Preaching to the choir: effects of the Mentors in Violence Prevention programme on ‘the bad apples’
Bibliographic record
Abstract
Mentors in Violence Prevention (MVP) is a systematic education programme aimed at addressing gender inequality and preventing violence among boys and men. The programme originates from Canada and the USA, and since 2015 has been introduced in a number of Swedish schools. Whereas most evaluations of MVP and other programmes addressing gender-based violence focus on broad changes, we argue that these evaluations fail to provide insight into where and for whom the programmes are or are not effective. By identifying the participants with knowledge and attitudes furthest away from the target assumptions of the programme and following them throughout the programme, we can see what effects the programme has on those with the most problematic knowledge and attitudes. The study shows that MVP does not seem to contribute to a more positive development for the group of students whose knowledge and attitudes are furthest from the programme’s target assumptions. Moreover, the study shows that the comparison group shows a more positive development over time than the MVP group. This leads to the conclusion that MVP seems to have limited potential to change the specific group with low levels of knowledge about violence and most problematic attitudes towards violent behaviour.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".