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Record W1546018842 · doi:10.7202/1000316ar

La diversité ethnoculturelle dans les programmes français de sciences et technologie de l’Ontario : une analyse comparative entre le programme de 1998 et celui de 2007

2010· article· fr· W1546018842 on OpenAlexaffvenueabout
Donatille Mujawamariya, Mirela Moldoveanu

Bibliographic record

VenueReflets Revue d’intervention sociale et communautaire · 2010
Typearticle
Languagefr
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversité de SherbrookeUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Le ministère de l’Éducation de l’Ontario (MEO) a procédé récemment à une réforme des programmes d’enseignement. En vigueur depuis septembre 2008, le nouveau programme de sciences de la 1re à la 8e année prône une éducation antidiscriminatoire. Cette visée se reflète-t-elle dans ce programme? En quoi le nouveau programme se distingue-t-il de l’ancien au chapitre de l’éducation antidiscriminatoire? Pour répondre à ces questions, notre étude propose une comparaison des programmes en français de sciences et technologie de la 1re à la 8e année, celui de 1998 et celui de 2007, afin de mettre en lumière la place qu’ils réservent à la diversité ethnoculturelle. S’inscrivant dans une perspective d’éducation scientifique multiculturelle, notre analyse s’appuie sur la typologie des approches multiculturelles de Banks (1989). Les résultats montrent qu’au-delà de la sensibilité exprimée dans les fondements, ces programmes ne laissent que peu de place à la diversité ethnoculturelle dans les attentes et les contenus 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)0.003
metaresearch head score (Gemma)0.006
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 score0.091
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0060.005
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.065
GPT teacher head0.393
Teacher spread0.328 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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