Promesses et défis entourant l’exploitation des données administratives en protection de la jeunesse au Québec
Bibliographic record
Abstract
Since their existence, administrative data on youth protection in Quebec have been developed by Quebec public authorities. Until very recently, these data were mainly developed by the ministère de la Santé et des Services sociaux and institutions in the health and social services network for administrative purposes. These banks nevertheless hold masses of data that can contribute to the development of scientific knowledge on child abuse and intervention in this regard. With the arrival in 2003 of a new computerized clinical system implemented provincewide, it is expected that more and more knowledge on abuse and youth protection practices can be generated from Quebec’s administrative data. Hence the importance for researchers to be aware of the potential of these data and to be familiar with the issues surrounding the development of these data. This article aims to share Quebec’s experience of developing administrative data on youth protection for research purposes, to highlight their potential and identify the challenges posed by this practice.
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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 | 0.195 | 0.262 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.018 |
| Science and technology studies | 0.010 | 0.020 |
| Scholarly communication | 0.025 | 0.007 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| 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".