Contested Conclusions: Claims That Can (and Cannot) Be Made from the Current Research on Gay, Lesbian, and Bisexual Teen Suicide Attempts
Bibliographic record
Abstract
As the press and communities interpret research reports, their conclusions may go far beyond a study's evidence, especially if groups are trying to support politically-motivated claims about controversial causes and solutions to health problems. Few research designs can "prove" cause and effect, especially in population health research. However, some designs are better than others at identifying influences on health. Several strategies can help non-researchers evaluate studies critically. Using these statistics, this paper explores claims that can (and cannot) be made about causes of suicide attempts among gay, lesbian, and bisexual adolescents, based on current research evidence available.
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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 | 0.247 | 0.580 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.008 | 0.071 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.012 | 0.013 |
| Research integrity | 0.019 | 0.022 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".