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Record W2321466385 · doi:10.1111/gec3.12117

Chinese Non‐Governmental Organisations and Civil Society: A Review of the Literature

2014· review· en· W2321466385 on OpenAlexaff
Jennifer Y.J. Hsu

Bibliographic record

VenueGeography Compass · 2014
Typereview
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCivil societyTransformative learningState (computer science)Political sciencePoliticsChinese societySociologyPolitical economyPublic administrationChinaLaw

Abstract

fetched live from OpenAlex

Abstract This article reviews the literature on Chinese non‐governmental organisations (NGOs) and civil society and argues that to understand the transformative potential of Chinese NGOs we need to consider beyond macro‐level political change. By looking at the tactics and strategies of engagement between NGOs and the state, it becomes clear that Chinese NGOs are capable of affecting communities and change at the local level. Furthermore, to fully understand the capacity of Chinese NGOs, this article argues that we cannot insist on a state–society separation as we would in other jurisdictions because it would not lead to fruitful analysis. The state of the field is assessed through an interdisciplinary lens, characterised by four major themes: the linkage between the rise of NGOs and the expansion of civil society; the rise of NGOs as a reflection of state–society relations; NGO sectoral development; and, to a lesser extent, the development of theory and frameworks.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.017
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.007
GPT teacher head0.294
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2014
Admission routes1
Has abstractyes

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