Assessment of the Reasons for the Termination of Entrepreneurial Activity: Data for Various Countries in 2020
Bibliographic record
Abstract
The research featured the issue of business termination. The COVID-19 pandemic hit small and medium-sized businesses all over the world. The research objective was to assess various economic indicators in order to explain why entrepreneurs had to abandon their business in 2020. The study was based on the economic and mathematical models that represent the functions of normal distribution. The author analyzed the opinions of entrepreneurs from 39 countries, who were asked to explain why they had to give up their business. The survey was part of the Global Monitoring of Entrepreneurship. The analysis revealed four indicators that determined the positive and negative reasons for the entrepreneurs to stop their business activities. The article introduces some new information about the impact of the COVID-19 pandemic on this process. Most entrepreneurs (56.3 %) gave up their business for some pandemic-unrelated negative reasons. A quarter of them (28 %) were forced to close their businesses due to the negative consequences of the pandemic. Only one-sixth of the participants terminated their business activities for a positive reason. Further research will assess the consequences of the pandemic in 2021.
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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 | 0.000 | 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 | 0.001 |
| 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".