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Record W4280516068 · doi:10.1093/polsoc/puac021

COVID-19, crisis responses, and public policies: from the persistence of inequalities to the importance of policy design

2022· article· en· W4280516068 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolicy and Society · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsInequalityPublic policySocial inequalityCoronavirus disease 2019 (COVID-19)Nexus (standard)Political scienceSociologyEconomicsDevelopment economicsEconomic growthMedicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.231
GPT teacher head0.449
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it