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Record W4394938397 · doi:10.1504/ijbg.2024.138020

Multivariate analysis of ethnic migrants' entrepreneurial motivation in Ghana

2024· article· en· W4394938397 on OpenAlex
Jacqueline Zakpaa, Léo‐Paul Dana

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.

Bibliographic record

VenueInternational Journal of Business and Globalisation · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEthnic groupMultivariate statisticsMultivariate analysisEntrepreneurshipDemographic economicsEconomicsSociologyStatisticsMathematicsAnthropology

Abstract

fetched live from OpenAlex

This study was a cross-sectional survey, and it sought to determine the multivariate structure of factors affecting the self-employment entrepreneurial motivation of internal ethnic migrant entrepreneurs in Ghana. A total of 210 entrepreneurs were selected through simple random sampling in the four major cities in Ghana. High dimensional sets of data produced from a Likert scale with 71 indicator variables of migrant entrepreneurial motivation factors, which were incorporated into a structured questionnaire, were factor analysed, using SPSS version 21. The findings revealed that the significant influences on the entrepreneurial motivation of this group of ethnic migrant entrepreneurs, consisted of factors such as relational social capital or informal personal networks, wealth creation through human capital development, lack of fear of risks taking, impact of a previous job, the effect of the regulatory environment, labour market-based unemployment, access to start-up capital through personal savings, culture, and increase wealth motivation.

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 score0.422
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.033
GPT teacher head0.327
Teacher spread0.294 · 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