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Record W2142054052 · doi:10.1177/0042098011422574

The Arts and Local Economic Development: Can a Strong Arts Presence Uplift Local Economies? A Study of 135 Canadian Cities

2011· article· en· W2142054052 on OpenAlexaboutno aff
Mario Polèse

Bibliographic record

VenueUrban Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsEconomic geographyContext (archaeology)Local economic developmentGeographyRegional scienceEconomicsEconomyEconomic growthPolitical science

Abstract

fetched live from OpenAlex

The paper looks at arts-related employment in 135 Canadian urban areas over 35 years (1971–2006), successively examining location patterns, co-location with knowledge-rich industries and impacts on employment growth. Arts-related employment is found to be highly concentrated in the very largest urban centres, with no indication of change. Smaller places with particular attributes (attractive natural setting, proximity to large urban centres) are increasingly successful in attracting arts-related activities, but this is not necessarily associated with stronger employment growth or the development of knowledge-rich industries. Evidence of co-location with knowledge-rich industries is weak, but stronger for larger cities. No consistently significant relationship exists with employment growth. This holds true for all cities, irrespective of size. If a synergy exists between the arts and local development, the paper concludes, it is limited to specific industries and only operates in the context of large cities.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.010
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.098
GPT teacher head0.282
Teacher spread0.184 · 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 designObservational
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

Citations43
Published2011
Admission routes1
Has abstractyes

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