Generational imprints: A contingency approach to corruption and entrepreneurship
Bibliographic record
Abstract
Abstract Research Summary Existing research offers conflicting evidence on how corruption affects entrepreneurship. We adopt a contingency approach highlighting the role of generational imprinting. Drawing on imprinting and generational research, we argue entrepreneurs develop distinct generational imprints shaped by the environment during their formative years. Using a proprietary dataset of Chinese private firms, our findings suggest that in corrupt environments, market‐generation entrepreneurs with a transactional imprint tend to outperform their premarket‐generation counterparts in the short run, as the latter's principled imprint likely limits public relations spending. Personal life experiences—rural living and higher education—attenuate the influence of the transactional imprint, narrowing intergenerational differences in firm performance. Our study advances research on corruption and entrepreneurship by integrating institutional, generational, and individual‐level perspectives to explain how corruption affects entrepreneurs differently. Managerial Summary The relationship between corruption and entrepreneurship remains contested. Our study takes a novel angle by examining generational differences among entrepreneurs. We suggest that the distinct environments entrepreneurs experienced during adolescence shape their value orientations, leading to variation in firm performance in corrupt environments. Using a dataset of Chinese private firms, we show that, in corrupt environments, younger‐generation entrepreneurs with a transactional orientation (i.e., transactional imprint) tend to outperform older‐generation entrepreneurs with a principled orientation (i.e., principled imprint) in the short run. However, this performance gap narrows among those who lived in rural areas or received higher education. Our work highlights the crucial role of institutional environments in shaping entrepreneurs' values across generations and advocates for initiatives that cultivate more ethically grounded entrepreneurial mindsets.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".