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Record W2758769579 · doi:10.1177/0032321717723507

Mini-publics and Public Opinion: Two Survey-Based Experiments

2017· article· en· W2758769579 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePolitical Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMacEwan University
FundersSocial Sciences and Humanities Research Council of CanadaMacEwan University
KeywordsPublicsLegitimacyPublic opinionPoliticsGovernment (linguistics)Public relationsSurvey researchPolitical sciencePublic administrationSociologyLawSocioeconomics

Abstract

fetched live from OpenAlex

In intense forms of public consultations, select groups of citizens, called mini-publics, are given a large amount of information and then asked to deliberate on policy directions and make recommendations. Government officials may refuse to act upon these recommendations, unless they are convinced that the recommendations have wider support in the populace. This article presents the results of two survey-based experiments that assess the impact of mini-publics on the opinions expressed by random digit dialing samples of the general public. The survey-based experiments were conducted in 2013 (n = 400) and in 2014 (n = 400). Being informed about the mini-publics affected support for some policies, but not others. In both studies, respondents who were informed about the mini-publics reported higher levels of political efficacy compared to the condition where respondents were not informed about the mini-public. Hearing about these mini-publics helps to generate a sense of legitimacy in the political system.

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)0.000
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
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 head0.351
GPT teacher head0.507
Teacher spread0.155 · 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