Bibliographic record
Abstract
OBJECTIVE: We evaluated 21 contact-based education interventions in 5047 Canadian high school students and identified student characteristics associated with success. METHODS: We used a one-group pretest/posttest design with standardized instruments to measure changes in behavioural intent. Variability across interventions was assessed using meta-analysis, and a mixed-effects logistic regression was used to identify student characteristics. RESULTS: Interventions were heterogeneous (I(2) = 62.4%) but generally successful. The odds of getting an A grade was 2.57 times greater on the posttest than the pretest (95% CI = 2.18, 3.03). Males were less likely to achieve a passing score overall; however, males who self-disclosed a mental illness were more likely to pass. Three percent of students experienced a large drop in social acceptance following the intervention. These were more likely to be male [OR = 1.5 (95% CI = 1.0, 2.1)]. CONCLUSION: Contact-based education is a promising practice for reducing stigma in high school students, although the field would benefit from fidelity criteria to reduce variation across interventions. Males and females react differently to antistigma programming; particularly those with self-reported mental illnesses and a small proportion may become more intolerant.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".