Societal Well-being, Self-Control, and Entrepreneurial Resilience
Bibliographic record
Abstract
Entrepreneurial resilience is associated with subsequent entrepreneurial re-entry of entrepreneurs who have had unfavorable exits due to a crisis. Considering well-being and self-control as emotional competencies explained by the individual level trait emotional intelligence (EI) model and rendering them as culturally contextualized societal psychological capital (PsyCap), we posit to explain their cross-cultural comparative influences on entrepreneurial resilience. We use PsyCap theory to establish these as emotional competencies that constitute an individual’s positive PsyCap. Societies with an increased number of individuals having such competencies will have higher reserves of positive PsyCap thus making these competencies as culturally contextualized. Using 5,351 survey responses from the Global Entrepreneurship Monitor obtained from 29 countries post the 2008 economic crisis and supplementing with data from the World Values Survey we show that the dimensions of well-being at the societal level positively influence entrepreneurial resilience. This influence is mediated by societal-level self-control. Implications of our findings in regard to entrepreneurial resilience are discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".