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Record W2903446681 · doi:10.3917/bupsy.558.0887

Accompagner les parents d’accueil québécois : comment aménager un espace pour les parents dans un système de protection des enfants ?

2018· article· fr· W2903446681 on OpenAlexaffabout
Ariane Boyer, Raphaële Noël

Bibliographic record

VenueBulletin de psychologie · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Les auteurs de cet article s’intéressent aux enjeux de la mise en place d’un accompagnement pour soutenir les parents d’accueil québécois. Des entretiens semi-directifs ont été réalisés auprès de 10 parents de familles d’accueil régulières (5 hommes et 5 femmes). Les principaux thèmes, qui émergent de l’analyse qualitative inductive, mettent à jour différentes difficultés, auxquels ces parents sont confrontés, des éléments qui ont facilité l’exercice de leur rôle, ainsi qu’un discours positif sur leur expérience de l’espace de parole permis par le contrat de recherche. Ces résultats soulèvent des questions quant à la possibilité du système de protection de l’enfance d’assurer une fonction de soutien pour ces parents. La recherche souligne le double mandat soutien-évaluation des représentants de l’institution, et conduit à s’interroger sur la prise en considération de l’expérience du parent d’accueil dans un système qui représente la protection des enfants. Les paramètres d’un accompagnement spécifique à la parentalité d’accueil sont discutés.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.980

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.007
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.052
GPT teacher head0.320
Teacher spread0.268 · 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 designQualitative
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

Citations4
Published2018
Admission routes2
Has abstractyes

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