Does mentoring reduce entrepreneurial doubt? A longitudinal gendered perspective
Bibliographic record
Abstract
Purpose Mentoring appears to be a good support practice to reduce entrepreneurial doubt, amongst other things. Although perceived similarity could foster the mentoring relationship, gender dyad composition may also influence doubt reduction for entrepreneurs because of the potential gender stereotype in entrepreneurship. Design/methodology/approach The authors performed longitudinal research based on an initial sample of 170 entrepreneurs supported by a mentor to investigate the evolution of entrepreneurial doubt. Findings This study demonstrates that doubt can be reduced with mentoring, but only temporarily for male mentees. Gender stereotypes may be at play when it comes to receiving the support of a female mentor as entrepreneurship is still, unfortunately, a “male-dominated world.” Receiving support from mentors perceived as highly similar within the dyad does not reduce entrepreneurial doubt. Trusting the mentor is an important aspect, besides gender, in reducing entrepreneurial doubt. Originality/value The research provides insights into the gendered effect of mentoring to reduce entrepreneurial doubt. It shows that gender dyad composition should be taken into consideration when studying mentoring or other similar support to 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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".