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Record W3096568259

Stages d’ergothérapie à la maternelle : analyse et proposition d’interventions préventives

2020· article· fr· W3096568259 on OpenAlexaboutno aff
Emmanuelle Jasmin, Caroline Hui

Bibliographic record

VenueErgothérapies · 2020
Typearticle
Languagefr
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMedicinePolitical sciencePsychologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Au Quebec (Canada), environ le tiers des enfants issus de milieux defavorises accusent un retard de developpement a la maternelle (5 ans). Afin de soutenir le developpement et la participation de ces eleves, un projet pilote a ete mis en place pour analyser les interventions preventives de stagiaires en ergotherapie a la maternelle. Operationnalise avec une etude de cas multiples, ce projet impliquait six stagiaires (trois dyades), supervisees a distance. Chaque dyade œuvrait durant sept semaines dans une ecole en milieu defavorise. Chaque cas incluait l’enseignante (ou l’intervenante) de maternelle et son groupe-classe. Des objectifs et des interventions ergotherapiques ont ete determines avec chaque enseignante. Les effets des interventions ont ete mesures a l’aide d’outils valides. Huit classes de maternelle ont participe a l’etude. Globalement, 78 % des objectifs d’intervention ont ete atteints. A partir des resultats, un modele logique de stages d’ergotherapie a la maternelle dans un but preventif est propose.

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)0.007
metaresearch head score (Gemma)0.015
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 score0.890
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.404
Teacher spread0.324 · 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
Published2020
Admission routes1
Has abstractyes

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