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Record W1532479252 · doi:10.1111/imre.12172

Unionization and Income Growth of Racial Minority Immigrants in Canada: A Longitudinal Study

2015· article· en· W1532479252 on OpenAlex
Anil Kumar Verma, Jeffrey G. Reitz, Rupa Banerjee

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Migration Review · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsImmigrationEarningsWhite (mutation)Earnings growthDemographic economicsSurvey of Income and Program ParticipationEconomicsPanel Study of Income DynamicsLabour economicsLongitudinal dataPolitical scienceSociologyDemography

Abstract

fetched live from OpenAlex

This study examines the effect of unionization on the labor market integration of newly arrived immigrants in Canada. We find that non-white recent immigrants gain access to unionized jobs at a slower rate than do white recent immigrants. The effect of unionization on earnings is somewhat lower for non-white recent immigrants than for white recent immigrants. These findings are based on growth curve modeling of longitudinal data from the Survey of Labour and Income Dynamics (SLID). Therefore, unionization does not contribute to reducing the earnings gap of non-white recent immigrants relative to white immigrants and the native-born.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.070
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.035
GPT teacher head0.330
Teacher spread0.295 · 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