Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After the outbreak of the COVID-19 crisis, the number of insolvency filings has reached a record low in 2020. However, industry sectors are affected differently. In the early phase of the COVID-19 crisis, the number of insolvencies in the service sector decreased most substantially. In the third quarter of 2020, we observe increasing insolvency numbers throughout all sectors that have, however, not reached pre-crisis level yet. Our analysis shows a pronounced decrease of insolvent micro firms with at most 10 employees until September 2020 while insolvency declarations among micro firms are rising again in the third quarter of 2020. Businesses with fully liable owners avoided insolvency filings to a much greater extent than companies with limited liability. Businesses with owners living abroad are more likely to file for insolvency. The COVID-19 crisis changed the age composition among insolvent entrepreneurs: The number of insolvency filings of older entrepreneurs (above 65 years) has started to catch up with the numbers among young entrepreneurs (below 35 years). In the age groups (35 -50 and 51-65 years) we see a strong decrease in insolvency filings. Insolvency declarations among firms located in Western Germany have dropped more sharply than the numbers in Eastern Germany resulting in a slight increase in the share of Eastern German insolvency filings. We observe no major shifts in the age composition of insolvent firms, the gender composition of insolvent entrepreneurs and entrepreneurial team size.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.044 | 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 it