The Legal Status of Aboriginal Customary Adoption Across Canada: Comparisons, Contrasts and Convergences
Bibliographic record
Abstract
Aboriginal customary adoption has been recognized for over 40 years in Canadian courts and under statutes as forming legal family relationships without requiring the same administrative procedures as statutory adoption. The rights and obligations flowing from those relationships vary from tradition to tradition, however, and it is still unclear which customary practices will be upheld in litigation. The integral to a distinctive aboriginal culture test in constitutional law presents steep evidentiary hurdles, and, since most cases involve statutory rights and benefits, customary adoption has sometimes been narrowly interpreted as simply mirroring statutory adoption, resulting in similar rights and benefits. At the same time, mainstream adoption in Canada has been moving towards an openness model in practice but the details of these agreements are rarely legally enforceable. The openness of customary adoption is admired and copied across the country, while some First Nations and Inuit communities are discussing more safeguards for custom adoption than have traditionally been in place. There appears to be a slow convergence of customary and statutory adoption both socially and legally in Canada. The larger trend towards open adoption may in fact operate as a corrective in respect to the somewhat narrow interpretation of custom favoured by some courts and legislators.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.015 | 0.019 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".