Childhood Prevalence of Involvement with the Child Protection System in Quebec: A Longitudinal Study
Bibliographic record
Abstract
The goal of this study, the first of its kind in Canada, was to estimate the child lifetime prevalence of child protection involvement in Quebec. Using administrative and population data spanning 17 years, we performed a survival analysis of initial incidents of child protection reports, confirmed reports, confirmation of a child's security or development being compromised, and placement outside the home for one day or more. We found that before reaching the age of 18 years, over 18% of children were reported to child protection at least once, one in every ten children (10.1%) in the province had a report that led to the finding of their security or development being compromised, and over 5% were placed outside the home. We found that neglect was a primary concern in close to half (47.6%) of cases. By using a full population dataset, we obtained a more accurate prevalence estimate than studies using synthetic cohort life tables. These findings only captured initial incidents of involvement with child protection, meaning this study does not show the extent of recurrent involvement for some children. The findings reflect prior results showing that neglect is common in initial child protection involvement but less pervasive than has been shown in incidence studies, suggesting that recurrent child protection involvement is more driven by neglect than initial incidents are.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".