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Record W2996731398

Impact de la culture sur l’évolution des perceptions des enseignants immigrants

2019· article· fr· W2996731398 on OpenAlexaffabout
Dorothée Michaud

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPolitical scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Les enseignants immigrants représentent aujourd’hui 7,99% des enseignants canadiens, cependant, très peu d’études s’intéressent à l’impact de leur culture sur leur rôle de « passeur culturel ». Cette recherche exploratoire s’intéresse donc à la question de l’évolution des perceptions des enseignants immigrants lors de leur pratique enseignante au Québec. Dans le cadre de cette recherche qualitative / interprétative, cinq enseignants immigrants, originaires du Cameroun, de Tchécoslovaquie, de Roumanie, d’Algérie et d’Uruguay, ont partagé leur expérience au sein du système d’éducation du Québec (SEQ). L’analyse de leurs récits de vie a été effectuée grâce à l’identification d’unités de sens, lesquelles ont été organisées afin de dégager les indicateurs qui décrivent le phénomène étudié. Un contrecodage a permis de valider l’analyse. Les résultats montrent que les enseignants immigrants vivent un choc culturel professionnel causé par le décalage des perceptions de ce que sont un enseignant et un élève entre leur pays d’origine et le Québec. Les enseignants ayant efficacement surmonté ce décalage ont entrepris le développement d’une culture tertiaire permettant l’évolution de leurs perceptions. Finalement, pour favoriser l’adaptation des enseignants immigrants au SEQ, la sensibilisation au choc culturel professionnel, les stages d’observation et le jumelage avec des enseignants immigrants d’expériences sont à envisager.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.422
Threshold uncertainty score0.840

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.001
Open science0.0010.003
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 head0.247
GPT teacher head0.574
Teacher spread0.327 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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