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Record W4414258040 · doi:10.1080/09644016.2025.2560168

‘Two hands, multiple fingerprints’: how ideology and politics shaped China’s water market reforms (1998–2021)

2025· article· en· W4414258040 on OpenAlexaff
Jesper Svensson, Yahua Wang, Sicheng Chen, Dustin Garrick, Hang Zheng

Bibliographic record

VenueEnvironmental Politics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIdeologyCorporate governancePoliticsChinaProperty rightsState (computer science)Institutional changeTRACE (psycholinguistics)

Abstract

fetched live from OpenAlex

Water markets in China have received ample scholarly attention, but less is known about the political, ideological, and international influences that shaped their evolution. Using institutional analysis and a power-centered approach, we trace three Australian-funded projects (2005–2019) alongside domestic policy shifts to analyze how market ideas were institutionalized. We show how policy entrepreneurs embedded water trading within China’s governance system by drawing on ideological principles—including politics at the centre, ideological pragmatism, and economic decentralization—to bind market instruments to Party legitimacy. We also examine variation across pilot sites, showing how China’s water markets evolved through distinct institutional pathways—from collective trading among Water User Associations in Gansu to corporate purchases in Inner Mongolia. These findings contribute to debates on state – market relations, ideational power, and institutional change in one-party states, while also opening new research avenues on group-level property rights and community-based environmental markets in China and beyond.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.704

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 studies0.0010.001
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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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