Quelques enjeux normatifs des nouvelles réalités de l’adoption internationale
Bibliographic record
Abstract
Dans une récente recherche comparative et interdisciplinaire (anthropologie et droit), menée en partenariat avec le Secrétariat à l’adoption internationale et l’Association des centres jeunesse du Québec, qui visait à réfléchir sur des ajustements du droit aux nouvelles réalités de l’adoption internationale, nous avons examiné les normes juridiques et les pratiques dans différents pays d’accueil et d’origine en dégageant les conceptions, les normes et les valeurs qu’elles véhiculent et en identifiant leurs principaux impacts. Le présent article expose les grandes lignes de cette problématique. Il soulève des questions pratiques qui subsistent au Québec, malgré de récents changements législatifs concernant la conciliation des différentes lois nationales et l'adoption intrafamiliale.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".