The Paradox of Breadth: The Tension between Experience and Legitimacy in the Transition to Entrepreneurship
Bibliographic record
Abstract
In a study of artists who launched independent record labels in the music industry from 1990 to 2013, we focus on explaining the paradox generated when prospective entrepreneurs accumulate broad functional experience, which signals to resource providers mastery of different skills and access to various information and resources but may also undermine the legitimacy of their entrepreneurial claims because they are not seen as specialists. To resolve this paradox, we theorize that the potential legitimacy discount of categorical membership can be avoided when individuals are classified according to multiple categories simultaneously. We find that the transition to entrepreneurship is most likely to occur when an artist’s functional experience is broad but market experience is narrow: he or she has mastered a variety of skills but solicited few audiences. We also find that the paradox of breadth is attenuated—the potential penalty of functional breadth and the corresponding need to develop narrow market experience are reduced—when the entrepreneur has alternate methods of signaling legitimacy, including high status and more-typical prior work experience. Moreover, some audiences are more disposed than others to allow an entrepreneur to pursue greater novelty. Our findings suggest that mastering a variety of skills is not universally beneficial for aspiring entrepreneurs. In some circumstances, such mastery is best coupled with a narrow market focus.
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".