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Record W2378049992 · doi:10.1017/s0008423916000160

Usage du français et préférences politiques des néo-Québécois

2016· article· fr· W2378049992 on OpenAlexaboutno aff
Antoine Bilodeau

Bibliographic record

VenueCanadian Journal of Political Science · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesFrenchPhilosophy

Abstract

fetched live from OpenAlex

Résumé Cette étude examine l'hypothèse qu'il existe un lien entre l'usage de la langue française chez les néo-Québécois et leurs relations aux communautés politiques québécoise et canadienne. L’étude examine séparément la première et la seconde génération de néo-Québécois appartenant à une minorité visible. Conformément aux autres études sur le sujet, la présente recherche montre qu'un plus grand usage du français est associé à une plus forte préférence pour la communauté politique québécoise. L’étude suggère également que la fréquentation de l’école francophone est associée à une plus forte préférence pour la communauté politique québécoise. Dans les deux cas, les relations sont observées autant chez la première que chez la seconde génération. Néanmoins, les résultats montrent que même lorsqu'ils ont fréquenté l’école francophone et qu'ils font usage de la langue française dans leur vie quotidienne, les néo-Québécois affichent une préférence pour la communauté politique québécoise plus faible que celle observée chez la population majoritaire francophone.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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 designObservational
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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

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