EFFECT OF THE UNIVERSITY IN THE ENTREPRENEURIAL INTENTION OF FEMALE STUDENTS
Bibliographic record
Abstract
Many researchers have studied gender differences in the entrepreneurial intention of students by analyzing the influence of several intrinsic and extrinsic factors on the antecedents of entrepreneurial intention. Fewer researchers have analyzed the influence of the university’s environment and support system on the precursors of the entrepreneurial intention of students in general and of female students in particular. This study aims to fill that gap by analyzing the influence of the university’s environment and support system on the precursors of entrepreneurial intention of female students at a university in Atlantic Canada. Findings of this study confirm that two precursors of entrepreneurial intention—i.e., attitude toward behavior and perceived behavioral control—mediate the effects of the university’s environment and support system on the entrepreneurial intention of female students. They also confirm that the university’s environment and support system comprises three distinct but interrelated dimensions, namely entrepreneurship training, start-up support, and entrepreneurial milieu. Results of this study also suggest that the university’s environment and support system has a positive relation with the perceived behavioral control of female students. However, findings of this study also suggest that the university’s environment and support system has a positive but negligible influence on the attitude toward the behavior of the same students. The outcomes of this study will help the university assess the efficacy of its innovation and entrepreneurship initiatives in promoting entrepreneurial activities. By understanding its entrepreneurial efficacy, the institution will be better equipped to raise the perceptions of venture feasibility and desirability, thus increasing students’ perceptions of opportunity.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".