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Record W4237643238 · doi:10.3138/tric.40.1_2.1

Introduction: Festivals

2019· article· en· W4237643238 on OpenAlexvenueaboutno aff
Ric Knowles

Bibliographic record

VenueTheatre Research in Canada · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsMusic festivalTourismDestinationsGeographyAsideVisual artsHistoryArchaeologyArt

Abstract

fetched live from OpenAlex

In Canada, as elsewhere, “the festivalization of culture” proceeds apace (Bennett et al). Even setting aside the ubiquitous music, film, and cultural festivals that have sprung up like mushrooms—not to mention mushroom festivals themselves (such as the “Fungus Among Us” Festival in Whistler, B.C.)—from the Sound Symposium in St. John’s to the Victoria Fringe Festival, and from the Island Unplugged festival on Pelee Island (Canada’s southernmost point) to the Alianait Arts Festival in Iqaluit, Nunavut, festivals dot the theatre and performance landscape in the land now called Canada. Across the country they turn small towns into tourist destinations and urban centres into “festival cities” (see Johannson, Thomasson). In editing the Cambridge Companion to International Theatre Festivals I compiled a list of over forty international theatre, performance, and multi-arts festivals in Canada, a list that does not include music or sound, circus or visual arts festivals, nor does it include the various Shakespeare festivals (from the “Shakespeare by the Sea” festivals on the east coast to Bard on the Beach in BC), the big repertory seasons at Stratford and Niagara-on-the-Lake, or the many festivals such as the peripatetic Magnetic North that have no international component. In addition to all of these, there are twenty-one Canadian members of the Canadian Association of Fringe Festivals (along with nine U.S.-based members), not including other “rogue” fringes.

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)0.000
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 score0.503
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.397
Teacher spread0.317 · 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

Citations2
Published2019
Admission routes2
Has abstractyes

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