Gendered impact of training on entrepreneurial self-efficacy: a longitudinal study of nascent entrepreneurs
Bibliographic record
Abstract
Entrepreneurial self-efficacy (ESE) is a central concept for understanding the entrepreneurial process. Studies show that ESE differs between men and women. Does training have a gender-specific effect on ESE? To answer this question, we followed 238 nascent entrepreneurs who received 330 hours of training and we measured their level of ESE before training, six months after the initial assessment, then 6 and 12 months after that (final sample of 42). We found that gender had a significant effect on ESE change throughout the periods. Women had lower levels of ESE than men before training, but this difference was no longer significant after. We also found a quadratic effect of gender: while ESE was boosted in women after training, this effect did not remain constant in the ensuing periods. For men, we found the opposite quadratic effect: training slightly reduced their ESE, and the level increased slightly in the ensuing periods. For both genders, training appears to have had a short-term effect on their ESE. This highlights the necessity to study changes in ESE from a long-term perspective, and also the need to investigate how training or other support can lead to ESE improvement for female entrepreneurs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".