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Record W1977919203 · doi:10.1162/posc.2010.18.2.189

Public Participation in the Making of Science Policy

2010· article· en· W1977919203 on OpenAlexaff
Darrin Durant

Bibliographic record

VenuePerspectives on Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsYork University
Fundersnot available
KeywordsIndividualismNormativePoliticsDemocracySociologyIdentity (music)Deliberative democracyAnalogyLiberal democracyPublic policyEpistemologyPolitical philosophyPolitical sciencePublic administrationLaw and economicsLawPhilosophy

Abstract

fetched live from OpenAlex

This paper argues that, because Science and Technology Studies (STS) lost contact with political philosophy, its defense of public participation in policy-making involving technical claims is normatively unsatisfactory. Current penchants for political under-laboring and normative individualism are critiqued, and the connections between STS and theorists of deliberative democracy are explored. A conservative normativity is proposed, and STS positions on public participation are discussed in relation to current questions about individual and group rights in a liberal democracy. The result is avenues to normatively defend public participation, by analogy with identity politics and Habermas, while also theorizing its limits.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.065
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0090.029
Scholarly communication0.0170.013
Open science0.0020.014
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0060.001

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 head0.578
GPT teacher head0.566
Teacher spread0.011 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2010
Admission routes1
Has abstractyes

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