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Citoyenneté et résultats économiques des immigrants au Canada

2025· article· fr· W6926447801 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2025
Typearticle
Languagefr
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationDeportationRefugeeIllegal immigrants

Abstract

fetched live from OpenAlex

Des recherches antérieures indiquent que les immigrants qui obtiennent la citoyenneté dans leur pays d'accueil en retirent divers avantages, y compris un statut juridique amélioré, des droits élargis, un engagement politique et civique accru et un sentiment plus fort d'appartenance et d'identité collective. Toutefois, les études empiriques ne permettent pas de déterminer de façon concluante si l'acquisition de la citoyenneté améliore la situation des immigrants sur le marché du travail. Deux questions sont abordées dans cette étude. Premièrement, la citoyenneté canadienne est-elle corrélée avec de meilleurs résultats économiques chez les immigrants au Canada? Deuxièmement, dans l'affirmative, l'acquisition de la citoyenneté entraîne-t-elle une amélioration de la situation sur le marché du travail?

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.012
Science and technology studies0.0030.001
Scholarly communication0.0030.000
Open science0.0000.001
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 head0.007
GPT teacher head0.256
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

Citations0
Published2025
Admission routes1
Has abstractyes

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