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Record W4392864902 · doi:10.1080/13504851.2024.2331653

The within occupation and industry component of the immigrant-native gap in U.S. self-employment rates

2024· article· en· W4392864902 on OpenAlexaff
Nick Manuel

Bibliographic record

VenueApplied Economics Letters · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsImmigrationComponent (thermodynamics)Demographic economicsSelf-employmentEconomicsLabour economicsPolitical scienceEntrepreneurshipFinance

Abstract

fetched live from OpenAlex

This paper examines whether the higher self-employment rates among U.S. immigrants, relative to native-born Americans, can be accounted for by immigrants being over-represented in occupations and industries that are commonly pursued through self-employment. After accounting for detailed occupations and industries, approximately 58% of the immigrant-native gap in self-employment rates remains. This finding suggests that the higher self-employment rate among immigrants is driven by factors that influence the likelihood of pursuing self-employment in and of itself, rather than factors that act indirectly by driving immigrants towards occupations and industries that are commonly associated with 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.

How this classification was reachedexpand

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.974

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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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