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Record W4288567506 · doi:10.5117/aup.7751456.v1

Hygiene, Sociality, and Culture in Contemporary Rural China. The Uncanny New Village

2019· preprint· en· W4288567506 on OpenAlexaff
Lili Lai

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSocialityUncannyChinaContext (archaeology)SociologyWelfareEthnographyEconomic growthGeographyGender studiesPolitical scienceAnthropologyAestheticsEconomics

Abstract

fetched live from OpenAlex

By taking the lived body as local, unstable, diverse, and open to urban and global incorporations, this book highlights contemporary Chinese and global reductions of diverse conditions into generalized objects, especially in the Chinese state's well-intended social welfare effort of "building socialist new villages" which in the mean time shows clearly how judgments come to be disguised as facts (Cf. Pigg 1992). The political economic roots and social determinants of "dirty villages," the strategies of inhabiting "villages with empty centers," and the local and national projects of cultural production all reveal much about class and power in China today. Unlike other close ethnographies of small places in China, this reading of local culture is considered in the context of the national and global practices that maintain a deeply divisive rural-urban divide in everyday hygienic practices. This book argues that substantive ethnographic attention to the specificities of village life in the contemporary Henan context can destabilize China's chronic rural-urban divide and contribute to an effective rural welfare intervention to improve the hygienic conditions of village life at present.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.009
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.308
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2019
Admission routes1
Has abstractyes

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