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Record W3001198345 · doi:10.3138/ctr.181.003

Applied Theatre Encounters at Canada’s National Holocaust Monument

2020· article· en· W3001198345 on OpenAlexvenueaboutno aff
Belarie Zatzman

Bibliographic record

VenueCanadian Theatre Review · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceThe HolocaustNarrativePerformativityContext (archaeology)Citizen journalismArchitectureVisual artsArtAestheticsSociologyArt historyHistoryArchaeologyLiteratureGender studiesLawPolitical science

Abstract

fetched live from OpenAlex

The stark, slanting, raw concrete walls of Landscape of Loss, Memory and Survival, reveal the essential performativity of Canada’s new National Holocaust Monument (NHM). Designed by architect Daniel Libeskind and opened in Ottawa in September 2017, the unexpected angles of the monument’s towering walls form six triangular “volumes” that constitute a deconstructed and elongated Star of David. Belarie Zatzman frames the NHM’s architecture, itself, as the foundation for conceptualizing an applied theatre project as she speculates about what it might mean to respond to the Holocaust from the present, in a specifically Canadian context. She draws on Rothberg’s concept of multidirectional memory as an approach for gathering participants’ multiple narratives as well as multiple communities’ responses to the Shoah. For Zatzman, the promise and challenge of applied theatre lies in the possibility of interacting with history, beyond passively consuming historiographic narratives. Thus, the article asks, how might applied theatre processes help shape our encounter with history and memory at the NHM as a performative, participatory, and pedagogical practice?

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)0.000
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: none
Teacher disagreement score0.896
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.030
GPT teacher head0.214
Teacher spread0.183 · 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
Published2020
Admission routes2
Has abstractyes

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