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Record W4310063277 · doi:10.1017/s0305741022001618

The Camp Fix: Infrastructural Power and the “Re-education Labour Regime” in Turkic Muslim Industrial Parks in North-west China

2022· article· en· W4310063277 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 · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Ethnic Minorities and Relations
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChinaLiminalityUnderclassGovernment (linguistics)State (computer science)Power (physics)Political scienceSociologyEconomic growthLawEconomics

Abstract

fetched live from OpenAlex

Abstract Industrial parks in north-west China occupy a liminal space between labour camps and private industry. Drawing on worker interviews, government documents, industry materials and images this article shows that for-profit public-private industrial parks have been built as part of a “camp fix” mechanism centred on detaining and “re-educating” Uyghurs and Kazakhs at the periphery of the nation. It argues that these industrial parks concentrate forms of repressive assistance and “dormitory labour regimes” that operate at other frontiers of Chinese state power and point these strategies of disempowerment towards a seemingly permanent, ethno-racialized underclass, producing a “re-education labour regime.” It further argues that the material infrastructures of these surveiled and policed spaces themselves are productive in enforcing the goals of the “camp fix”: the creation of high-quality, underpaid, docile and non-religious Muslim workers who are controlled through the built environment.

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)0.002
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 score0.717
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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