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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.027 |
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 teacher head, 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".