COVID-19, crisis responses, and public policies: from the persistence of inequalities to the importance of policy design
Bibliographic record
Abstract
Abstract The coronavirus (COVID-19) pandemic has once again highlighted the importance of social inequalities during major crises, a reality that has clear implications for public policy. In this introductory article to the thematic issue of Policy and Society on COVID-19, inequalities, and public policies, we provide an overview of the nexus between crisis and inequality before exploring its importance for the study of policy stability and change, with a particular focus on policy design. Here, we stress the persistence of inequalities during major crises before exploring how the COVID-19 pandemic has highlighted the need to focus on these inequalities when the time comes to design policies in response to such crises. Paying close attention to the design of these policies is essential for the study of, and fight against, social inequalities in times of crisis. Both during and beyond crises, policy design should emphasize tackling with inequalities. This is the case because current design choices shape future patterns of social inequality.
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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 | 0.053 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".