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Record W2299341114 · doi:10.7202/1034762ar

L’immigration francophone comme marché

2016· article· fr· W2299341114 on OpenAlexaffvenueabout
Isabelle Violette

Bibliographic record

VenueAnthropologie et Sociétés · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsHumanitiesPolitical scienceImmigrationEthnologyFrenchSociologyArtLaw

Abstract

fetched live from OpenAlex

Cet article a pour objectif d’analyser les tensions qui émergent de l’articulation de logiques nationalistes et économistes dans la mise en place d’un marché de l’immigration destiné à la francophonie canadienne, et plus particulièrement telles qu’elles se manifestent sur le terrain acadien néo-brunswickois. Il est argumenté que : 1) les pratiques de recrutement et de sélection de l’État canadien favorisent des parcours migratoires axés sur une idéologie individualiste néolibérale de la langue ; et que 2) cela suscite des conflits au sein du milieu d’accueil au vu du rôle de vitalisation des communautés minoritaires attribué à l’immigration francophone. Les stratégies promotionnelles adoptées par les acteurs officiels font du bilinguisme un argument de distinction vendeur sur le marché de l’immigration, ce qui attire une part d’immigrants francophones cherchant à acquérir l’anglais comme voie d’accès aux économies mondialisées. Prenant appui sur un débat entourant la langue de scolarisation, il est montré que la valorisation du bilinguisme comme capital individuel chez ces immigrants se heurte à la position nationaliste militante pour laquelle le partage du français implique une allégeance envers la minorité acadienne.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.600

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.171
GPT teacher head0.492
Teacher spread0.321 · 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

Citations10
Published2016
Admission routes3
Has abstractyes

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