The COVID‐19 pandemic and government responses: A gender perspective on differences in public opinion
Bibliographic record
Abstract
OBJECTIVE: The 2019 novel coronavirus disease (COVID-19) crisis has led to shutdowns of the cultural, associational, and economic life in many parts of the world and had a severe impact on gender relations in many societies. This study engages with gender differences in public support of severe infringements of personal and economic freedoms. METHODS: We use data from an original survey conducted by CINT in the United States and Germany in June 2020. Descriptive statistics both aggregated for the two countries and then split by country as well as multinomial logistic regression analyses gauge gender differences in support of COVID-19 related confinement measures. RESULTS: Men and women rather converge on the level of risk COVID-19 might cause to their health and economic situation, but the two sexes still differ in their assessment of their preferred government reaction to the disease. Women are approximately one-third more likely to advocate stricter infringements, compared to men. This finding illustrates that while both sexes share similar risk evaluations, women are more prudent for their health than men. CONCLUSION: With this study, we add to the literature on risk aversion and gender differences. In a pandemic situation, women appear to be more risk averse than men.
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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 | 0.004 | 0.010 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".