Uncovering physical harm in cases of reported child maltreatment
Bibliographic record
Abstract
Child protection statutes are designed to protect children from harm, yet there is surprisingly limited information available about injuries or other forms of harm documented in cases of reported child maltreatment. To examine trends in the rate of substantiated child maltreatment investigations in Canada involving physical harm over a twenty-year period. and Setting: The Canadian Incidence Study of Reported Child Abuse and Neglect is a cyclical study which uses a file review methodology to collect information about child maltreatment-related investigations from child protection workers across Canada. We conducted secondary analysis of data from three cycles of the Cis (1998, 2008, and 2019). Because information on physical harm was not available from Quebec during the 2019 cycle, we limited the analyses to the rest of Canada, excluding Quebec. The rate of child maltreatment-related investigations has more than doubled between 1998 and 2019 from 24.53 to 56.03 investigations per 1000 children. Rates of substantiated maltreatment have also increased (from 10.21 to 17.56 investigations per 1000 children), while the rate of substantiated investigations involving documented physical harm has decreased (from 1.81 to 0.79 investigations per 1000 children). Child protection agencies in Canada are identifying less physical harm than they were two decades ago although the overall rate of investigations has increased in the same time period. As protecting children from harm is a paramount purpose of child protection statutes across the country, further information is needed to understand whether the duty to protect is being met.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".