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Record W1849047237

Two Trust-Based Uses of Mini-Publics in Democracy

2009· article· en· W1849047237 on OpenAlexaff
Mark E. Warren

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPublicsDeliberative democracyDemocracyPoliticsPolitical sciencePublic relationsPublic opinionFunction (biology)Law
DOInot available

Abstract

fetched live from OpenAlex

An important success of deliberative democratic theory and practice over the last two decades has been to show that ordinary citizens are capable of sophisticated political judgments, if they participate in focused, deliberative processes. Among the most interesting of these processes are minipublics. A minipublic is a deliberative forum consisting of 20-500 participants, focused on a particular issue, selected as a representative sample of the public affected by the issue, and convened for a period of time sufficient for participants to form considered opinions and judgments. While the basic structure of these processes is already well developed, the question of what minipublics might do for a democratic political system - how they might come to function within it - is less well understood. Minipublics have primarily been justified as a way of providing advice to decision-makers that represents considered public opinion, or more generally as one means of increasing citizen participation in decision-making. I suggest here that in addition to these “democratic” roles, minipublics can serve in two key trust-based functions. They can serve as trusted information proxies to guide citizens’ political judgments in the absence of informed, deliberative opinion in broader publics. And they can serve as anticipatory publics in rapidly developing policy areas that are likely to generate issues, but which do not (yet) have public opinion attached to them. Both roles enhance citizens’ capacities to divide their political labours between participation and trust in ways that enhance democratic norms.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.066
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.328
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations12
Published2009
Admission routes1
Has abstractyes

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