Suicide Prevention in the Americas
Bibliographic record
Abstract
The Americas encompass the entirety of the continents of North America and South America, representing 49 countries. Together, they make up most of Earth's western hemisphere. The population is over 1 billion (2006 figure), with over 65 % living in one of the three most populated countries (the United States, Brazil, and Mexico). The Americas have low-, middle-, and high-income countries. Data from this region have not been readily and consistently available. There are several English-speaking Caribbean nations and countries in South America that have not had updated information. This chapter will focus on suicide prevention within North America (United States and Canada), some countries in the Caribbean region, and some countries in South America. Guyana, Suriname, and Trinidad and Tobago have severe issues with pesticide suicide, with average rates of 44.2 (global rank 1); 27.8 (global rank 5) and 13.0 (global rank 41) per 100,000 respectively. Jamaica, however, had one of the lowest rates: 1.2 per 100,000 (global rank 166). General, regional, and country-specific prevention proposals are suggested, highlighting intersectoral, private collaboration, attention to at-risk persons, substance abuse and mental health interventions, training, and reducing access to lethal means.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".