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Representing Global Public Concern: A Critical Analysis of the Danish Participatory Experiment on Climate Change

2015· article· en· W2252592691 on OpenAlexaff
Gwendolyn Blue

Bibliographic record

VenueEnvironmental Values · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsClimate changeNegotiationUnited Nations Framework Convention on Climate ChangePolitical sciencePublicsConventionGlobal warmingCitizen journalismCorporate governancePower (physics)DanishSociologyEnvironmental ethicsPublic relationsPoliticsLawEcologyBusiness

Abstract

fetched live from OpenAlex

Drawing on the recognition that questions of discourse and power are vital components in analysing the public participation in environmental governance, this paper examines the ways in which dominant scientific discourses about the Earth's climate inform the types of public talk facilitated in and by mini-publics, particularly when they are ‘scaled up’ to address environmental issues such as climate change. World Wide Views on Global Warming (WWViews) serves as a case study. Conceived and organised by the Danish Board of Technology, WWViews was a historically unprecedented public forum in which participants, invited from a range of nations, were given the opportunity to deliberate on key themes addressed in the negotiations taking place during the United Nations Convention on Climate Change in Copenhagen (COP 15). The overarching purpose of this analysis is to invite reflection on the practices and assumptions that serve to make up publics in relation to issues that have been framed, predominantly, as scientific, universal and global.

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)0.122
metaresearch head score (Gemma)0.117
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1220.117
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0490.053
Scholarly communication0.0200.012
Open science0.0040.021
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.757
GPT teacher head0.513
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2015
Admission routes1
Has abstractyes

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