Responding to child maltreatment in Canada: Context for International Comparisons
Bibliographic record
Abstract
The purpose of this paper is to both describe the major fi ndings from the Canadian Incidence Study of Reported Child Abuse and Neglect, 2008 (CIS-2008), and to compare these fi ndings to data reported by Gilbert et al. (2011), who derived their estimates from the US National Child Abuse and Neglect Data System. The CIS-2008 tracked 15,980 maltreatment-related investigations of children under the age of 16 conducted in a representative sample of 112 child welfare organizations across Canada in the fall of 2008. Bivariate analyses were used to explore the differences in service dispositions, age, and referral sources by primary maltreatment category and risk. The Canadian/US comparison reveals that rates of investigated maltreatment are nearly identical. Rates of substantiated maltreatment are also comparable, although slightly higher in Canada when substantiated risk of maltreatment is included in the substantiation category. The variation in substantiation and service response rates across types of investigated maltreatment requires closer analysis and highlights the need for a detailed understanding of each type of maltreatment. The rapid expansion of reports over the last decade in Canada invites discussion of the extent to which a response focused exclusively on child protection is appropriate for all cases and optimal for addressing a broad array of needs. The complexity of comparing rates between Canada and the United States requires an understanding of both substantiation rates and thresholds.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".