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Record W2610457977 · doi:10.7202/1039273ar

Élaboration d’un outil écosystémique et participatif pour l’analyse des besoins des enfants en contexte de négligence : L’outil Place aux parents

2017· article· fr· W2610457977 on OpenAlexaffvenue
Annie Bérubé, Vicky Lafantaisie, Sylvain Coutu, Diane Dubeau, Josée Caron, Line Couvillon, Marjolaine Giroux

Bibliographic record

VenueRevue de psychoéducation · 2017
Typearticle
Languagefr
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCégep de l'OutaouaisUniversité du Québec à Trois-RivièresUniversité du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La négligence auprès des enfants est un phénomène reconnu et largement documenté. Malgré les nombreuses études sur le sujet, il demeure difficile de bien mesurer quelle réponse la famille et son environnement offrent aux besoins des enfants. Cette difficulté pourrait expliquer pourquoi les études actuelles peinent à documenter des changements au sein des familles en contexte de négligence. L’article s’appuie sur une définition écosystémique de la négligence et présente l’élaboration d’un outil destiné à fournir une analyse des besoins de l’enfant, de la réponse qu’il obtient, ainsi que des caractéristiques de l’environnement familial et social dans lequel il grandit. L’outil préconise en outre une approche participative auprès des familles en permettant aux intervenants, mais également aux figures parentales de se prononcer sur la situation familiale. Les propos de 54 parents et de 8 intervenants ont été analysés de façon qualitative afin de connaître les avantages et les défis reliés à l’utilisation de l’outil proposé.

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)0.015
metaresearch head score (Gemma)0.015
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 score0.016
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0090.019
Scholarly communication0.0120.012
Open science0.0020.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.091
GPT teacher head0.414
Teacher spread0.323 · 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

Citations11
Published2017
Admission routes2
Has abstractyes

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