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Record W2959313082

Au-delà du cabinet : Evaluer le bégaiement dans différents contextes et évaluer la qualité de vie

2019· article· fr· W2959313082 on OpenAlexaff
Anne‐Lise Leclercq, Lucie Ménard, Anne Moïse‐Richard

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2019
Typearticle
Languagefr
FieldPsychology
TopicStuttering Research and Treatment
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesCabinet (room)GeographyPolitical scienceArtArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Le bégaiement est un trouble complexe dont les manifestations varient d’une situation à l’autre. Les patients peuvent témoigner d’une bonne gestion de leur parole au quotidien, mais évoquer des difficultés marquées dans certaines situations comme le fait de devoir s’adresser à un étranger ou prendre la parole devant un groupe. Par conséquent, lors de l’évaluation, un recueil de parole dans le cadre sécurisant du cabinet de logopédie ne permet pas toujours de révéler les principales difficultés rencontrées par les personnes qui bégaient. En outre, plusieurs études ont révélé un impact négatif du bégaiement sur la qualité de vie, qui n’est pas forcément lié à la sévérité objective du bégaiement. Cet exposé présente d’une part la réalité virtuelle comme un outil permettant d’évaluer la prise de parole dans différentes situations et d’autre part des données préliminaires sur la validation en français du questionnaire OASES, un outil d’évaluation de la qualité de vie chez la personne qui bégaie.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.023
GPT teacher head0.304
Teacher spread0.281 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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