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Record W2082596430 · doi:10.1080/13562570802515184

Engineering the Northern Bohemian: Local Cultural Policies and Governance in the Creative City Era

2008· article· en· W2082596430 on OpenAlexaffabout
Jonathan Paquette

Bibliographic record

VenueSpace and Polity · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsLaurentian University
Fundersnot available
KeywordsThe artsCultural policyMetropolitan areaEnthusiasmCorporate governancePopularityNarrativeCreative cityTheme (computing)Political scienceSociologyCreative industriesPublic administrationEconomic growthCreativityEconomicsGeographyManagementLaw

Abstract

fetched live from OpenAlex

This paper addresses the transformations of local cultural governance following the popularisation of the creative city thesis. While the economic impact of the arts in urban settings has been a topic of great interest in recent years and an amply documented theme, little is known about the consequence of such development knowledge and practice on the local cultural policy arena where it takes roots. Moreover, given the popularity and the enthusiasm for such strategies within municipal governments, we have seen a growing tendency to implement the creative city strategy and to formulate cultural policies that follow it in rural and smaller communities which are quite different from the more extensively documented urban and metropolitan cases. Through case studies of three cities in Northern Ontario (Canada), we can identify a number of changes in cultural governance and policy logics. Overall, the creative city narrative appears to be detrimental to typical arts advocacy in smaller communities since it leads to the domestication of the arts.

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)0.003
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.020
Scholarly communication0.0070.003
Open science0.0010.007
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 head0.033
GPT teacher head0.270
Teacher spread0.238 · 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

Citations17
Published2008
Admission routes2
Has abstractyes

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