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Record W4362685868 · doi:10.1504/ijtgm.2023.130143

Determinants of entrepreneurial intentions among the immigrants: Canadian perspective

2023· article· en· W4362685868 on OpenAlexaffabout
Nadeem Akhtar, Syed Muhammad Azeem, Abdullah Basiouni, Ghulam Mustafa Mir

Bibliographic record

VenueInternational Journal of Trade and Global Markets · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPerspective (graphical)ImmigrationDemographic economicsEntrepreneurshipPsychologyBusinessEconomicsPolitical science

Abstract

fetched live from OpenAlex

The observational study revolves around the attitudes towards entrepreneurship. A survey of 387 Canadian immigrants, predominantly from the South Asian countries, i.e., Pakistan and India, was conducted. The data was then analysed using SmartPLS 3.2.8. The study reveals that perceived structural support (PStS) is a weak pointer of entrepreneurial intentions. Instead, personal attributes, i.e., self-efficacy and internal locus of control, contribute to entrepreneurial intentions. The outcomes also raise questions about the Canadian government's immigration strategy, which chooses foreigners based on financial potential and not on starting their own business. The study serves as a guideline for policymakers that if immigrants carrying personal attributes of high self-efficacy provided social support in the immigrant country, they could quickly start a new business.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.868

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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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
Published2023
Admission routes2
Has abstractyes

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