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Record W2215968032

L'inégalité, la pauvreté et l'intégration économique des immigrants au Canada depuis les années 1990

2014· preprint· fr· W2215968032 on OpenAlexaboutno aff
Nong Zhu, Cécile Batisse

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2014
Typepreprint
Languagefr
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Le changement de la composition ethnique et sociale des immigrants combiné à une segmentation du marché du travail et à un nouvel environnement économique depuis les années 1980 conduit à une nouvelle inégalité des chances sur le marché du travail et à des disparités de performance économique des immigrants. Une partie d'entre eux ne peuvent s'extraire de la pauvreté. À partir de données de recensements, la présente étude vise à analyser ces différentes formes d'inégalité et à en préciser les sources parmi les migrants originaires des pays du Sud au Canada depuis les années 1990. Une discrimination apparaît à travers un niveau de revenu inférieur à celui des autres groupes et une inégalité de revenu plus importante. Par ailleurs, le rendement du capital humain de ces immigrants a diminué entre 1996 et 2006. Enfin, l'analyse souligne le rôle important de l'emploi et des revenus du travail dans l'augmentation du niveau de vie des immigrants. Les politiques visant à améliorer le bien-être social et l'insertion des immigrants doivent donc se centrer sur l'amélioration du niveau de revenu et l'augmentation du taux d'emploi

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)0.003
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 score0.042
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0070.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.236
Teacher spread0.219 · 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
Published2014
Admission routes1
Has abstractyes

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