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Record W2750389359 · doi:10.3138/tric.38.1.11

Ryga, Miss Donohue, and Me: Forty Years of <i>The Ecstasy of Rita</i> Joe in the University

2017· article· en· W2750389359 on OpenAlexvenueaboutno aff
Moira Day

Bibliographic record

VenueTheatre Research in Canada · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipEcstasyMeaning (existential)George (robot)CurriculumPedagogySociologyHistoryPsychologyMedia studiesVisual artsArtPolitical scienceArt historyLawPsychiatry

Abstract

fetched live from OpenAlex

While the seminal role that George Ryga’s 1967 classic, The Ecstasy of Rita Joe, played in igniting the modern Canadian theatre has often been acknowledged, the extent to which its success also constituted a concentrated attack on what Ryga termed the “complacent educator” in 1977, and helped revolutionize the publication and teaching of Canadian plays at the post-secondary level, may have been less well acknowledged. This article, which documents Moira Day’s own forty-year odyssey with the play in the (largely) prairie university classroom as both a student and an instructor, investigates the play’s initial impact on scholarship, publication, curriculum at the post-secondary leve , and some of its ramifications on school and university production and actor training over the 1970 and 1980s. It also deals with the challenges of continuing to teach and interpret the play from the 1990s onward, as new practices and theories have continued to alter its meaning, and considers why this odd, iconoclastic text, despite its flaws, continues to fascinate us fifty years after its initial production.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.116
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0250.022
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.279
Teacher spread0.216 · 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 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
Published2017
Admission routes2
Has abstractyes

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