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Voices of Protest Against Industrial Pollution in Hubei, China, During the 1970s and 1980s

2020· article· en· W3035457894 on OpenAlex
Liu Yun

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

VenueEnvironment and History · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsQueen's UniversityUniversity of Regina
Fundersnot available
KeywordsChinaPollutionNegotiationPolitical scienceCorporate governanceIndustrial pollutionAir pollutionEnvironmental protectionGeographyBusinessLaw

Abstract

fetched live from OpenAlex

Abstract This article examines local official records to find voices of protest against industrial pollution in Hubei, China, during its early reform era from the 1970s to the 1980s. Archival evidence from unpublished official documents indicates that to some extent local officers responded to citizens' petitions against two main forms of industrial pollution: air pollution and soil pollution. Air pollution mostly affected urban residents but elicited more contention. Soil pollution got comparatively less exposure but caused more direct damage to impacted peasants. Both rural and urban victims of industrial pollution projected their own voices of protest typically by submitting group-authored and signed or anonymous whistle-blowing letters. Protests against pollution emerged with inter-group conflict negotiation in public or semi-public venues as well as in local investigation reports. The findings discussed here help to explain how local environmental governance evolved through increasing public awareness at subnational levels in China's early reform years.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.191
Teacher spread0.175 · 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