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Record W1855269821 · doi:10.25336/p6np62

Immigrant Language Proficiency, Earnings, and Language Policies

2009· article· en· W1855269821 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Studies in Population · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrodata (statistics)EarningsImmigrationLanguage proficiencyDemographic economicsLanguage policyGovernment (linguistics)Quantile regressionPolitical scienceEconomicsCensusPsychologyLinguisticsSociologyDemographyAccountingPopulationEconometricsMathematics education

Abstract

fetched live from OpenAlex

This paper addresses two questions: 1) what are the impacts of language proficiency on the earnings of Canadian adult immigrants; 2) what are the current policy responses. Using a five-level scale of English/French language use, our analysis of Public Use Microdata File for the 2001 census confirms the positive association between proficiency in Canada’s charter language(s) and immigrant earnings. Compared to permanent residents who are highly proficient in English and/or French, those with lower levels of proficiency have lower weekly earnings. Quantile regressions reveal that the relative advantage of English/French language proficiency is higher for those in the top quarter of the earnings distribution; conversely, greater penalties exist for immigrants with low levels of language proficiency at the upper end of the earnings distribution. The likely impacts of federal policies on increasing English/French language proficiency of immigrant workers are discussed, focusing on two federal government initiatives for language training and two recent immigration policy changes.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.578
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.344
Teacher spread0.324 · 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