Mesurer les forces des jeunes personnes contrevenantes ? Pourquoi et comment ?
Bibliographic record
Abstract
Deux outils sont généralement utilisés pour mesurer les facteurs de protection chez les jeunes contrevenants : the SAVRY and the SAPROF-YV. Bien que ces outils présentent de bonnes propriétés psychométriques, ils ne mesurent que les aspects positifs dans la vie du jeune qui ont un effet protecteur au moment de l’évaluation. Les forces, pour leur part, peuvent être présentes sans pour autant être mobilisée (Ward, 2017) et ne pas avoir d’effet protecteur au moment de l’évaluation (Serin et al., 2016). Les outils mesurant les facteurs de protection ne mesurent ainsi qu’une facette des aspects positifs dans la vie des jeunes. L’objectif de cette conférence est de présenter le premier instrument consacré à l’évaluation structurée des forces chez les jeunes personnes contrevenantes, le Strengths / Structured Assessment for Youth (S/SAY), comprenant l’ancrage théorique et le descriptif de l’instrument, ainsi que ses propriétés psychométriques évaluées au Québec et en Belgique francophone.
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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 | 0.006 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.013 |
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".