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Record W4401622042 · doi:10.1177/08912416241273245

The Making of Everyday Space of Publicness: Insights from a Mall in Beijing

2024· article· en· W4401622042 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Contemporary Ethnography · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicWalter Benjamin Studies Compilation
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBeijingEveryday lifeSociologyPublic spaceSpace (punctuation)EthnographyDimension (graph theory)Shopping mallChinaTRACE (psycholinguistics)UrbanismAestheticsAdvertisingPolitical scienceBusinessAnthropologyArchitectureVisual artsLawComputer scienceArtArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

The rise of malls in China raises questions about their roles as public spaces in Chinese cities. This article proposes the concept of everyday space of publicness to trace contextually sensitive ways that urban inhabitants make the mall a space for public life. The making of everyday space of publicness is evidenced using data from ethnographic fieldwork conducted in an inner-city open-air mall in Beijing. I demonstrate how the mall becomes an everyday space of publicness across three aspects: spontaneous social activities, cooperative practices of regulation, and users' interpretations of their mall experiences. Centering on mall users' everyday experiences and interpretations, these accounts offer nuanced insights into the dynamic relationship between urban spaces and publicness, and contribute to understanding the lived dimension of Chinese urbanism.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.071
GPT teacher head0.279
Teacher spread0.208 · 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