tzLSEk'IER OPPORTUNITY COSTS AND ENTREPRENEURIAL ACTIVITY
Bibliographic record
Abstract
We provide empirical support for the hypothesis that the lower the EXECUTIVE opportunity costs of individuals, the more likely they are to undertake SUMMARY entrepreneurial ctivity. This prediction emerged from earlier theoretical work in which we modeled the decision of individuals to develop new ventures on their own, seek the backing of a venture capitalist, or remain as paid employees. We use a large sample, drawn from the 1992 Canadian Labor Market Activity Survey. We find that paid employees who choose to leave their employment to become entrepreneurs earned, prior to leaving, substantially less on average then those whose employment s atus did not change and who remained paid employees throughout he survey period. Specifically, we establish that the wages of those workers who chose to remain paid employees throughout he survey period were, on average, 12 % higher than the wages of those who left their employment to become entrepreneurs. To obtain this result, we performed a multivariate regression analysis in which we isolated the effect of employment status by controlling for gender, age, education, marital status, and region of the country. The employment-status coefficient was 2349 (t = 2.644; p =.008), indicating that new entrepreneurs earned in 1988, on average, $2349 less than
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".