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In and Out of the Ethnic Economy: A Longitudinal Analysis of Ethnic Networks and Pathways to Economic Success across Immigrant Categories

2012· article· en· W1826055952 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 · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmigrationEthnic groupDemographic economicsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The economic benefits to immigrants of taking jobs in ethnic workplaces, relative to the open economy, are heavily debated. We examine longitudinally differences across immigrant categories in how the choice of ethnic or non-ethnic workplace influences the ethnic composition of social networks and how these factors impact immigrants’ economic success. Using the Longitudinal Survey of Immigrants to Canada, with data 6 months, 2 years, and 4 years after arrival, we find support for both sides of the ethnic economy debate when it is qualified by immigrant category. While economic immigrants benefit from non-ethnic workplaces, family immigrants face economic penalties in the open economy and do better in ethnic workplaces. We argue that policies sorting immigrants into visa categories do much of the work of leading them into segmented paths of incorporation.

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 score0.365
Threshold uncertainty score0.996

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 communication0.0000.001
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 head0.056
GPT teacher head0.369
Teacher spread0.313 · 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