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Record W2807468672 · doi:10.6000/1929-7092.2018.07.18

Antecedents of Entrepreneurial Intent: A Cross-Country Comparison of Generation Y University Students

2018· article· en· W2807468672 on OpenAlexvenueno aff
Esther Marire, M. Dhurup

Bibliographic record

VenueJournal of Reviews on Global Economics · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsCross countryPsychologyDemographic economicsEconomicsBusiness

Abstract

fetched live from OpenAlex

This paper convey the findings of a study carried out to compare the antecedents of entrepreneurial intentions of students from two universities within the Southern African continent. A cross-sectional survey, based on 400 students from two universities of two different countries (South Africa and Zimbabwe) was conducted using a self-administered questionnaire. Using the theory of planned behavior, personal attitude, subjective norms and perceived behavioral control, and entrepreneurial education were used to predict entrepreneurial intentions. Personal attitude and subjective norms and entrepreneurial education seem to positively influence behavioral intentions. Behavioral control showed insignificant predictive relationship with behavioral intentions. It is recommended that entrepreneurial education should be made a core and integral component of study at universities so that universities as social institutions can create an impetus with a holistic approach including all role players with adequate resources to support students in entrepreneurial ventures.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.047
GPT teacher head0.325
Teacher spread0.278 · 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 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

Citations6
Published2018
Admission routes1
Has abstractyes

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