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Immigrants in the Labour Market: Transnationalism and Segmentation

2009· article· en· W1969434528 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.

Bibliographic record

VenueGeography Compass · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsToronto Metropolitan UniversityUniversity of Guelph
Fundersnot available
KeywordsTransnationalismImmigrationWorkforceSociologyMarket segmentationSocioeconomic statusEconomic geographyHierarchyPhenomenonScale (ratio)Labour economicsEconomicsDemographic economicsPolitical scienceEconomic growthGeographyMarket economyEpistemologyMicroeconomicsPopulationLaw

Abstract

fetched live from OpenAlex

Abstract Various theories speak towards the labour market segmentation of an immigrant workforce. Theoretical frameworks such as Dual Labour Market Theory or Hierarchy Theory provide some value in outlining why immigrants are often found in the least desirable forms of employment. However, most theories do not consider the phenomenon of immigrant transnationalism and how forces at multiple scales shape labour market trajectories. In this paper we argue that traditional theories primarly consider socioeconomic factors in destination countries, and focus on factors at the local or national scale of analysis. In contrast, the literature on transnationalism illustrates how socioeconomic processes that operate at the global scale also influence the employment trajectories of immigrants. The integration of transnationalism with traditional labour market theories therefore provides a more complete picture when trying to understand the segmentation of an immigrant workforce.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

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 studies0.0000.000
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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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