Entrepreneurship Out of Shame: Entrepreneurial Pathways at the Intersection of Necessity, Emancipation, and Social Change
Bibliographic record
Abstract
Shame has been identified as a debilitating emotion that impedes entrepreneurial action. Yet, there are many examples of people who experience shame and go on to create entrepreneurial ventures. How then is entrepreneurship possible in the face of such shame? To address this question, we develop a theoretical process model that highlights the connection between individual and collective experiences of shame and elaborates when and how such experiences may lead to entrepreneurship. We suggest that third-person experiences of shame can transform first-person experiences and trigger identification with a community of similarly stigmatized others. We argue that the distinct narratives provided by these communities can reduce or enhance entrepreneurial self-efficacy, and therefore lead to different entrepreneurial pathways: some individuals may create ventures out of necessity, while others will create ventures that act as shame-free havens for themselves and others, and become a source of emancipation and social change. By outlining distinct entrepreneurial pathways out of shame, we extend current research at the intersection of entrepreneurship, necessity, emancipation, and social change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".