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Record W2992013997

Survival of Necessity Immigrant Entrepreneurs: An Exploratory Study

2009· article· en· W2992013997 on OpenAlexaffvenueabout
Elie Chrysostome, Sébastien Arcand

Bibliographic record

VenueJournal of Comparative International Management · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsImmigrationEntrepreneurshipFace (sociological concept)Relevance (law)Latin AmericansExploratory researchDemographic economicsSociologyEconomic growthPublic relationsMarketingBusinessEconomicsPolitical scienceSocial scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

The immigrant entrepreneurs face many obstacles in host countries. Recently some researchers in management and economics have started to shade some light on these issues. However, there still remains much to be known about the phenomenon of immigrant entrepreneurship. The purpose of this paper is to fill this gap. It focuses on the factors that can foster the survival and success of the immigrant entrepreneur. This research studies the factors that can help necessity immigrant entrepreneurs achieve businesses success in their host countries. It proposes a profile for the necessity immigrant entrepreneur and discuss the relevance of the concepts of success and survival for necessity immigrant entrepreneurs. The research proposes a model that is rooted in a theoretical explanation of the survival of immigrant entrepreneurs. This model has been tested through a multiple-case study of immigrant entrepreneurs in the Latin American community of Montreal, Canada, and the results are discussed.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.064
GPT teacher head0.370
Teacher spread0.305 · 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 designQualitative
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

Citations61
Published2009
Admission routes3
Has abstractyes

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