The importance of grit and its influence on female entrepreneurs
Bibliographic record
Abstract
Objective: This study aims to provide a deeper understanding of the connection between grit and its impact on female entrepreneurs. Research Design & Methods:A qualitative research study was conducted among female entrepreneurs from different industries and life stages.The theoretical framework by Bandura of self-efficacy was used to guide and inform the study. Findings:The key finding among all of the participants was the importance of grit, which according to them, made the ultimate difference in their success.Grit is an important construct that we should scrutinize, because it was demonstrated to have profound effects on the respondents.The narrative surrounding female entrepreneurs is often presented in regards to the challenges they face.However, it is necessary to comprehend the element regarding how women continue to be resilient in the face of adversity across every step of the entrepreneurial life-cycle from experiencing gender bias, juggling their personal lives, and professional responsibilities.There is evidence that proves the impact of grit on personal and professional endeavors, most notably entrepreneurs. Implications & Recommendations:Further research is recommended given the importance of the study and the impact female entrepreneurs have on the global economy. Contribution & Value Added:This study aimed to further validate the importance of this research and analyze whether when you possess grit you are able to demonstrate passion and perseverance towards your longterm goals and follow through despite adversity and setbacks.Demonstration of a North American lens and the feedback from women from different industries and life stages positively demonstrated the impact that grit had on their entrepreneurial endeavors and entrepreneurial success.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".