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Record W2996428002 · doi:10.1017/s0305741019001528

Maintaining Social Stability without Solving Problems: Emotional Repression in the Chinese Petition System

2019· article· en· W2996428002 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.

Bibliographic record

VenueThe China Quarterly · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsDissentAuthoritarianismPolitical sciencePoliticsGrassrootsPublic relationsLawDemocracy

Abstract

fetched live from OpenAlex

Abstract What role do emotions play in state repression? Building upon ethnographic observation in one Beijing petition bureau, this paper explores the emotional labour performed by grassroots officials to demobilize social dissent. The petition system serves as an official channel through which the Chinese government receives complaints and grievances from citizens. Notwithstanding its institutional inefficiency in addressing petitioners’ requirements, this system plays a critical role in maintaining social stability. I investigate the process by which frontline petition officials manage petitions. I argue that channelling petitioners’ emotions has become one of these officials’ core functions. Petition officials have developed three types of emotional strategies – emotional defusing, emotional constraint and emotional reshaping – to absorb petitioners’ complaints. This study of emotional repression offers a fresh perspective on the affective dimension of contentious politics and also contributes to the theoretical discussion on how authoritarian regimes deal with dissent.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.290
Teacher spread0.274 · 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