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Record W3139466183 · doi:10.1111/spol.12718

Social policy in the face of a global pandemic: Policy responses to the <scp>COVID</scp>‐19 crisis

2021· article· en· W3139466183 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

VenueSocial Policy and Administration · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Face (sociological concept)Political scienceSocial policyFinancial crisisPolitical economyDevelopment economicsSociologyEconomicsSocial scienceKeynesian economicsLawMedicineVirology

Abstract

fetched live from OpenAlex

How have welfare states responded to the coronavirus pandemic? In this introductory article, we provide a synopsis of papers that comprise this special issue on social policy responses to COVID-19, an overview of some of the key questions they raise, and some provisional answers to these questions. Our conclusions are threefold: first, these social policy responses, while entailing new developments in many countries, nonetheless reflect, at least in part, existing national policy legacies. Second, these responses can be understood as a form of "emergency Keynesianism," which is characterized by the massive use of deficit spending during economic crises, with the aim of to supporting rather than challenging core capitalist institutions. Third, there are clear differences in terms of the nature of the reforms enacted during the initial phase of the COVID-19 crisis as compared to reforms enacted as a response to the 2008 financial crisis.

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.078
GPT teacher head0.441
Teacher spread0.363 · 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