Entrepreneurial but not Entrepreneur: How Entrepreneurial Identity Shapes Career Identities
Bibliographic record
Abstract
Graduates of entrepreneurship programs acquire an entrepreneurial identity that empowers them with a creative mindset. In this paper, I answer the question, how does this entrepreneurial identity help graduates develop a meaning that conceptualize their entrepreneurial role in their future careers? I examine how entrepreneurial identities shape the future careers of those who study entrepreneurship. I analyzed and coded 83 interviews with students and graduates from an undergraduate (43 informants) and graduate (32 informants) entrepreneurship programs, in addition to eight informants who took entrepreneurship courses at some point in their university education and founded new ventures. I found that entrepreneurial identity acquired during entrepreneurship education shapes the profiles of graduates, and five career paths were identified: dream-building, entrepreneurship pop culture, institutional entrepreneurship, investment entrepreneurship, and new venture path. I argued that entrepreneurship education might not prepare its graduates to become founders, but it empowers them with entrepreneurial identity awareness and entrepreneurship institutional knowledge. Finally, graduates of entrepreneurship education can perform entrepreneurial activities beyond new venture creation.
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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 | 0.009 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".