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Record W4380926129 · doi:10.3138/ctr.136.019

Boom or Bust? A Survey of Theatre for Young Audiences Activities in Alberta

2008· article· en· W4380926129 on OpenAlexvenueaboutno aff
Nicholas Hanson

Bibliographic record

VenueCanadian Theatre Review · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBustBoomCensusBaby boomWork (physics)GeographyStormEconomic historyHistoryDemographic economicsDemographyEconomyEconomic growthSociologyMeteorologyEngineeringEconomicsPopulation

Abstract

fetched live from OpenAlex

Data from the 2006 Census confirmed some obvious realities about recent demographic trends in Alberta: the province was the fastest growing in Canada, with the youngest median age and among the highest percentage of people under the age of fifteen (Statistics Canada). Between the robust economy and the high concentration of young families, one could logically presume that the conditions were in place for Alberta to become a highly fertile landscape for Theatre for Young Audiences (TYA) activities. Of course, a dynamic boom in one industry can trigger a catastrophic bust in another — How have TYA practitioners in Alberta weathered the storm of rapid provincial expansion? This article aims to explore how Alberta's boom has affected TYA activities; as well, this piece surveys a few general TYA trends across the province and highlights some of the exceptional work presented by regional companies.

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 score0.021
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.067
GPT teacher head0.264
Teacher spread0.198 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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