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Record W2618061468 · doi:10.7202/1039681ar

Évaluation de la trousse d’intervention A pour Autre©

2017· article· fr· W2618061468 on OpenAlexaffvenue
Daphnée St-Laurent, Marie-Hélène Poulin

Bibliographic record

VenueRevue de psychoéducation · 2017
Typearticle
Languagefr
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article porte sur les résultats obtenus dans le cadre de l’évaluation de la trousse d’intervention A pour Autre©. Il s’agit d’une trousse pédagogique composée de trois outils (guide, DVD, plateforme web interactive) élaborée pour soutenir l’apprentissage des habiletés sociales chez les jeunes présentant un trouble du spectre de l’autisme (TSA) âgés entre 6 et 17 ans. Elle s’adresse aux personnes autistes ainsi qu’à leurs parents et leurs intervenants. Une enquête par questionnaire en ligne et par la poste a été menée entre mars 2015 et février 2016 dans le but d’établir un portrait des utilisateurs ainsi que d’évaluer leur appréciation des divers éléments de la trousse. Cent cinq personnes (N = 105) ont répondu au questionnaire et vingt-huit (n =28) utilisent les outils. De façon globale, elles sont satisfaites de leur expérience (ergonomie du site web et utilité des outils) et considèrent la trousse efficace pour l’enseignement des habiletés sociales. Les répondants souhaitent que d’autres vidéos abordant des thèmes différents soient offertes.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.086
GPT teacher head0.422
Teacher spread0.336 · 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 designObservational
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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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