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Record W3166786729 · doi:10.3138/tric.42.1.f03

Dreaming New Worlds: Katz and Kerr in the 1970s

2021· article· fr· W3166786729 on OpenAlexaffvenueabout
Mary Margaret Kerr, A. Newton

Bibliographic record

VenueTheatre Research in Canada · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article porte sur l’amitié et la relation de travail du metteur en scène Stephen Katz et de la scénographe Mary Kerr, qui ont créé ensemble neuf productions novatrices entre 1970 et 1976. Une brève entrée en matière présente les trajectoires professionnelles de Katz et Kerr, deux célèbres artistes de théâtre au Canada, tout en situant Katz dans le contexte d’artistes dont la vie a été écourtée par le SIDA. Ce préambule est suivi d’un entretien avec Kerr sur les aspects uniques de la synergie créative qu’elle partageait avec Katz, de même que les spécificités d’une collaboration qui remonte à l’époque où les deux artistes étudiaient à l’University of Toronto. Kerr parle de la première expérience professionnelle de l’équipe au Tarragon Theatre de Toronto, de même que des expériences vécues plus tard dans des théâtres à plus grande échelle comme le Vancouver Playhouse et le festival Shaw. Elle reflète ensuite sur la relation de collaboration/travail idéale entre artistes œuvrant à la mise en scène et à la scénographie, sur la formation des artistes en théâtre et sur la myriade d’effets qu’ont eus sur son travail avec Katz le milieu culturel expérimental et le radicalisme de la fin des années 1960 et du début des années 1970.

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)0.005
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 score0.777
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0250.042
Scholarly communication0.0140.012
Open science0.0010.011
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.086
GPT teacher head0.317
Teacher spread0.231 · 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

Citations0
Published2021
Admission routes3
Has abstractyes

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