Differentiating Between Substantiated, Suspected, and Unsubstantiated Maltreatment in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The decision to substantiate is a key factor in determining eligibility for services and decisions to press criminal charges or to remove a child, and it is frequently the basis for selecting samples of maltreated children or to measure recidivism or intervention effectiveness. Although there is a growing body of research on case substantiation in the United States, few studies have examined this decision in other jurisdictions. Using data from the 2003 Canadian Incidence Study of Reported Child Abuse and Neglect, this study examines the profiles of a national sample of 10,010 investigations. Multivariate analyses reveal that substantiation decisions are generally made in a fashion that is relatively consistent with the clinical characteristics of cases. Along with severity of harm, parent risk factors, and housing risk factors, police referrals are among the most important predictors of case substantiation. Cases involving multiple forms of maltreatment are also more likely to be substantiated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it