Replication Data for: Comparative Cybersecurity in the Americas
Bibliographic record
Abstract
What factors explain the level of commitment to Cybersecurity in the Americas? This research seeks to answer this question through a configurational-qualitative analysis of the performance of 35 American countries in the Global Cybersecurity Index. As explanatory conditions, a) Securitization; b) Military Expenditure; c) Rare events; d) Time of the Legal-Institutional Framework; e) Militarization of Cyberspace; and f) Economic Development are tested. Methodologically, this mixed-method work couples Qualitative Comparative Analysis with an in-depth study of the Brazilian case, based on quantitative and qualitative indicators and on interviews. Results identified three causal pathways towards a greater commitment with Cybersecurity: 1) Military Expenditure associated with Economic Development (United States, Canada, Chile, and Uruguay); 2) Military Expenditure and Time of the legal-institutional framework (Cuba); 3) Militarization of Cyberspace and Economic Development (Brazil and Colombia). The case study of Brazil identified the institutional bargains between military and civil sectors as a key causal mechanism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.158 | 0.052 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".