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Record W2034308365 · doi:10.1177/0042098009103856

Geographies of Displacement in the Creative City: The Case of Liberty Village, Toronto

2009· article· en· W2034308365 on OpenAlexafffundabout
John Paul Catungal, Deborah Leslie, Yvonne Hii

Bibliographic record

VenueUrban Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersCentre for Addiction and Mental Health
KeywordsPrecinctCreative cityTourismPoliticsNeighbourhood (mathematics)Creative industriesSociologyWork (physics)Tourist attractionEconomic geographyEconomyPolitical scienceEconomic growthLawCreativityGeographyEconomicsEngineering

Abstract

fetched live from OpenAlex

Creative industries are increasingly associated with employment, tourism and the attraction and retention of talent in economic development discourse. However, there is a need to foreground the interests involved in promoting the creative city and the political implications of such policies. This paper analyses new industry formation in Liberty Village—a cultural industry precinct in inner-city Toronto, Canada. The focus is on the place-making strategies at work in constructing Liberty Village. In particular, the paper explores a series of displacements associated with creative districts, focusing on three scales in particular—the level of the city, the neighbourhood and the precinct itself. An examination of these displacements foregrounds the contested nature of the creative city script.

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)0.000
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 score0.054
Threshold uncertainty score0.309

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0180.013
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.058
GPT teacher head0.347
Teacher spread0.289 · 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

Citations173
Published2009
Admission routes3
Has abstractyes

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