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Record W4396234346 · doi:10.18162/fp.2023.845

Stratégies à déployer par les étudiants en situation de handicap en stage et accompagnement souhaité

2023· article· fr· W4396234346 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueFormation et profession · 2023
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à ChicoutimiUniversité du Québec en Outaouais
Fundersnot available
KeywordsSociologyPolitical science

Abstract

fetched live from OpenAlex

Les universités connaissent une hausse d’étudiants en situation de handicap (ESH) qui suscite des questions concernant l’accompagnement à leur offrir en stage. Cette recherche collaborative leur donne une voix afin qu’ils puissent : 1) identifier leurs principaux défis rencontrés en stage, 2) répertorier leurs stratégies d’apprentissage pour composer avec leurs défis et 3) identifier les mesures d’accompagnement souhaitées de la part des formateurs de stage. Un processus itératif de collecte et d’analyse de données, comportant questionnaire et groupes de discussion, suggère que les ESH souhaitent ardemment réussir en déployant différentes stratégies tout en étant accompagnés par des formateurs disposés à les accueillir dans leur altérité.

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.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.073
GPT teacher head0.434
Teacher spread0.361 · 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