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Record W2163838791

L'effet des politiques sociales sur l'emploi des nouveaux immigrants à Montréal : une analyse longitudinale et conjoncturelle

2009· preprint· fr· W2163838791 on OpenAlexaboutno aff
Nong Zhu, Cécile Batisse

Bibliographic record

VenueAmericanae (AECID Library) · 2009
Typepreprint
Languagefr
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

La question de l'insertion sur le march du travail des immigrants est aujourd'hui devenue essentielle.Les dispositifs mis en place au Canada cherchent favoriser la rarticulation entre immigration, march du travail, protection sociale, formation et cohsion sociale.Cet article tudie l'insertion des immigrs sur le march du travail qubcois quatre points de leur parcours : aprs 1, 2, 3 et 10 ans de sjour.Outre les caractristiques individuelles, nous portons une attention particulire l'impact de l'environnement macroconomique et des politiques sociales de redistribution sur la probabilit de sortie d'un pisode de non-emploi de ces immigrants.Nos rsultats montrent que les immigrs forment un groupe htrogne du point de vue de leurs caractristiques individuelles et de leur employabilit.Certains restent marginaliss sur le march du travail.C'est le cas notamment des femmes, des migrants gs et dans un premier temps des moins qualifis.L'assurance chmage et les prestations sociales jouent ngativement sur la sortie de l'pisode de nonemploi.Le taux de chmage local exerce un effet significativement ngatif sur la probabilit d'avoir un emploi et touche essentiellement l'emploi des immigrants peu qualifis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0030.004
Scholarly communication0.0000.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.360
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2009
Admission routes1
Has abstractyes

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