Entrepreneurship and the Post-COVID-19 Recovery in Emerging Economies
Bibliographic record
Abstract
ABSTRACT Entrepreneurs play a focal role in a society's economic recovery from major disruptions such as the COVID-19 pandemic. We argue that entrepreneurs’ ability to identify and act on entrepreneurial opportunities during the crisis reflects their resilience, and their innovations facilitate new patterns of work, learning, and leisure activities in post-COVID-19 societies. However, how, how quickly they act, and how influential their actions are depends on their context in terms of institutions, resource access, and market volatility. In China, some entrepreneurs have shown great resilience by utilizing network relationships and digital technology, not only to overcome short-term disruptions in 2020 but to shape the evolving ‘new normal’ where behaviors and capabilities have changed as a consequence of the experience of the pandemic. We discuss drivers of such resilient entrepreneurship during the COVID-19 pandemic in China and call for further research on the interplay between external disruptions, different types of entrepreneurship, and the consequences for resilience in emerging economies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".