Kids and critters : links between child maltreatment and animal abuse
Bibliographic record
Abstract
The purpose of this study was to examine the links between child maltreatment and animal abuse, how these two forms of maltreatment often occur simultaneously within a family and how the existence of one maltreatment type should alert professionals to the potential for other types of harm. File reviews were completed at both Family and Children's Services of Renfrew County (FCS) and the Ontario Society for the Prevention of Cruelty to Animals (OSPCA), Renfrew County Branch. Data were collected on relevant variables, including maltreatment type, removal and return of children/animals, legal involvement and risk ratings. A total of 188 common files were found, representing almost 25% of OSPCA cases in a 6-year period; 48% of these cases were open at both agencies at the same time. When the files for the two agencies were merged, several statistically significant correlations were found, including: correlations between physical harm to pets and domestic violence for FCS clients; between Criminal Code charges for FCS clients and police involvement for OSPCA clients; and between removals of children from families involved with FCS and neglect of pets. These findings suggest that there is a need for cross-training and cross-reporting between child protection and animal welfare sectors to ensure better protection of both children and animals.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".