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Record W2124842280 · doi:10.22230/cjc.2005v30n2a1417

Toronto’s Cultural Renaissance

2005· article· en· W2124842280 on OpenAlexaffvenueabout
Barbara Jenkins

Bibliographic record

VenueCanadian Journal of Communication · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsThe RenaissanceBoomCultural policyContext (archaeology)ReputationCultural tourismTourismCultural capitalPolitical scienceNationalismCompetition (biology)Cultural nationalismCultural identityEconomySociologyPolitical economySocial scienceHistoryTourism geographyEngineeringLawEconomicsArchaeologyPolitics

Abstract

fetched live from OpenAlex

Toronto is experiencing a building boom, with eight major cultural construction projects in the works. These new monuments, part of what the City of Toronto calls its “Cultural Renaissance,” are intended to bolster the city’s reputation as an international economic and cultural capital. Albeit architecturally important, these buildings are better understood in the context of contemporary patterns of global economic competition and the changing role of culture in capitalist production. They also assert national identity and reflect a reorientation of Canadian cultural policy. This paper analyzes Toronto’s “Cultural Renaissance” in light of changing cultural policies at the municipal, provincial, and federal levels, examining the role these new buildings will play in terms of promoting cultural tourism, city “branding,” and nationalism.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.004
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.057
GPT teacher head0.315
Teacher spread0.258 · 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

Citations73
Published2005
Admission routes3
Has abstractyes

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