People Financing Entrepreneurs within and outside the Family: Pandemic Decline and Resilience in Cultures around the World
Bibliographic record
Abstract
People may finance entrepreneurs, often family members. Here, the question is: how has the COVID-19 pandemic affected people’s funding of family-related entrepreneurs and non-family-related entrepreneurs? The pandemic predictably reduced the funding of family-related entrepreneurs and especially the financing of non-family-related entrepreneurs. However, a culture supportive of family businesses may alleviate the declining funding of family-related entrepreneurs, predictably, while a secular–rational culture supportive of non-family businesses may alleviate the declining financing of non-family-related entrepreneurs. Similar to a field experiment, a globally representative survey was conducted before and after the disruption in 42 countries, interviewing 266,983 adults either before or after the disruption. The individual-level data are combined with national-level data on culture, amenable to hierarchical linear modeling. People’s financing of family-related entrepreneurs and especially of non-family-related entrepreneurs are found to have declined with the COVID-19 pandemic. However, culture provides resilience, in that the declining funding of family-related entrepreneurs was alleviated where the culture supports family businesses, and the declining funding of non-family-related entrepreneurs was alleviated in societies with a secular–rational culture. The findings contribute to contextualizing business angel financing temporally, as embedded in time before and after the COVID-19 pandemic disruption, and societally, as embedded in culture providing resilience.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".