Bibliographic record
Abstract
Abstract This chapter presents a discussion of practice, education, policy, and research implications pertaining to the mandatory reporting of child abuse and neglect. The first section centres on implications for practice in urban, suburban, rural, and remote environments and includes aspects such as working with colleagues, reporting in the workplace, and discussing the limits of confidentiality. What follows are implications for educators of future mandatory reporters. These implications explore educating students in the typology of child abuse and neglect, working in Northern Canada, and the importance of reflection. This chapter also includes suggestions for training that can be incorporated into the curriculum such as reflection, experiential exercises, case vignette, and simulation. The latter half of the chapter explores policy implications with specific attention to data collection and analysis of reported children and families in an effort to detect and respond to racial disparities in the child welfare system. At a national level, implications also include greater consistency in mandatory reporting legislation between provinces and territories. The chapter concludes with implications for research and focuses specifically on furthering our understanding of decision-making processes and disclosure within child sexual abuse.
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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 | 0.049 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.037 | 0.006 |
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".