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Record W4386772905 · doi:10.1080/07352166.2023.2247502

Gendering grassrootscapes: The sociospatial relations of lower working-class women dwelling in the socialist Workers’ New Villages in post-reform Shanghai

2023· article· en· W4386772905 on OpenAlexfundno aff
Penn Tsz Ting Ip, Tsung‐yi Michelle Huang, Jing Wang

Bibliographic record

VenueJournal of Urban Affairs · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGrassrootsSociologyConceptualizationTransformative learningGender studiesUrbanizationScholarshipWorking classChinaPolitical scienceEconomic growthLaw

Abstract

fetched live from OpenAlex

Women of the lower working-class in Shanghai are seemingly invisible in Chinese urban scholarship. Drawing on fieldwork conducted between 2017 and 2021 in Shanghai, this article sheds light on the social lives of lower working-class women dwelling in the Workers’ New Villages in the wake of rapid urbanization. Mounting a threefold conceptual exploration of grassroots urbanism, genderscapes, and guanxi (social connectivity), the article develops and coins the term grassrootscapes to explicate grassroots women’s sociospatial relations with housing units, the community, and the city. Probing these multi-layered horizons to trace women’s life trajectories and gendered experiences, the article discerns how sociospatial dynamics of grassrootscapes are produced under a socialist system, in which women’s day-to-day suffering is a by-product of market reforms. Socialist workers’ housing is employed as a case study to show how the conceptualization of grassrootscapes can be a useful tool to examine the social transformation brought about by the drastic changes in urban policies in globalizing cities.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.021
GPT teacher head0.264
Teacher spread0.244 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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