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Record W7161972304 · doi:10.82308/2183

Représentations culturelles et identité d'immigrants adultes de Montréal apprenant le français

2007· dissertation· fr· W7161972304 on OpenAlexaboutno aff
Valérie Amireault

Bibliographic record

Venuenot available
Typedissertation
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCultural environmentIdentity (music)Cultural backgroundSubject (documents)

Abstract

fetched live from OpenAlex

L'environnement cosmopolite montréalais s'enrichit et se modifie au fil des annéesavec la mobilité des populations et l'arrivée de nouveaux immigrants. Dans ce contexte,il apparaît essentiel de connaître le développement des représentations culturelles desimmigrants en lien avec leur propre identité culturelle, et envers la langue française et lesgens qui parlent cette langue. Pour le milieu de l'enseignement du français, une telleconnaissance est essentielle pour susciter le développement de curriculum répondant auxbesoins langagiers et culturels des immigrants. L'éducation en langues secondes peutdonc fournir des opportunités pour mieux connaître l'Autre, sa langue et sa culture, etéventuellement pour permettre de le comprendre et de l'apprécier davantage.

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)0.004
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 score0.179
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.014
GPT teacher head0.362
Teacher spread0.348 · 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
Published2007
Admission routes1
Has abstractyes

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Same topicFrench Language Learning MethodsFrench-language works237,207