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Record W1979495537 · doi:10.1080/00036846.2012.703311

A note on Canadian migration to the United States during the 1980s and 1990s

2012· article· en· W1979495537 on OpenAlexaffabout
Richard Mueller

Bibliographic record

VenueApplied Economics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsImmigrationCensusDistribution (mathematics)EarningsEconomicsDemographic economicsSuccessor cardinalQuality (philosophy)QuantileLabour economicsPolitical scienceEconometricsPopulationDemographyAccountingSociology

Abstract

fetched live from OpenAlex

Considerable media attention had been directed towards the flow of highly talented Canadians to the United States in the 1990s. There are firm theoretical reasons, however, to believe that qualitative differences in migration began as early as the 1980s, owing to the widening distribution of earnings and the related increased returns to education in the United States relative to Canada, both of which could result in qualitative improvements in the migration flow. US immigration policy remained essentially unchanged during the 1980s, but changed markedly in the 1990s owing to the implementation of the Canada–US Free Trade Agreement (CUFTA) and its successor, the North American Free Trade Agreement (NAFTA). We use a flexible empirical approach to document these changes in immigrant quality using 1980, 1990 and 2000 US census data. Our results suggest that improvements in Canadian immigrant quality occurred during the 1990s, but these also happened earlier, casting doubt on the hypothesis of improving Canadian immigrant quality in the 1990s. Quantile regressions also show that improvement in the entry quality of immigrants was not limited to the upper tail of the earnings distribution.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.866

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 studies0.0010.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 designNot applicable
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

Citations0
Published2012
Admission routes2
Has abstractyes

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