Predictors of injury in reported cases of child punishment abuse in Canada
Bibliographic record
Abstract
In 1998 an estimated 135, 573 child maltreatment investigations were conducted in Canada (Canadian Centre for Justice Statistics, 2001).Of these reports, 45Yo were substantiated by the investigating child welfare worker.Across all maltreatment categories investigated (physical, emotional, sexual, neglect), physical harm was documentedin 17% of substantiated cases.Furthermote, almost half $a%) of all the substantiated physical abuse cases documented physical harm, the harm being sufficiently severe to require medical treatment n6% of the cases.The majority of injuries (86%) involved bruises, cuts, and scrapes, and the remainng injuries were evenly distributed over the other physical harm types such as burns, scalds, broken bones, head traum4 fatal harm, or other health condition (Canadian Centre for Justice Statistics, 2001).Figures highlighted by police-reported data and hospitalization records of injuries to children resulting from maltreatment also present a cause for concern.In 1999, police- reported data indicated that 55% of children and youth physically assaulted by family members suffered minor injuries requiring first aid and3Yo suffered physical injuries that required medical attention at the scene or transportation to a medical facility (Canadian Centre for Justice Statisticg 2001).Also, although hospitalization records for assault and maltreatment in Canada from 1993/1994 to 1998/1999 revealed that overall rates of children treated in hospitals for injuries as a result of violence declirred slightly from a rate of 26 to 23 per 100,000 children, the rate for children under the age of one increased from 45 to 58 per 100,000 children during this time period (Canadian Centre for Justice CHAPTER I
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".