Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract American countries and cities are among the world’s most prone to gun-related violence. In 2017, the regional homicide rate hovered at 17.2 per 100,000 people, as compared to a global average of closer to 6.1 per 100,000. Rates in Central and South America are over 24 per 100,000 population. Just four countries—Brazil, Colombia, Mexico, and Venezuela—accounted for a quarter of all global gun-related deaths. Firearms on their own are not the cause of homicide or violent crime, but their abundance dramatically increases the risk of a lethal outcome. The sheer diversity and scale of arms and ammunition moving into Latin America constitutes a serious policy challenge. This chapter focuses on the normative dimensions of arms control and emphasizes the salient policy angles, including the necessity of additional border and custom controls, oversight of local arms production, and better controls and management of military, police, and private security arsenals. To responsibly control the problem, Latin America needs better enforcement of existing laws.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it