props in propaganda against nations that have never used them. Japan’s prime minister stood where 140,000 died and pointed at Beijing and Moscow, not Washington.

Within five years of Hiroshima, MacArthur was rearming Japan. Within six years, the San Francisco Treaty excluded China and the Soviet Union – two nations that actually defeated Japanese fascism. Now, Hegseth announces Japan as a warfighting headquarters against Chinese Communist aggression. This timeline reveals the truth: a temporary conflict between imperialist states (1941–1945) and a permanent war against socialism that began in 1917 and continues for more than a century.

The West’s historical erasure operates on multiple levels. The first is a near-total silence in the popular sphere, where the foundational facts of the war – that the Soviet Union destroyed 80% of the Wehrmacht and China tied down the Japanese army at a cost of 27 million and 24 million dead respectively – are simply absent.

Beyond this public silencing, a more subtle academic erasure occurs. Even when a high death toll – perhaps 50 million – is technically acknowledged, it is frequently buried in obscure, supposedly neutral texts and presented as data stripped of perpetrator, responsibility, and the context of a socialist victory. Simultaneously, the most comprehensive research from victim nations is actively minimised through a grotesque demand for bookkeeping from the graveyards, allowing their casualty reports to be dismissed as politically inflated while the perpetrators control the historical ledger. This is how empires lie – by making the dead disappear twice. First, they kill and maim them. Then they deny they ever existed. The gap between Western admissions and reality is not an error, oversight, or methodological difference. It is a deliberate, systematic, and ongoing act of erasure.

The full accounting, therefore, requires restoring this lost context and human cost. The calculation is derived by summing two main groups of silenced victims:

• The full human cost of the WAFW, including both the socialist victors and the colonised victims whose suffering is ignored:
  • Soviet Union: 40–45 million casualties (dead and wounded)
  • China: 35–50 million casualties (dead and wounded)
  • Colonised peoples (Asia and Africa): 11.2 million dead
• The victims of the anti-communist genocides that followed, and whose murders are minimised or forgotten:
  • Koreans killed: 4.5 million
  • Southeast Asians killed (Vietnam, Laos, Cambodia): 3.1–5.1 million
  • Indonesians killed (1965–1966): 1–2 million

The sum of these figures reveals the true scale of what is hidden behind the West’s neutralised data and public silence: a total of 90–115 million human beings rendered invisible. This conservative tally does not even include the victims of terror by US-backed regimes from Chile to Guatemala, nor those murdered during six centuries of uninterrupted imperial barbarism across the African continent. Every uncounted casualty serves empire. Every genocide minimised protects the guilty.

16. The Architecture of Betrayal: Cairo to San Francisco

Post-War Betrayals Were Scripted before the War Ended

The Cairo Declaration (27 November 1943) promised Korea would become ‘free and independent’ – Roosevelt, Churchill, and Chiang signed this while Korean forced labourers died in Japanese mines.¹²² The Atlantic Charter (1941) guaranteed ‘no territorial changes that do not accord with the freely expressed wishes of the peoples concerned’.¹²³ However, Prime Minister Churchill clarified to Parliament less than a month later that this principle applied only to ‘states and nations of Europe now under the Nazi yoke’ and explicitly excluded the subjects of the British Empire.¹²⁴ The Potsdam Declaration (26 July 1945) demanded Japan’s complete demilitarisation and China’s territorial restoration. Roosevelt’s ‘Four Policemen’ concept envisioned the UN under the control of four great powers: the US, Britain, the USSR, and China. Every promise would be systematically broken.

The reversal began immediately. In August 1945, Dean Rusk – a mere colonel – drew the 38th parallel line dividing Korea, the nation promised independence.¹²⁵ By 1950, the US was incinerating the Korea it had pledged to free. The Atlantic Charter’s territorial integrity? The US would eventually establish 902 foreign military bases across 98 countries and territories.¹²⁶

After the WAFW, the US military occupied Okinawa – the Ryukyu Kingdom that Japan had forcibly annexed in 1879. The Potsdam Declaration limited Japanese sovereignty to its main islands and ‘such minor islands as we determine’ but made no provision for Ryukyuan self-determination. The US simply replaced Japan as the occupying power, maintaining control until 1972 when it transferred administrative authority back to Japan – again without consulting the Okinawan people. US bases remained, occupying 18% of the island today, where 70% of all US forces in Japan are concentrated.¹²⁷ Japan’s demilitarisation? MacArthur created the Police Reserve (later known as the Self-Defence Forces) in 1950, just five years after the bombing of Hiroshima.

The San Francisco Exclusion

The Treaty of San Francisco (8 September 1951) crystallised the betrayal through calculated exclusion. Neither Beijing nor Taipei was invited, despite China having borne 35–50 million casualties defeating Japan. The USSR attended but refused to sign.¹²⁸ Soviet delegate Andrei Gromyko protested that the treaty would turn Japan into ‘an American military base’ while excluding China, ‘one of the main victims’.¹²⁹ When he attempted to secure a discussion, US-orchestrated parliamentary manoeuvres ruled him ‘out of order’. The question of China’s participation was simply dismissed. US Secretary of State John Foster Dulles received ‘paeans of praise’ from twenty delegations for engineering this exclusion – the same Dulles who would later threaten ‘massive retaliation’ and push the world to nuclear brinkmanship. The US negotiated peace with Japan by excluding the two nations that sacrificed the most in defeating it. This was not oversight – it set the security architecture of post-war East Asia.

The United Nations (UN), designed for collective security through great power cooperation, was immediately circumvented. The US exploited the Soviet absence during the Security Council vote on Korea then created alternatives to bypass Soviet vetoes. The North Atlantic Treaty Organisation (NATO), established in 1949, and other parallel structures operated outside UN authority. By calling Korea a ‘police action’, the US established precedent for endless interventions without Security Council approval. The same semantic manipulation is used today in Syria, Libya, and Yemen.

Three wars. One pattern.

The final accounting shatters imperial mythology: those with overwhelming wealth inflicted maximum violence on those who had the least – and still lost. Socialist forces with minimal wealth mobilised maximum humanity – and won.

Today’s ‘new Cold War’ against China and Russia (independent, not socialist) follows the same script. The faces change, the imperialism remains. When Western media demonise China while ignoring its lifting of 800 million from poverty, when it portrays Russia as aggressive while NATO expands to its borders, we see the same propaganda machinery that erased the truth about who defeated fascism.

17. Conclusion: The World Anti-Fascist War within the Century-Long Struggle

The WAFW was not humanity’s ‘good war’ against evil, after which peace prevailed. It involved one chapter in imperialism’s century-long assault on socialism that began with the 1917 Russian Revolution and continues today.

The liberal fiction of three competing systems – democracy, fascism, and communism – obscures the truth: fascism is capitalism in crisis, its mask dropped. The real struggle was never between three systems but between two: socialism and capitalism, with fascism as capitalism’s emergency response to revolutionary threat.

The colonial metropoles supported fascism’s rise – from Churchill praising Mussolini to US corporations building Hitler’s war machine – because fascism was the solution to defeat any emergence of socialism in the weakest links of the imperialist chain and to destroy the Soviet experiment. Only when fascism threatened the interests of Western imperialist powers did they reluctantly join the socialist powers they had hoped to see destroyed.

The numbers expose the truth with brutal clarity.

The Soviet Union and China – controlling less than one-sixth of global economic output – destroyed over 80% of fascist military power while suffering 59.8% of all WAFW deaths. They won the war. Roosevelt and Churchill positioned themselves to win the peace. This was not a coincidence, strategy, or clever timing. This was betrayal – planned from the beginning, executed with precision, covered with propaganda that continues to this day – as the West celebrates D-Day while minimising Moscow and Stalingrad, honours Churchill while hiding his Bengal genocide, and claims victory while those who actually won lie in unmarked graves by the millions.

But this war never strategically ended. It simply changed form. In 1931, Japan invaded China. In 1941, Germany invaded the USSR. In 1950, the US invaded Korea. In 1955, the US took over France’s war in Vietnam. No pause between ‘defeating fascism’ and attacking socialism – because defeating socialism was always the decisive goal.

The same arithmetic of sacrifice continued. Korea: 4.5 million deaths, while the US lost 54,246. Vietnam: 3.1 million deaths by Vietnamese documentation, while the US lost 58,000. Indonesia: 1–2 million murdered in 1965–1966 through death lists provided by the governments of Australia and the United States.¹³⁰ For Africa there have been six centuries of uninterrupted imperial barbarism, starting with the slave trade and colonial genocide. This year also marks seventy years since the 1955 Bandung Conference, when twenty-nine African and Asian nations declared their refusal to be pawns in the Cold War while demanding genuine independence from both colonial rule and emerging neocolonial domination.

Today, anti-communist and colonial genocide has stretched from Korea’s mountains and Indonesia’s islands to Congo’s mines, Chile’s copper fields, and Gaza – the target never changes. Each nation pays in blood for the crime of seeking real independence. The weapons improve; the genocide remains constant. Any nation attempting truly independent development faces the choice: submit to capital or face imperialist assault.

As the US-led military bloc now accounts for over 75% of the world’s total military spending, as NATO expands despite promises, and as sanctions strangle any nation asserting sovereignty – from Cuba to the Sahel – imperialism promotes the same war by other means.¹³¹ The ‘rules-based international order’ means the same thing as the ‘civilising mission’: submit or be destroyed.

When Western leaders invoke the World Anti-Fascist War to justify aggression, remember who actually fought and died. They claim to defend democracy, yet they allied with fascism until forced to fight. They promise to protect human rights while they let millions burn, preserving their strength.

The Soviet and Chinese peoples saved humanity not through wealth but through sacrifice; not through superior resources but through superior strategy; not through the preservation of capital but through the mobilisation of the masses.

Socialist peoples and leadership can defeat imperialism in any form – fascist then, hyper-imperialist now – despite every material disadvantage. That victory required genius, courage, and unimaginable sacrifice. It also proved something imperialism cannot accept: ordinary people, organised and led with brilliance, can defeat any empire. Mao crystallised this truth in On Protracted War (1938): ‘The richest source of power to wage war lies in the masses of the people’. Not in GDP percentages or military budgets, not in colonial extraction or industrial capacity, but in the mobilised masses who refuse to kneel. The arithmetic proved him right: those with 8% of world GDP defeated those with 30–32%. The formula remains unchanged – when the people are organised, no empire can stand.

We live in times of change not seen in a hundred years. It has been a century since the first socialist state established the precedent that a world beyond capital was achievable. Today, for the first time since 1900, the eight richest imperialist countries have fallen from 57.3% of world GDP to 29.9% – their economic stranglehold weakening as the Global South rises. We draw inspiration from all our martyrs. We will not allow their sacrifice to be in vain. History is on our side.

That is why they lie about who won the war.

That is why we must tell the truth.

Appendix: Data, Sources, and Methodology

This appendix provides a comprehensive overview of the data sources, calculations, and methodological principles underpinning this study. It is intended to offer transparency and a centralised resource for readers seeking to understand the foundational evidence for the article’s central arguments. The appendix is divided into three sections:

• Data Tables and Sources for Figures: the summary tables as they appear in the article
• Methodological Notes: explanations of how data were calculated and interpreted, including key comparative data tables
• Verbatim Data Source Excerpts: key data tables reproduced directly from primary sources for full transparency

Section 1: Data Tables and Sources for Figures

Section 2: Methodological Notes

GDP and Population Data Methodology

All GDP and population data in this article follow a systematic source hierarchy to ensure consistency and maximise data coverage.

GDP Data

All GDP values are expressed in 1990 International Geary-Khamis dollars for cross-country comparability. Primary GDP figures are sourced from Harrison (1998). Where Harrison does not provide coverage, data are supplemented from Maddison (2010). Alternative sources are used only when both primary sources lack the required data.

The 1941 world GDP total is estimated using the following methodology: beginning with Maddison’s 1940 world total ($4,547 billion), we calculated the weighted average growth rate (4.6%) for countries with continuous 1940–1941 coverage (representing 73.7% of 1940 world GDP) and applied this rate to derive the 1941 global estimate based on 1940 world GDP data. Calculation: $4,547 billion × 1.046 = $4,759 billion.¹³²

For China, only the 1938 GDP figure is available; its 1941 GDP and share of world GDP are estimates.¹³³

Population Data

Population figures primarily derive from the Maddison 2010 database, which provides the most comprehensive coverage for the countries and time periods examined. While Harrison (1998) utilised an earlier version of Maddison’s dataset (now unavailable), this article uses the 2010 revision for consistency. Where Maddison lacks coverage, alternative sources or interpolation methods are employed. Specifically, USSR population data for 1941 and 1946 are sourced from Statista (2025), with values for 1942–1945 derived through linear interpolation.¹³⁴

We acknowledge that linear interpolation during wartime represents a simplified assumption that does not capture actual demographic disruptions; these figures should be considered rough estimates only.

Note

All interpolated or derived values represent methodological compromises necessitated by gaps in the historical record. Where territorial boundaries changed during the period under study, we use the boundaries as defined by the primary source for each respective year.

Note on Casualty Calculations for the World Anti-Fascist War

This study documents deaths only. Our total of 85.3 million deaths falls at the high end of Western ranges, primarily due to our acceptance of comprehensive national research projects from the nations that suffered most.

• USSR: The figure of 27 million Soviet deaths is from Andreev et al. (1993).¹³⁵
• China (1931–1945): We assert that the WAFW began with Japan’s invasion of Northeast China in 1931. Our total of 24.05 million Chinese deaths is a comprehensive figure derived from multiple components, based primarily on the research of Bian (2012). The calculation is as follows:
  • Direct deaths (1937–1945): about 20.6 million
  • Indirect deaths (1937–1945): about 3 million (primarily from war-induced famine and displacement)
  • Estimated deaths (1931–1937): about 450,000 (an educated estimate, as official figures for this period are unavailable, based on numerous documented incidents during the initial invasion and occupation of Northeast China)
  • Total calculated deaths: about 24.05 million¹³⁶
• India: The calculation of Indian deaths during the WAFW centres on two primary components: military casualties (87,000) and the Bengal Famine of 1943 (3 million) (Sen, 1977). While Indian deaths totalled 3.087 million, we use the consolidated figure of 3 million for analysis.¹³⁷ This rounding does not materially affect any of our calculations – India’s deaths remain 3.5% of global deaths and the Lend-Lease aid per death remains $1,189. Using the round figure of 3 million maintains consistency with our conservative methodological approach while acknowledging that famine deaths, not military casualties, constitute the overwhelming majority of Indian losses.

African Deaths in the World Anti-Fascist War

The assessment of African casualties during the WAFW presents unique challenges due to incomplete colonial record-keeping and historical marginalisation of African losses. This section establishes a conservative baseline of 1.6 million deaths, with a reasonable range of 1.6–2.0 million when accounting for undocumented losses.

Primary Source Documentation

The Ethiopian government’s 1945 memorandum to Allied powers recorded 760,300 deaths during the Italian invasion and occupation (1935–1941), comprising:¹⁴¹

1. 275,000 battlefield deaths
2. 300,000 deaths from war-induced famine and forced displacement
3. 185,300 deaths from massacres, executions, concentration camps, and chemical warfare

This documentation, reported in Del Boca (1969), p. 275, represents the most rigorous national accounting from the African theatre.

The Oxford Research Encyclopedia of African History provides consolidated estimates for the remainder of the continent:¹⁴²

• 475,000 African military personnel deaths (including colonial troops in European and Asian theatres)
• 500,000 civilian deaths from war-related causes (excluding Ethiopia)

These figures synthesise recent scholarship on North African campaigns, colonial troop deployments, and civilian casualties.

Methodological Notes

Consistent with our definition of the WAFW (1931–1945), we include the Italo-Ethiopian War beginning in 1935 as part of global anti-fascist resistance. The documented baseline of 1.74 million deaths derives from primary sources (Ethiopian government) and peer-reviewed academic syntheses (760,300 Ethiopian + 975,000 other African).

Colonial records systematically undercounted African deaths, particularly forced-labour mortality, localised famines, reprisal killings, and scorched earth campaigns. Based on analogous gaps in Asian theatre documentation, a 10–15% adjustment factor could account for these exclusions, yielding an upper bound of 2 million deaths.

Conservative Approach: Using 1.6 million

We deliberately adopt the most conservative figure of 1.6 million African deaths – the absolute lower bound – for several reasons:

• Documentary rigour: This figure requires minimal extrapolation from documented sources and accounts for potential overlap between categories, making it highly defensible on evidentiary grounds.
• Strategic understatement: Using the lowest defensible estimate ensures our broader argument about sacrifice distribution cannot be dismissed as inflated. If anything, we understate African losses.
• Comparative context: Even at 1.6 million deaths – our most conservative estimate – African losses exceeded the combined military deaths of the United States and United Kingdom (847,000 total), demonstrating the profound disparity between who paid the price and who claimed victory.

The actual death toll was almost certainly higher, likely approaching 2 million when accounting for systematic colonial undercounting. However, our methodological conservatism strengthens our central argument: even using minimum estimates, the erasure of African sacrifice from WAFW narratives represents a grave historical injustice.

Death Calculations: Korean and Vietnam Wars

• North Korea (1950–1953): 5–2.5 million deaths. The upper bound derives from Halliday and Cummings (1988): ‘Over 2 million North Korean civilians died and about 500,000 North Korean soldiers’.¹⁴³ This aligns with US Air Force General Curtis LeMay’s admission of killing ‘twenty percent of the population’.
• South Korea (1950–1953): 5–2 million deaths. Shin (2001) notes: ‘Underreporting of war deaths and inadequate death-registration systems following the war render this estimate less than half of reported war-related losses, which are likely to have been between 1.5 and 2 million’.
• Total Korean Peninsula (1950–1953): 3–4.5 million deaths, representing 10–15% of the pre-war population.
• Vietnam (1955–1975): Current Vietnamese government figures document 3.1 million deaths, with some earlier demographic studies reaching as high as 5.1 million.¹⁴⁴

Note: Vietnamese and US deaths calculated as percentage of their respective 1965 populations (midpoint of 1955–1975 war period) to account for demographic changes over the twenty-year conflict. Using a single reference year provides consistent baseline for comparison while acknowledging populations fluctuated throughout the war.

Lend-Lease Aid Calculation

The Department of State (1945) reports total Lend-Lease aid to the British Empire as $30.26921 billion (p. 14, table 2) but does not provide breakdowns for individual Commonwealth nations. To estimate aid distribution among the United Kingdom, British India, Australia, and New Zealand, we developed the following methodology:

Step 1: Calculate Export Proportions Using Table 25 (pp. 42–43)

We calculated each destination’s share of total British Empire Lend-Lease exports, which is $17,954,911. Therefore, for the United Kingdom, the share is: $13,842,043 ÷ $17,954,911= 77.1%.

Step 2: Apply Proportions to Total Aid

We then applied these percentages to the total British Empire aid and rounded them to thousand dollars.¹⁴⁶ Therefore, for the United Kingdom, the estimated aid is: $30,269,210,000 × 77.1% = $23,335,549,000.

Note: Ceylon (Sri Lanka) is included with India in both the source data and our calculations, as the two were administratively linked in US Lend-Lease accounting.

Methodological Limitations:

1. This method assumes aid distribution matched export distribution, which may not reflect actual patterns.
2. Some aid may have been distributed through channels not captured in export data.
3. Military equipment transfers may have followed different allocation patterns than general supplies.

Definitional Note of British Empire

This study employs two distinct definitions of ‘British Empire’ corresponding to their historical usage by the respective governments:

British Definition (Used for Population Data)

For the 1941 population calculations in figure 1 we use the British government’s official definition of the British Empire, which included:

1. Dominions: Canada, Australia, New Zealand, South Africa, and Newfoundland (separate from Canada until 1949)
2. The Indian empire: India (including present-day India, Pakistan, and Bangladesh), Burma, and Ceylon
3. Colonial empire: colonies, protectorates, and mandated territories across Africa, Asia, the Middle East, the Americas, Pacific, and Mediterranean regions

This comprehensive definition encompasses all territories under British sovereignty or protection, regardless of their degree of self-governance.

United States Definition (Used for Lend-Lease Aid)

For Lend-Lease aid distribution calculations in figure 3, we necessarily adopt the US Department of State’s administrative classification from 1945. The US definition treated the British Empire as follows:

This definition affected how aid was allocated and reported in official US documentation.

The distinction is critical: while the British definition was used for understanding the Empire’s total population and resources, the US definition determined the actual flow and accounting of wartime aid. Our calculations for per capita aid and per death valuations in figure 3 reflect these US administrative categories, not British imperial self-conception.

Calculation of the Eight Richest Imperialist Countries (1900 and 2024)

The comparison stating that ‘the eight richest imperialist countries have fallen from 57.3% of world GDP to 29.9%’ required specific methodological decisions for both historical consistency and political categorisation.

2024 Calculation

The eight richest imperialist countries are identified through GDP ranking among nations classified as imperialist powers. The eight countries are: the US, Japan, Germany, France, United Kingdom, Italy, Spain, and Canada. Note that the GDP for these eight countries and world total are in Purchasing Power Parity (PPP) sourced from World Bank World Development Indicators, last updated July 2025.

1900 Calculation

The eight powers in 1900 – the US, United Kingdom, German Empire, French Empire, Russian Empire, Austria-Hungary, Italy, and Japan – were all engaged in imperial expansion or colonial administration. Using Maddison (2010) as our primary source, we confronted two specific issues:

1. Austria-Hungary: The Maddison 2010 database does not provide unified data for Austria-Hungary, as the empire had dissolved by the database’s construction. To reconstruct the 1900 Habsburg Empire’s economic weight, we summed the GDP figures for:
   1. Austria
   2. Hungary
   3. Czechoslovakia (as the Czech lands were part of Austria-Hungary in 1900)

This aggregation provides the closest approximation to the actual Austria-Hungarian Empire’s economic output.

2. Poland: Maddison (2010) provides Poland’s GDP for 1900, despite Poland not existing as an independent state (having been partitioned between Russia, Germany, and Austria-Hungary since 1795). To accurately reflect the 1900 distribution among the partitioning powers, we allocated Poland’s reported GDP as follows:
   1. 60% to the Russian Empire (reflecting Russia’s control of Congress Poland, the largest partition)
   2. 30% to the German Empire (reflecting Prussia’s control of Greater Poland and Pomerania)
   3. 10% to Austria-Hungary (reflecting Austrian control of Galicia)

These percentages approximate the territorial and population distribution of the Polish partitions.

Note on Political Categorisation

The exclusion of Russia from the 2024 list and its inclusion in the 1900 list reflects changed historical circumstances and our analysis of contemporary global power structures. This methodological decision ensures consistency in tracking the economic weight of imperialist powers across time.

The resulting calculation shows these eight imperialist powers controlled approximately 57.3% of world GDP in 1900, compared to the current eight richest imperialist countries’ 29.9% share in 2024.

Section 3: Verbatim Data Source Excerpts

This section reproduces key data tables from foundational sources to provide maximum transparency for the statistical claims made in this article.

Data Used to Generate Figure 1. Economic capacity and population (1941)

Data Used to Generate Figure 2. Late to the fight: troops as a percentage of population (1939–1945)

Data Used to Generate Figure 3. Western calculations on the relative value of a life: Lend-Lease distribution (1941–1945)

Data Used to Generate Figure 4. The economics of delay: military spending commitments

Reader’s Guide to the Four-Layer Endnotes

Part I: How to Read the Four-Layer Endnotes

The Four-Layer Structure of Each Endnote

Each endnote contains multiple layers of information, though only three are visible to readers.

What Each Layer Means

• Layer 1: Context – interpretive framing that explains why this evidence is important
• Layer 2: Verifiable claim – specific facts that can be independently verified
• Layer 3: Sources – where to verify the facts with exact page numbers
• Layer 4: Evidence – research methodology that exists in the database but is not published

Note on claim numbering: Claims are numbered X001, N002, and so on, but the numbering is not consecutive (e.g., 1, 9, 47). This reflects an iterative multi-team research approach in which some claims were merged, moved, or deprecated during the writing process. The gaps are normal.

Example Endnote:

Following the Data Trail: A Simple Example

Main text states: ‘China suffered 24.05 million deaths’

Endnote provides: Basic sources and context

Appendix explains:

• How the 24.05 million was calculated
• Why it differs from Western estimates
• Which sources were used and why

The following section provides methodological context for academic readers.

Part II: Methodology and Principles

Understanding the Research Methodology

This document uses a forensic historiography approach – investigating gaps and erasures in historical records rather than simply accepting established narratives. The endnotes reflect this methodology through a system that separates interpretation from facts and prioritises evidence from the nations that suffered the losses.

Key Methodological Innovations

1. Investigating Erasure, Not Just Recording Events

The research identifies two types of erasure:

• Undercounted deaths – millions missing from mainstream accounts
• Ignored evidence – facts that exist in archives but rarely appear in mainstream histories

2. Temporal Reframing

By starting the World Anti-Fascist War (WAFW) in 1931 (Japan’s invasion of China) rather than 1939, the methodology reveals eight years of resistance erased by Western periodisation.

3. Transparency Through Layers

Unlike traditional footnotes that mix everything together, this endnotes system:

• Separates interpretation from facts
• Documents methodology (even if not published)
• Enables verification at multiple levels
• Shows when sources conflict and explains choices

Critical Reading Questions

As you read, consider:

1. Whose voices are centred? Notice when documentation from victim nations takes precedence over that of external observers.
2. What is being recovered? Many of the facts presented existed in archives but were omitted from mainstream narratives.
3. Why do numbers differ? When you see conflicting estimates, the appendix explains which was chosen and why.
4. What remains unknown? The methodology acknowledges when records were destroyed (as in Burma) and evidence cannot be recovered.

Source Prioritisation and Why It Matters

The Source Hierarchy: A Holistic Approach

This research systematically considered various sources:

1. Primary sources from victim nations – Chinese government surveys, Soviet archives, Vietnamese records
2. Scholarship from affected countries – historians with access to local archives and languages
3. International investigations – UN reports, war crimes tribunals
4. Western sources citing primary evidence – academic works properly documenting original sources
5. Western sources for comparison – to establish what mainstream narratives claim

Why This Prioritisation?

Victim nations had better direct access to the information needed to document their own losses. The figure of 24.05 million Chinese deaths comes from historian Bian Xiuyue of the Chinese Academy of Social Sciences, whose 2012 book documents approximately 23.6 million deaths from 1937 to 1945, plus the author’s estimate of 450,000 deaths from 1931 to 1937. Separately, the Chinese government’s decade-long survey documented 35 million total casualties (including both dead and wounded). When comprehensive victim-nation research shows 24.05 million deaths while Western estimates show only 14–20 million, the discrepancy reveals systematic undercounting in mainstream historiography. The methodology prioritises rigorous scholarship and surveys from affected nations over external estimates.

Strategic Use of Perpetrator Admissions

When perpetrators admit damaging facts, these serve as conservative baselines. For example, when British Colonial Office records admit a 10% mortality rate in Nigerian tin mines, the actual rate was likely higher. Even the minimum admissions reveal severe exploitation.

Understanding Conservative Estimates

Throughout this work, the methodology generally uses conservative estimates from victim nations’ own documentation, though the approach varies based on available evidence and attribution challenges. This means:

• The actual human cost was likely higher than stated.
• Even these minimum figures reveal systematic erasure.
• Conservative numbers typically strengthen arguments, but the selection process reflects evidentiary complexities.
• When ranges exist, the methodology varies by case: for Africa, using 1.6 million (from a 1.6–2.0 million range) reflects the challenge of determining which deaths are primarily attributable to the war versus other causes – a question that remains understudied despite almost equal likelihood of higher numbers; for Indochina, using 1.5 million reflects documented undercounting; for the Philippines, using 765,000 (a midpoint) balances sources suggesting even higher figures.

The Substantive Innovation: Connecting Buried Evidence

Beyond the methodological innovations, this research assembles scattered and minimised evidence into a coherent pattern that reveals the West’s strategies.

Corporate Complicity

• IBM’s Thomas Watson befriended US President Franklin D. Roosevelt while receiving Hitler’s medals and automating the Holocaust with punch card systems.
• General Motors claimed tax write-offs for Wehrmacht truck factories while producing vehicles that invaded the Soviet Union.
• Two hundred and fifty US corporations operated in Nazi Germany as late as 1941.

Protection of War Criminals

• Churchill’s secret memos ordered protection of Italy’s highest-ranking war criminals, including Badoglio.
• General Douglas MacArthur freed all 3,607 Unit 731 members who tortured prisoners to death, paying them for their data.
• Nobusuke Kishi went from war criminal to prime minister in nine years with CIA orchestration.

Strategic Calculations

• The atomic bombings targeted Soviet and Chinese influence more than Japan – which was already defeated.
• The Second Front was systematically delayed by 730 days while the Soviet Union bled.
• Lend-Lease aid reveals a racial calculus: whites received $442 per person; non-whites received $4.40 per person – a 101:1 ratio.

The Death Rate Arithmetic

• Socialist forces: 59.8% of all WAFW deaths
• Colonised peoples: 13.1% of deaths
• Anglo-Americans: 1% of deaths
• This pattern continued through Korea (92% Korean/Chinese deaths) and Vietnam (98% Southeast Asian deaths)

These documented facts, usually scattered across specialised archives and minimised in mainstream histories, are brought together here with full citations. The endnotes don’t just provide sources – they reveal a systematic pattern of complicity that mainstream narratives work to obscure.

Understanding the Appendix Structure

The appendix provides complete transparency through three sections:

Section 1: Data Tables and Sources for Figures

Clean presentation of the data as it appears in the main text, with source attribution.

Section 2: Methodological Notes

Detailed explanations of:

• How calculations were performed
• Why certain sources were chosen over others
• How conflicting estimates were resolved
• What assumptions were made and why
• Conservative estimation principles

Section 3: Verbatim Data Source Excerpts

Original tables reproduced exactly as they appear in primary sources, allowing readers to verify all calculations themselves.

Part III: Research Infrastructure and Technical Infrastructure: Industrial-Strength Citation Management

For researchers interested in replicating the methodology or understanding the full scope of findings.

Abstract

This section documents a novel research infrastructure combining Zotero with supplemental software and development practices to manage more than 200 claims and more than 400 citations across a globally distributed research team. The system enforces the same four-layer separation of concerns defined in Part I (here presented from a workflow perspective: interpretation, facts, sources, methodology) while maintaining complete verification trails.

System Architecture

Core Components

1. Zotero as Data Layer

• Case items – store claims with four-layer structured notes
• Book Section items only – every citation requires specific page numbers
• Map items – shared research reports and methodology documentation
• Flat repository structure – sequential numbering (80WAFW-001 through 80WAFW-999)

2. Four-Layer Separation

• Layer 1: Context (interpretive) → published
• Layer 2: Verifiable claim (factual) → published
• Layer 3: Sources (citations) → published
• Layer 4: Evidence (methodology and verification) → archived

3. Verification Infrastructure

• Software-assisted initial verification (pattern detection at scale)
• Mandatory paired human review (catches systematic biases)
• Colour-coded tracking (green, orange, yellow, red flags)
• Consensus requirement before approval
• Full audit trail in Layer 3

Key Technical Innovations

Book-Sections-Only Architecture for Books

Every book citation is a complete Book Section with full metadata. Benefits:

• Self-contained records (no dependency failures)
• Bibliography creation software code automatically de-duplicates
• Simpler export/import pipelines
• Each citation links to multiple claims via the Extra field

Structured Note Templates

Every case item requires a note with an exact structure:

• Claim ID: X001
• Claim name: [descriptive]
• Claim context: [Layer 1 – interpretive]
• Verifiable claim: [Layer 2 – factual]
• Claim sources: [Layer 3 – citations]
• Claim evidence: [Layer 4 – methodology]
• Verification note: [paired review documentation]
• Additional information: [optional]

Software Pipeline

Export Infrastructure

• Zotero → CSV (v63 script): Extracts four-layer structure, generates Chicago-style notes formatting
• CSV → Word (VBA v64): UTF-8 handling, DOCX fallback, publication-ready endnotes

Version Control Strategy

• Dedicated backup machine with snapshots
• Collection-level RDF exports
• Deprecation collections (never delete)
• External metadata tracking in spreadsheets, json and markdown files.

Review Process

• Software-assisted systems enable four rounds of review of claims and citations to address the many conflicting facts and interpretations. Each round included extensive review by researchers.

Implementation Requirements

Technical Stack

• Zotero 6+ with Better BibTeX
• Node.js for export scripts
• Excel or LibreOffice for CSV manipulation
• Word with VBA support
• Cloud storage for PDF repository

Conclusion

This methodology demonstrates how historical research can benefit from software development best practices while maintaining scholarly rigour. The four-layer architecture enables teams to challenge established narratives through systematic, transparent, and reproducible research.

Key Takeaways for Researchers:

• Separation of concerns (interpretation, facts, sources, methodology) improves clarity
• Structured data enables verification at scale
• Multiple stages of review catch systematic biases
• Comprehensive source evaluation strengthens claims
• Complete audit trails defend controversial findings

The infrastructure investment pays dividends when defending research that challenges dominant historiography.

Endnotes

Bibliography