Gender role identity and entrepreneurial intentions: a study with university students
Bibliographic record
Abstract
The aim of this study is to investigate the association of gender role identity with the precursors (antecedents) of entrepreneurial intentions by empirically validating the relationship between gender role identity and entrepreneurial intentions. The theoretical frameworks used in the study are the Theory of Planned Behaviour (TPB) and Social Role Theory (SRT) (Ajzen, 1991; Eagly,1987). The study investigates the mediating role of the constructs of TPB- attitude towards behavior (ATB), perceived behavioral control (PBC) and subjective social norms (SSN) in the relationship between gender role identity (GRI) and entrepreneurial intentions (EI). A survey was conducted with 149 undergraduate and graduate students of all departments from the Memorial University of Newfoundland located in St John’s city in Newfoundland and Labrador province, Canada. Results suggest that gender role identity is indirectly associated with entrepreneurial intentions through subjective social norms and attitude towards behavior and also through subjective social norms and perceived behavioral control. Findings also show that higher the level of femininity, lower are the subjective social norms. This study makes a significant contribution by investigating a conceptual model of gender role identity and entrepreneurial intentions. Limitations, future directions, and conclusion have been outlined.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".