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Record W4319303886 · doi:10.1080/14672715.2022.2164738

The Party-State’s Hegemonic Project and Responses from Civil Society: The Case of Service-oriented NGOs in China

2023· article· en· W4319303886 on OpenAlexaff
Shirley Yang

Bibliographic record

VenueCritical Asian Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHegemonyCivil societySociologyPoliticsChinaState (computer science)AuthoritarianismPublic administrationIdeologyPolitical scienceLawPolitical economyDemocracy

Abstract

fetched live from OpenAlex

This article investigates the Chinese party-state’s hegemonic project to construct social consent in NGOs and how they react to this. Using service-oriented NGOs as examples, it argues that the changing institutional dynamics of NGO governance in China demonstrates that Chinese civil society is a site of ideological struggle. The party-state has adapted some foreign concepts and practices of civil society, which have been popular in China since the reform era, to serve its political and socioeconomic agenda, while avoiding political challenges of liberal values and discourse. Civil society’s hegemonic transformation relies on two major mechanisms—professionalization and Maoist incorporation. This process, however, also leaves some space for NGOs to act differently. Some have been comfortably incorporated into the state-led welfare system and reproduce authoritarian norms and practices among their beneficiaries, whereas counter-hegemonic activism still exists among groups that link their stance and agenda closely with marginalized groups in society.

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)0.009
metaresearch head score (Gemma)0.005
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 score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0250.029
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.371
Teacher spread0.333 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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