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Record W2920797354 · doi:10.1111/gove.12393

Authoritarian responsiveness: Online consultation with “issue publics” in China

2019· article· en· W2920797354 on OpenAlexaff
Yoel Kornreich

Bibliographic record

VenueGovernance · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of British Columbia
FundersChiang Ching-Kuo Foundation for International Scholarly Exchange
KeywordsBlueprintAuthoritarianismGovernment (linguistics)PublicsBureaucracyChinaPolitical sciencePublic relationsSocial mediaPublic opinionPublic policyPublic administrationSociologyDemocracyPoliticsLaw

Abstract

fetched live from OpenAlex

In recent years, public consultation has become a standard feature of policymaking in authoritarian regimes. While previous studies found evidence of government responsiveness to citizens' demands, they did not measure responsiveness in terms of real policy change. This article presents the first systematic analysis of Chinese central government policy responsiveness to consultative input. In 2008, the Chinese government unveiled a blueprint for health‐care reform, inviting the public to post their opinions online. Having collected 27,899 online comments, the government subsequently published a revised draft. This article analyzes a random sample of 2% of this corpus of comments, assessing the effect of comments on revisions while controlling for both media content and bureaucratic preferences. The findings demonstrate that public comments have an impact upon policy revisions and suggest that the Chinese government is more responsive to street‐level implementers than to other social groups.

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)0.013
metaresearch head score (Gemma)0.034
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.350
Teacher spread0.330 · 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

Citations70
Published2019
Admission routes1
Has abstractyes

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