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Record W2920051667 · doi:10.3917/nresi.081.0201

Expériences rapportées de la situation universitaire par des étudiants ayant une dyslexie

2018· article· fr· W2920051667 on OpenAlexaff
Emely Ross, Georgette Goupil, France Landry

Bibliographic record

Venue˜La œNouvelle revue Éducation et société inclusives/˜La œNouvelle revue Éducation et société inclusives · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

Les universités québécoises doivent favoriser l’inclusion des étudiants en situation de handicap, dont ceux qui présentent une dyslexie. Ce trouble affecte, entre autres, la lecture et l’écriture, deux habiletés essentielles à la réussite scolaire. Cette étude exploratoire, auprès de sept étudiants universitaires ayant un diagnostic de dyslexie, vise à décrire leurs expériences rapportées de ce trouble et de leur situation universitaire. Ces étudiants ont participé à un entretien semi-structuré et ont répondu à un questionnaire. Les entretiens ont fait l’objet d’une analyse de contenu. Les résultats font ressortir que les participants semblent avoir peu de connaissances théoriques sur leur dyslexie et font peu mention de stratégies destinées à garder ou structurer l’information. Les participants utilisant des aménagements se servent surtout du temps supplémentaire lors des examens. Les participants décrivent des réactions à la fois positives et négatives de la part de leurs professeurs, appuyant ainsi la nécessité de poursuivre les activités de sensibilisation aux troubles d’apprentissage.

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)0.013
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 score0.234
Threshold uncertainty score0.464

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.428
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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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