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Record W2944883877

Quebec and French Educational Systems for Students Diagnosed with Autism Spectrum Disorder

2016· article· en· W2944883877 on OpenAlexaboutno aff
Nathalie Poirier, Émilie Cappe

Bibliographic record

VenueBulletin de psychologie · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumAutism spectrum disorderInstitutionMedical educationClass (philosophy)AutismPopulationPsychologyEducational institutionHigher educationSpecial educationMedicinePedagogyPsychiatrySociologyPolitical scienceSocial scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

In this article, the authors identify the prevalence, severity and possible comorbidities of students diagnosed with autism spectrum disorder, educated in France or in Quebec. They describe the available academic services and evaluation systems according to the educational curriculum followed. Moreover, the educational curriculum is specific to the student’s needs, which may include being schooled in a regular classroom within a regular institution, in a special needs program within this institution, or receiving academic training and services in a special needs institution. Post-secondary and university education for this population are then described. The results identify several similarities and differences experienced by both Quebec and French autistic students. In both regions an increase in prevalent rates, regular class education, and professional services are identified. The differences lie in the number of students educated, as well as the training program received by the educators.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.032
GPT teacher head0.348
Teacher spread0.316 · 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 designNot applicable
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

Citations1
Published2016
Admission routes1
Has abstractyes

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