All bark and no bite: Legal and professional consequences for failing to report child maltreatment
Bibliographic record
Abstract
The duty to report child maltreatment is a key legal and professional responsibility. Over time this duty to report has expanded and increasing numbers of families experience investigations by the child protection system. However, research shows that the vast majority of reports are not substantiated, and that broader mandated reporting legislation does not lead to more substantiation of child maltreatment (Rosenberg et al., 2024). This suggests there is a need to adjust reporting decisions to decrease unnecessary intrusive investigations for families and decrease resources used for investigation by an already over-burdened child protection system. One potentially fruitful area for decreasing unnecessary reports is to decrease those made by social workers to meet legal or professional responsibilities, rather than based on a genuine child protection concern. Fearing potential legal or professional disciplinary consequences mandated reporters may over-report and this research focuses on cases where mandated reporters faced legal or professional disciplinary consequences for failing in the duty to report to decrease fear-based reporting. Examining cases in Ontario, Canada only one person was found guilty in court and three social workers faced discipline. These cases involved failing to report direct disclosures of abuse, rather than suspicion. This is not meant to deter reporting based on genuine child protection concerns. This research aims to provide concrete information about the risk social workers face in cases where they do not report a situation that falls within the duty to report legislation but where they do not have a meaningful concern about child maltreatment.
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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 | 0.012 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".