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Record W2048963375 · doi:10.3917/sta.106.0055

Participation des jeunes ayant une limitation fonctionnelle à des activités physiques et sportives. Visions et préoccupations des intervenants en milieu scolaire au Québec

2015· article· fr· W2048963375 on OpenAlexaboutno aff
Romain Roult, Hélène Carbonneau, Marie-Michèle Duquette, Émilie Belley-Ranger

Bibliographic record

VenueStaps · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les jeunes ayant une limitation fonctionnelle (ALF) font face à des défis plus importants en ce qui a trait à la pratique d’activités physiques et sportives et à l’adoption de saines habitudes de vie, comparativement aux jeunes présentant un développement typique. Par le biais d’une approche qualitative fondée sur la conduite de 56 entretiens, cette étude vise à mieux comprendre les stratégies mises en place par les personnes intervenant auprès de ces jeunes ALF en milieu scolaire pour les faire participer à des activités physiques et sportives et, de fait, mettre en lumière les besoins, les attentes et les préoccupations de ces encadrants sur cette problématique intégrative et éducative liée au sport. Les résultats démontrent que les activités de sports inclusifs ont un impact substantiel sur ces jeunes, leur entourage et leur milieu de vie. Parallèlement, la faiblesse de l’offre sportive pour ce public dans des cadres scolaires et parascolaires illustre bien la pertinence et l’importance de soutenir le développement d’outils pédagogiques, de formation et une nécessaire liaison à l’aménagement des espaces de pratique notamment pour inciter la mise en œuvre d’approches inclusives en activités physiques et sportives.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.114
GPT teacher head0.432
Teacher spread0.318 · 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
Published2015
Admission routes1
Has abstractyes

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