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Record W2979346629 · doi:10.1080/17510694.2019.1673121

From clothing to culinary industries: creativity in the making of place

2019· article· en· W2979346629 on OpenAlexaboutno aff
Himasari Hanan, Dwitya Hemanto

Bibliographic record

VenueCreative Industries Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityQuarter (Canadian coin)Creative industriesCreative CitiesClothingGovernment (linguistics)Creative citySociologyMarketingCompetition (biology)Economic growthPublic relationsEconomic geographyBusinessPolitical scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Creative clusters in many Western and Asian cities are predominantly established through policy-making and the involvement of government and private institutions. This paper investigates another way creative industries emerge, whereby individual initiatives of creative young people transform a colonial residential quarter into creative clusters. The creativity of young people has brought life and diversity to a mono-functional urban area by seizing new opportunities for small-scale business practices. The paper is based on a field survey and mapping of 80 clothing and culinary industries at Trunojoyo quarter in Bandung, Indonesia, that contributed to the nomination of Bandung as UNESCO City of Design in 2015. The young people of Bandung exhibit tactical strategies in the emergence of creative clusters and exercise informal processes and social networks as catalysts for growing creative industries. They reveal how youthful energy and creativity within everyday life brings about something that is rational and practical in creating an experiential place and making an historical quarter into a place of high economic performance.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.349
Teacher spread0.270 · 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.

Study designNot applicable
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

Citations13
Published2019
Admission routes1
Has abstractyes

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