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Record W4408576103 · doi:10.1080/07256868.2025.2469232

Beyond Consumption? The Mall as Everyday Space of Cosmopolitan Sociability in Beijing

2025· article· en· W4408576103 on OpenAlexafffund
Meng Xu

Bibliographic record

VenueJournal of Intercultural Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBeijingConsumption (sociology)Space (punctuation)CosmopolitanismAestheticsEveryday lifeSociologyEconomic geographyChinaGeographyArtPolitical sciencePoliticsComputer scienceArchaeology

Abstract

fetched live from OpenAlex

This paper engages with recent theorization of cosmopolitanism in practices and public spaces to explore everyday cosmopolitanism in the context of contemporary urban China. By broadening its original focus on transnational migration and mobility, I use cosmopolitan sociability as a lens to analyse how everyday cosmopolitanism takes shape in Taikoo Li, a large-scale inner-city open-air mall in Beijing. Drawing on ethnographic research conducted in the mall, I identify three aspects of cosmopolitan sociability: (1) passive sociability that enables Chinese mall visitors to cultivate open attitudes toward difference; (2) fleeting sociability through which they establish competencies to deal with otherness; and (3) routinized sociability whereby they demonstrate willingness to engage with cultural diversity. These findings move beyond viewing the mall merely as a space for consumption to highlight its role as a space where intercultural conviviality thrives. I argue that cosmopolitan sociability is not just what the mall offers to its visitors but, more importantly, what people do to make the mall a cosmopolitan canopy.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.388
Teacher spread0.362 · 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
Published2025
Admission routes2
Has abstractyes

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