Best Interests of the Child: Exploring Social Science and Jurisprudential Perspectives
Bibliographic record
Abstract
In this chapter we share our beginning journey to better understand the notion of best interests of the child from two perspectives: a social science perspective and a jurisprudential perspective. First, to explore the best interests of the child from a social science viewpoint, an electronic Delphi survey approach was used with leading/executive human services professionals (from health, social services, education, and justice) and state-level public policy makers to ascertain their extant notions of the best interest of the child and related issues. Just over 80 intersectorial experts (by position), whose work directly or indirectly (policy or administration) related to children and their families, provided their viewpoints. Second, this chapter describes our exploration of the best interests of the child concept from a jurisprudential angle. This involves a consideration of the special nature of children’s rights along with a brief analysis of two important Supreme Court of Canada decisions where the focus is on best interests of the child.
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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 | 0.027 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.016 | 0.102 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".