Bibliographic record
Abstract
BACKGROUNDSuicide is a significant and preventable public health issue in Massachusetts and across the nation.The impact of suicide is enormous: it is conservatively estimated that for every suicide completion, there are six loved ones who are left behind to experience the complicated grief that comes from losing someone to suicide. 1 For youth suicide, the impact of the death on parents, friends, and the community is heightened.Youth suicides are defined as suicides occurring between the ages of 10-19; this age group gives up the largest number of healthy years of life and therefore represents an important risk group for suicide prevention.The information for this bulletin was gathered from the Massachusetts Violent Death Reporting System (MAVDRS).MAVDRS is a state-based surveillance system that compiles information on violent deaths in order to provide a detailed picture of how and why they occur.MAVDRS utilizes multiple data sources including death certificates, medical examiner files, toxicology reports, and law enforcement records in creating its data records.MAVDRS includes all suicides that occur within Massachusetts, regardless of whether or not those individuals were Massachusetts residents.2MAVDRS Massachusetts Violent Death Reporting System Massachusetts Department of Public Health Key Findings from 2004-2008 • On average, 21 youth suicides occurred each year from 2004-2008.• The highest youth suicide rate overall was among White, non-Hispanic youths (N=92, 2.8/100,000).• The youth suicide rate for males (3.4/100,000) was more than twice the rate for females (1.4/100,000).• The most common weapon was hanging, accounting for 68% of the youth suicides (N=73).3
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".