A Gender-Informed Understanding of Children in the Care of Child Protection
Bibliographic record
Abstract
The purpose of the present study was to explore the differential representation of children\nby gender in child protection services. The sample of children was drawn from a large child protection agency in south-western Ontario consisting of 1,041 cases. Child protection files were reviewed to derive study data. Results indicated that there were significant differences by gender regarding the type o f maltreatment children experienced. Girls were more likely to be sexually abused, while boys were more likely to be neglected. Girls more often had psychological concerns, while boys exhibited more cognitive impairment. Further, boys were involved with more other agencies/services than their female counterparts. Boys were younger, more often suspended from school, had more attention and/or conduct disorders, and were more often medicated for adjustment disorders. Girls were significantly older and more likely to have been chronically absent from school. It is suggested that boys may come to the attention of children’s services at an earlier age due to more obvious, externalizing behaviours.\nThese findings are discussed in relation to their implications for understanding the gendered experiences of boys and girls in child protection services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".