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Record W3114719979 · doi:10.1177/2057150x20980843

Stability and change in strategic action fields: Municipal solid waste incineration in China, 1988–2020

2020· article· en· W3114719979 on OpenAlexaff
Xixi Zhang

Bibliographic record

VenueChinese Journal of Sociology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIncinerationContext (archaeology)ChinaMunicipal solid wasteAction (physics)Empirical researchPolitical scienceEngineeringGeographyWaste management

Abstract

fetched live from OpenAlex

The theory of strategic action fields (SAFs) is a perspective from which to better understand the emergence, stability, and change of the meso-level social order. However, the transferability of this theoretical perspective requires additional empirical evidence. Therefore, this study regards municipal solid waste (MSW) incineration in China as a SAF, in which various forces vie for the dominant position around the construction and operation of incineration plants. Given that all fields are embedded in a shifting social and cultural context, I analyze the interactions and competitions between incumbents and challengers. I then examine a series of consecutive events in the SAF, such as the emergence of the waste crisis, the development of MSW incineration, and consequential episodes of contention. I also investigate other factors that may affect the prospects for stability and change of the SAF, including actions of the state, influences of other related fields, and large-scale crises. By tracing the developmental trajectory of the SAF of MSW incineration, I discuss the applicability of the theory of SAFs to understanding an underexplored field in China.

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 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)0.001
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 score0.113
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.064
GPT teacher head0.316
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2020
Admission routes1
Has abstractyes

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