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Record W1841926999 · doi:10.25336/p6s899

Trends in occupational and earnings attainments of women immigrants to Canada, 1971-1996

2003· article· en· W1841926999 on OpenAlexafffundvenueabout
Richard A. Wanner, Michelle Ambrose

Bibliographic record

VenueCanadian Studies in Population · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMicrodata (statistics)EarningsImmigrationCensusDemographic economicsDemographyOccupational prestigeCohort effectGeographyPopulationEconomicsSociologySocioeconomic status

Abstract

fetched live from OpenAlex

This study examines the extent to which immigrant women arriving in Canada between the 1960s and the early 1990s were able to attain occupations and earnings equivalent to those of Canadian-born women using a data file created by merging public-use microdata files from Censuses of Canada between 1971 and 1996. We study both changes in country of birth effects on the earnings and occupational status of women aged 25 to 29 immigrating prior to each of the five census years and the experience of successive female immigrant cohorts as they age to determine the extent to which the effects of birthplace on occupational status and earnings change over their careers. In both cases we find a considerable advantage associated with being educated in Canada compared to being educated abroad. For those visible minority immigrants just beginning their careers in Canada, we could find no evidence that more recent cohorts have lower attainments than earlier cohorts, though this was true for some European groups. In our analysis of aging cohorts we find evidence of a tendency for immigrant earnings to converge with those of the Canadian born and for that tendency to be stronger in more recent cohorts.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.336
Teacher spread0.303 · 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 teacher head, 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

Citations13
Published2003
Admission routes4
Has abstractyes

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