Supporting Children Whose Parents are in Conflict with the Law through the Convention on the Rights of the Child: Honouring the Legacy of Hon. Landon Pearson
Bibliographic record
Abstract
Hon. Landon Pearson was a lifelong dedicated advocate for children, both in Canada and abroad. Her contributions to advancing children’s rights in Canada were unparalleled and, notably, included ensuring Canada’s policies and practices were in line with the country’s international commitments through the United Nations Convention on the Rights of the Child (CRC). To honour her legacy, we examine how the principle of the best interests of the child ought to be applied when decisions are made within the criminal justice system concerning offenders with parental responsibilities. While it is increasingly understood that parental conflict with the law is a traumatic and developmentally impactful experience for children, the criminal justice process seldom takes steps to mitigate these detrimental impacts. This article discusses the current research on Canadian children whose parents are in conflict with the law, particularly through the lens of Canada’s obligations under the CRC. It provides recommendations for action to standardize considerations for the best interests of the child, as defined by the CRC, into Canadian criminal justice policy.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.019 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| 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".