<scp>Group Status and Entrepreneurship</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Do unfettered markets produce too many or too few entrepreneurs? Two seminal papers [ Stiglitz and Weiss (1981) and de Meza and Webb (1987) ] obtained ambiguous answers to this question based on different assumptions about the character of information asymmetries in credit markets. The present paper approaches the same question but using a labor market model in which income is determined by ability and individuals derive utility from income and occupational group status. Occupational group status for entrepreneurs depends on the average entrepreneurial income (due to ex post screening by banks), whereas status for wage employees depends on their own income and ability (due to ex ante screening by employers). Thus, individuals create externalities through their occupational choice. It is shown that there can be too many or too few entrepreneurs in equilibrium depending on the marginal returns to ability in entrepreneurship relative to paid employment; this enables the researcher to use independent evidence about occupational marginal returns to identify the relevant equilibrium likely to arise in practice, together with the likely appropriate policy responses. Based on this approach, we suggest that there may be too many (low ability) entrepreneurs in the USA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it