Utilization of the Canadian Incidence Study of Reported Child Abuse and Neglect by child welfare agencies in Ontario
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study was to analyze how child maltreatment surveillance data from the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS) is used by senior child welfare decision makers. METHODS: This triangulation mixed-methods study included quantitative and qualitative methods to facilitate an in-depth exploration from multiple perspectives. We interviewed Ontario child welfare decision makers to measure utilization of the CIS in policy development. RESULTS: The majority of respondents were aware of the CIS data. Decision makers reported using these data to determine resource allocation, understand reported maltreatment trends and validate findings at their own agencies. Urban agencies used the data more than did rural agencies. CONCLUSION: This study is the first to triangulate data to understand and improve utilization of child maltreatment surveillance data. The study participants indicated considerable appreciation of the data and also provided ideas for improvements across the surveillance cycle.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".