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Intergenerational Implications of Immigration Policy on Apprenticeship Training and the Educational Distribution in Canada

2013· article· fr· W1966701741 on OpenAlexaffvenueabout
James Ted McDonald, Christopher Worswick

Bibliographic record

VenueCanadian Public Policy · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsCarleton UniversityUniversity of New Brunswick
Fundersnot available
KeywordsHumanitiesPolitical scienceImmigrationArt

Abstract

fetched live from OpenAlex

Dans cet article, nous analysons, à partir de données du recensement de 2006, l’incidence et le rendement de la formation en apprentissage chez les hommes parmi les immigrants et les Canadiens nés au pays. Les hommes qui ont immigré au Canada quand ils étaient enfants ainsi que ceux de la première génération qui sont nés au Canada sont plus susceptibles d’avoir suivi une formation en apprentissage s’il y a une forte probabilité que les hommes de la génération de leur père (venant du même pays d’origine) aient suivi une telle formation. Le rendement de cet apprentissage (lié à une scolarité de niveau secondaire) équivaut approximativement à une hausse de 13 % des revenus. Une simulation intercohortes suggère également que des changements à long terme dans les pays d’origine des immigrants sont susceptibles de mener à une réduction du nombre de garçons des cohortes qui commenceront l’école dans les années à venir et qui voudront suivre une formation en apprentissage.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.951
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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".

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Citations0
Published2013
Admission routes3
Has abstractyes

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