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Record W4407187850 · doi:10.1017/s0265052524000256

The Moral of the Story: Contesting Narratives at the Nexus of Science and Policy During COVID-19

2024· article· en· W4407187850 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 Philosophy and Policy · 2024
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNexus (standard)Coronavirus disease 2019 (COVID-19)Narrative2019-20 coronavirus outbreakPolitical scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyLiteratureVirologyArtMedicineComputer scienceOutbreak

Abstract

fetched live from OpenAlex

Abstract Using the case of the Scientific Advisory Group for Emergencies in the United Kingdom as illustration, this essay offers a framework for understanding the role of narratives and competition among narratives in mediating the relationships between scientific advisers and policymakers during the COVID-19 pandemic. Throughout the pandemic, competing judgments about scientific independence and democratic accountability, about the risks of action and inaction, and about the appropriate balance of costs and benefits to society as a whole and to subgroups of the population were filtered through the narrative perspectives of different discourse coalitions. This narrativization of the process had both positive and negative effects. On the one hand, it provided common platforms for the integration of disparate types of knowledge relevant to policymaking. On the other hand, narratives provided platforms for rival coalitions in ongoing contests that left unresolved the central normative questions of distributional fairness and democratic accountability.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
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 head0.054
GPT teacher head0.376
Teacher spread0.322 · 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