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Record W3023012788

Changing Income Inequality and Immigration in Canada 1980-1995

2002· article· en· W3023012788 on OpenAlexaffabout
Eric G. Moore, Michael A. Pacey

Bibliographic record

VenueSocial and Economic Dimensions of an Aging Population Research Papers · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsQueen's UniversityMcMaster University
Fundersnot available
KeywordsMetropolitan areaImmigrationInequalityDemographic economicsEconomic inequalityDifferential (mechanical device)EconomicsSpatial inequalitySocial inequalityDevelopment economicsGeography
DOInot available

Abstract

fetched live from OpenAlex

While there is a general consensus that income inequality has increased in most developed countries over the last two decades, the analytical focus has been at the national scale. However, these increases in inequality have not been uniform across different segments of society, either in terms of social group or geographic region. In particular, the high levels of immigration to metropolitan Canada have contributed to growing inequality. Using micro-level data on household income from the 1981, 1986, 1991 and 1996 censuses, this paper identifies the role of immigration and its differential impact on metropolitan and non-metropolitan areas. The impacts accelerated during the first half of the 1990s when immigration remained high yet the economy slowed. The evidence suggests that the overall impact of immigration is a relatively short-run phenomenon as recent immigrants take time to adjust to the labour market. If recent immigrants are excluded, inequality is still increasing, but at a slower rate, especially in the largest metropolitan areas.

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)0.001
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 score0.064
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.080
GPT teacher head0.347
Teacher spread0.267 · 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

Citations0
Published2002
Admission routes2
Has abstractyes

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