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Immigrants' Propensity to Self-Employment: Evidence from Canada

2001· article· en· W2077502849 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 · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsImmigrationDemographic economicsResidenceSelf-employmentHuman capitalOddsDescriptive statisticsLabour economicsLogistic regressionEconomicsPolitical scienceEconomic growthEntrepreneurshipMedicine

Abstract

fetched live from OpenAlex

Despite the appeal of the “enclave thesis” and the “blocked mobility thesis,” there are other relevant factors that help to explain why some immigrants engage in self-employment. Using the Longitudinal Immigration Data Base in Canada for 1980 to 1995, this study identifies characteristics of immigrants that yield a higher or lower propensity to self-employment. Descriptive statistics show that immigrants often use self-employment to supplement employment income and that the intensity and extensity of self-employment vary among immigrant entry cohorts, depending on gender, the year of immigration, and duration of stay in Canada. A logistic model predicting self-employment indicates that arrival in better economic years, longer residence in Canada, higher educational levels, older immigrants, and immigrants selected for human capital have higher odds of self-employment. These findings suggest that even though immigrants may be attracted or driven to self-employment, better-equipped immigrants are more inclined to engage in self-employment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.051
GPT teacher head0.325
Teacher spread0.273 · 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