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Record W92617509 · doi:10.5206/cie-eci.v38i2.9136

Pour une conceptualisation de la compétence multiculturelle de l’enseignant

2009· article· fr· W92617509 on OpenAlexaffvenue
Mirela Moldoveanu

Bibliographic record

VenueComparative and International Education · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPedagogyProfessionalizationCompetence (human resources)SociologyHumanitiesPsychologyPhilosophySocial psychologySocial science

Abstract

fetched live from OpenAlex

Dans un contexte de professionnalisation des enseignants, la compétence multiculturelle bénéficie d’un statut ambigu et controversé autant dans les discours gouvernementaux que dans la pratique enseignante. En s’appuyant sur des formalisations récentes du concept de compétence, cette étude vise à cerner le sens et le statut de la compétence multiculturelle de l’enseignant. Menée auprès de neuf étudiants-maîtres francophones, cette recherche exploratoire utilisant une méthodologie qualitative interprétative propose une définition de la compétence multiculturelle de l’enseignant et discute du statut à lui accorder parmi les autres compétences professionnelles. Enfin, des suggestions de développement de ladite compétence pendant la formation initiale des enseignants sont formulées. In the context of teacher professionalization multicultural competence receives an ambiguous and controversial status both in the government discourse and in teaching practice. Based on recent formalizations of the concept of competence, this study aims at defining the meaning and status of teachers’ multicultural competence. This exploratory research carried out with nine francophone student teachers used an interpretive qualitative methodology to propose a definition of multicultural competence for teachers, and discusses the status it should be granted among other professional competences. Suggestions are provided on how to devleop this competence during initial teacher education.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.300
GPT teacher head0.517
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2009
Admission routes2
Has abstractyes

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