Examining Child Maltreatment-Related Investigations of Children from Newcomer and non-Newcomer Households in Ontario, Canada
Bibliographic record
Abstract
Objectives: The study aims to further the understanding of child welfare involvement with Newcomer families in Ontario, Canada in 2018. This study examines a) the rate and characteristics of child maltreatment-related investigations involving Newcomer families and b) differences in child maltreatment-related investigations between Newcomer and non-Newcomer families.Methods: This study is a secondary data analysis of the Ontario Incidence Study of Reported Child Abuse and Neglect-2018 (OIS-2018). Using Statistics Canada Census Data, the Population-based Disparity Index (PDI) was calculated for Newcomer and non-Newcomer families. Descriptive and bivariate chi-square analyses were conducted to determine characteristics of investigations involving Newcomer and non-Newcomer households.Results: The PDI of the incidence of maltreatment-related investigations involving children under the age of 15 from Newcomer households versus non-Newcomer households in Ontario in 2018 is 2.48.Implications: The findings suggest that a child maltreatment-related investigation is more than twice as likely to occur if the investigation involves a child from a Newcomer household, when compared a non-Newcomer household in Ontario. This study demonstrates a need for further collaboration with Newcomer communities and their social service providers to better understand risk factors of child welfare involvement, and to increase protective factors for children from Newcomer families.
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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".