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Record W4380874512 · doi:10.3138/ctr.129.016

Shared Histories and Collective Stories

2007· article· en· W4380874512 on OpenAlexvenueno aff
Heidi Bickis

Bibliographic record

VenueCanadian Theatre Review · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)NarrativeStorytellingMeaning (existential)Style (visual arts)Action (physics)AestheticsOrder (exchange)HistoryCollective memorySociologyVisual artsLiteratureEpistemologyArtComputer scienceLawPolitical science

Abstract

fetched live from OpenAlex

The assorted collection of individual plays reviewed here covers a range of subjects and styles. Despite their many differences, however, there are two significant and overlapping themes that provide a framework with which to work. The past is one theme that plays a crucial role in many of these plays. Journeys are taken back into history and memories of the past haunt the present; both of these emphasize the way history shapes multiple generations. Revisiting the past is a means of making amends or is an attempt at reconciliation with past horrors in order to make some sense of the world or of oneself. A secondary theme, which is certainly connected to the first, has more to do with the plays’ style. Several of the plays tell of shared histories or a community story and make use of an ensemble method of storytelling and performance to bring these collective narratives to the stage. For all these plays, the significance of sound is apparent. The addition of music and song and the incorporation of a range of sound effects both add multiple layers of meaning to the text and action onstage.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.032
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0130.027
Scholarly communication0.0120.011
Open science0.0030.012
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.031
GPT teacher head0.240
Teacher spread0.209 · 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
Published2007
Admission routes1
Has abstractyes

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