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Record W2031930498 · doi:10.1111/imre.12128

Immigration Policy in Australia, Canada, New Zealand, and the United States: An Overview of Recent Trends

2014· article· en· W2031930498 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Migration Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsLegalizationImmigrationImmigration policyPolitical scienceContext (archaeology)RefugeePublic policyImmigration lawEconomic growthHuman capitalDevelopment economicsEconomicsGeographyLaw

Abstract

fetched live from OpenAlex

Immigration policies in most host nations of the west have undergone significant changes in recent years. Based on the four country-specific papers that appear in this section of the journal, and also on our own research, we present an overview of these changes and their context. In all countries, economic considerations play a central role in shaping immigration policy and greater importance is given to scientific research. Several common policy changes are noted in Australia, Canada and New Zealand which include: a shift away from a human capital focus toward more targeted selection based on labor market demand for specific skills, increased emphasis on temporary foreign worker programs, attraction of international students, an overhauling of the refugee system, and regionalization of immigration. In the U.S., while adoption of some of these changes has often surfaced in public policy and academic discussions, legalization of unauthorized migrants remains an important policy debate, with recent arguments focusing on the economic benefits of legalization.

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)0.000
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: Review · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.387
Teacher spread0.332 · 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