Responding to safety concerns and chronic needs: trends over time
Bibliographic record
Abstract
BACKGROUND: For the past 20 years, the Ontario child welfare sector has made significant legislative and policy changes. Changes to legislation and policy can impact the public and sector's response to child maltreatment and inform identified trends. Using an investigative taxonomy of urgent protection and chronic need this paper examines the shift in the nature of investigated maltreatment over time. METHODS: Data from five cycles of the Ontario Incidence Studies of Reported Child Abuse and Neglect (1993, 1998, 2003, 2008 and 2013) were used. Provincial incidence rates were calculated by dividing the weighted estimates by the child population 15 years of age and under and then multiplying by 1000 in order to produce an annual incidence rate per 1000 children. Investigations were divided into urgent (severe physical harm, sexual abuse, neglect and physical abuse of children under 4) and chronic (risk only, exposure to intimate partner violence, emotional maltreatment, neglect and physical abuse of children four or over). Tests of statistical significance were calculated to assess changes in subtypes between cycles. RESULTS: Between 1993 and 2013, the rate of child maltreatment related investigations completed in Ontario has increased from 20.48 per 1000 children to 53.27 per 1000 children. Overall there has been a decline in the incidence of urgent investigations from 9.31 per 1000 child maltreatment investigations in 1993 to 5.94 per 1000 maltreatment investigations in 2013. There has been a fourfold increase in the incidence of chronic investigations from 11.18 per 1000 child maltreatment investigations in 1993 to 47.33 per 1000 maltreatment investigations in 2013. CONCLUSION: The nature of child protection work using the urgent-chronic taxonomy shows a dramatic shift in the types of concerns identified without a corresponding shift in the way families are assessed for need. The provision of a forensic investigation to all families does not distinguish between urgent safety concerns and needs that may require prolonged engagement. Effective service provision requires more precision in our response to these diverse concerns.
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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 | 0.001 | 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".