Estimating costs and benefits associated with evidence-based prevention: Four case studies based on the Fourth R program
Bibliographic record
Abstract
Teen violence in dating and peer relationships has huge costs to society in numerous areas including health care, social services, the workforce and the justice system. Physical, psychological, and sexual abuse have long-lasting ramifications for the perpetrators as well as the victims, and for the families involved on both sides of that equation. An effective violence prevention program that is part of a school’s curriculum is beneficial not only for teaching teenagers what is appropriate behaviour in a relationship, but also for helping them break the cycle of violence which may have begun at home with their own maltreatment as children. The Fourth R program is an efficacious violence prevention program that was developed in Ontario and has been implemented in schools throughout Canada and the U.S. Covering relationship dynamics common to dating violence as well as substance abuse, peer violence and unsafe sex, the program can be adapted to different cultures and to same-sex relationships. The program, which gets its name from the traditional 3Rs — reading, ’riting and ’rithmetic — offers schools the opportunity to provide effective programming for teens to reduce the likelihood of them using relationship for violence as they move into adulthood.
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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 | 0.060 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".