Research and Development of Dual-Use Technologies in Latin America and the Caribbean as a Regional Evolution and Integration Tool
Bibliographic record
Abstract
Amid the 21st-century imperative of innovation, particularly evident within the defense sector, this paper delves into the challenges and prospects for Latin American and Caribbean (LAC) countries in enhancing their capabilities in dual-use technologies and collaborative alliances. The study emphasizes the heightened intensity of this phenomenon in defense, where military and dual-use technologies intersect with geopolitical dynamics in a global context marked by resurgent power rivalries. LAC nations, varying in developmental stages and constrained by economic shifts, face an urgent need to prioritize research and development (R&D) for dual-use technologies, warranting a serious consideration of innovation. The research delineates three country categories within LAC: those capable of autonomous dual-use technology production, those progressing towards that goal, and a third group contributing to the supply chain. Finally, this paper offers a timely exploration of LAC’s strategic opportunities, from innovation to collaboration, with the potential to shape the region’s defense landscape and broader global positioning.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".