A Profile of Exposure to Intimate Partner Violence Investigations in the Canadian Child Welfare System: An Examination Using the 2008 Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-2008)
Bibliographic record
Abstract
Objectives: To provide a profile of the incidence and characteristics of substantiated exposure to intimate \npartner violence (IPV) investigations in Canada in 2008. Methods: Bivariate analyses were conducted \nexamining four types of substantiated investigations in order to better understand the response of the child \nwelfare system to IPV investigations: (i) investigations in which exposure to IPV was the single substantiated \nform of maltreatment; (ii) investigations in which another type of maltreatment (physical abuse, sexual \nabuse, neglect, or emotional maltreatment) was the single substantiated form of maltreatment; (iii) \ninvestigations in which exposure to IPV co-occurred with at least one other form of maltreatment; (iv) \ninvestigations in which there were co-occurring forms of maltreatment that did not include IPV. Results: \n41% of substantiated investigations involved exposure to IPV, with 31% of investigations involving single \nform IPV and 10% of investigations involving IPV that co-occurred with another form of maltreatment. A \ntotal of 51% of investigations were substantiated for a single form of other maltreatment (physical abuse, \nsexual abuse, neglect or emotional maltreatment) and 8% of investigations were substantiated for cooccurring \nforms of these four types of maltreatment. The investigations were compared on family, child, \ncase, and service characteristics. Conclusions and Implications: Exposure to IPV is a complex issue \nand demands an equally complex response that includes cross sector collaboration. Child welfare agencies \nreceiving referrals regarding intimate partner violence should aim to identify opportunities to prevent \nrecurrence and support the victims identified in the investigation.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".