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Record W4402734068 · doi:10.1017/s0026749x2400009x

Tunnels of power: The cultural politics of the Beijing subway

2024· article· en· W4402734068 on OpenAlexaff
Cheng Li, Yanjun Liu

Bibliographic record

VenueModern Asian Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsBeijingPoliticsPower (physics)Political scienceChinaBusinessLawPhysics

Abstract

fetched live from OpenAlex

Abstract This article investigates the cultural politics of the Beijing subway. Drawing on diverse sources, we trace the evolution of the subway over the last half-century to reveal that it transcends its fluctuating, time-specific practicalities to serve as a potent conduit through which the Chinese state consistently shapes subjecthood. The article begins with the subway’s Cold War inception as a military enterprise, spotlighting its deliberate concealment to safeguard the echelons of power and obscure both international and domestic tensions. The second section delves into the subway’s rebirth in the wake of China’s opening-up reform and rapid economic rise, as it transforms into a mobile gallery of political aesthetics that extols China’s cultural heritage and triumphs, cultivating national pride under siege from unleashed market and social forces. The final section dissects the subway’s orchestration of undesirable passengers, sculpting a socioeconomic hierarchy in the city’s commuting system. As a multifaceted prism, the Beijing subway encapsulates a range of covert and overt, pragmatic and aesthetic, and inclusive and exclusive elements in the cultural politics of Chinese infrastructure at large; and it illustrates the sustained centrality of state power in shaping individual subjectivities and defining the cultural and representational significance of Chinese infrastructure, albeit amid growing contestation.

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)0.001
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.014
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.364
Teacher spread0.315 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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