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Record W1978430432 · doi:10.3828/idpr.2011.18

The emerging cultural economy in Chinese cities: early dynamics

2011· article· en· W1978430432 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.

Bibliographic record

VenueInternational Development Planning Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDynamismBeijingEconomic geographyConsumption (sociology)Metropolitan areaHandicraftProduction (economics)EconomyEconomic growthChinaBusinessPolitical scienceEconomic systemGeographyEconomicsSociology

Abstract

fetched live from OpenAlex

In recent years, Chinese national and municipal governments have emphasised growth of the urbancultural economy, aiming to achieve 15–20% economic output share in the largest metropolitan regionsby 2020. There is wide variation in policy and physical approaches to growing the urban culturaleconomy, explored in Beijing, Shanghai and Foshan. Differing physical models of cultural economicdevelopment are explored: formal arts facilities, cultural preservation based redevelopment, high-techcreative zones and bottom-up clusters. Key drivers are discussed and tensions are explored – betweenproduction and consumption spaces, top-down and bottom-up approaches and between authenticity andgentrification. The authors conclude the sector is becoming a major shaper of physical form, affirm the keyrole the private sector has played and assert that bottom-up districts, driven by the producers themselves,have been among the most successful. Spatial dynamism is emphasised, particularly the emergence ofnew cultural production spaces on the urban periphery, and the evolution in the urban core of formerproduction spaces into new cultural consumption environments.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.340
Teacher spread0.273 · 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