The Canadian Experience with Views of the Child Reports: A Valuable Addition to the Toolbox?
Bibliographic record
Abstract
Non-evaluative Views of the Child Reports prepared by legal or mental health professionals are an increasingly popular means of involving children in the resolution of parenting disputes in parts of Canada, but there are no widely accepted standards and significant differences exist in how children are interviewed and how these reports are prepared. This article examines the methods by which children's views are obtained for use in court and non-court dispute resolution processes, reviews Canadian case law on Views of the Child Reports and presents the results of a survey of 65 legal and mental health professionals about their practice and experience preparing Views of the Child Reports. We discuss the benefits and limitations of these reports, the need for clear protocols and the factors that should be taken into account in establishing best practices, as well as the need for further research.
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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 | 0.046 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".