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Record W2989654402 · doi:10.7202/1065163ar

Mesurer les attitudes des enseignants vis-à-vis de l’intégration scolaire : qualités psychométriques de la version française de l’échelle Opinions Relative to Integration of Students with Disabilities (ORI) : Opinions relatives à l’intégration d’élèves ayant des besoins éducatifs particuliers (ORI-f)

2019· article· fr· W2989654402 on OpenAlexvenueno aff
Valérie Benoit, Marjorie Valls

Bibliographic record

VenueMesure et évaluation en éducation · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Les échelles permettant de mesurer les attitudes des enseignants vis-à-vis de l’intégration scolaire disponibles en français sont rares. Cet article a pour but de présenter la validité structurelle et la fiabilité de la version française de l’échelle nord-américaine Opinions Relative to Integration of Students with Disabilities (ORI ; Antonak et Larrivee, 1995). Des analyses factorielles confirmatoires et exploratoires ont été menées à partir des réponses de 306 enseignants de classe ordinaire d’un canton suisse. Les indices de la qualité d’ajustement indiquent que les modèles issus des analyses factorielles exploratoires représentent mieux les données récoltées que ne le font les modèles originaux. En conséquence, de légères différences structurelles avec l’échelle originale s’observent. Les indices de cohérence interne sont acceptables (de 0,68 à 0,91). L’échelle ORI traduite en français représente un instrument de mesure valable pour répondre aux questions de recherche relatives à l’intégration scolaire dans les pays francophones.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.417
Teacher spread0.346 · 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 teacher head, not a consensus.

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".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

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