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Record W4400314181 · doi:10.7202/1111682ar

La recomposition familiale en droit québécois : des propositions de réforme à la Loi de 2022, une reconnaissance réduite à peau de chagrin

2023· article· fr· W4400314181 on OpenAlexvenueaboutno aff
Clémence Bensa, Michelle Giroux

Bibliographic record

VenueRevue de droit Université de Sherbrooke · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La recomposition familiale concerne un nombre accru d’enfants au Québec. Le droit peine à encadrer cette dynamique familiale polymorphe. Ce texte analyse les recommandations du rapport du Comité consultatif sur le droit de la famille de 2015 sur cette question et montre qu’elles ont été réduites à peau de chagrin dans la réforme du droit de la famille de 2022. Cela s’explique par la difficulté d’encadrer la complexité de la recomposition familiale, mais également par le fait que le législateur refuse de reconnaître plus de deux parents à un enfant et d’octroyer un rôle parental à un adulte si les deux parents sont présents. La Loi 2 maintient le rôle du beau-parent à celui de parent de substitution pendant la vie commune. Une place plus importante lui est accordée au moment de la rupture de l’union recomposée, quoique toujours conditionnée à la reconnaissance d’un lien significatif avec l’enfant et sans octroi d’attributs parentaux. La Loi 12 n’a apporté aucun autre changement sur ce point.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.592

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.013
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.013
GPT teacher head0.246
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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