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Record W2606350579 · doi:10.1163/15718115-02402003

Labour Migrations to Resource-rich Countries: Comparative Perspectives on Migrants’ Rights in Canada, Norway and the United Arab Emirates

2017· article· en· W2606350579 on OpenAlexaffabout
Marko Valenta, Zan Strabac, Jo Jakobsen, Jeffrey G. Reitz, Mouawiya Al Awad

Bibliographic record

VenueInternational Journal on Minority and Group Rights · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIrregular migrationResource (disambiguation)Order (exchange)Political scienceMigrant workersDevelopment economicsGeographyDemographic economicsEconomyEconomic growthEconomicsEconomic geography

Abstract

fetched live from OpenAlex

This article compares migrants’ rights and labour-migration policies of three resource-rich receiving countries located in the Persian Gulf, North America and Europe, respectively. The wealthy economies of Canada, Norway and the United Arab Emirates have emerged as some of the largest receivers of labour migrants. The comparative analysis herein focuses on distinctive characteristics of the different migration regimes and policies which regulate the rights of labour migrants. It is maintained that the countries we have explored could hardly be more different, and that the actual similarities with regard to migration policies are limited. Yet, we have still identified some surprising and unexpected converging trends. Specifically, these countries use some similar tools and exclusionary policies in order to restrict the legal status of certain categories of labour migrants, particularly low-skilled migrants.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0070.005
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2017
Admission routes2
Has abstractyes

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Same venueInternational Journal on Minority and Group RightsSame topicMigration and Labor DynamicsFrench-language works237,207