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Record W3205473356

In the Modern Age

2017· book· en· W3205473356 on OpenAlexaboutno aff
Kim Solga

Bibliographic record

VenueBloomsbury Academic eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQueen (butterfly)Performance studiesArt historyPoliticsMedia studiesHistoryStrategic studiesSociologyAnthropologyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

List of Illustrations Notes on Contributors Series Preface Editor's Acknowledgements Introduction: The Impossible Modern Age Kim Solga, Western University, Canada 1 Institutional Frameworks: Theatre, State, and Market in Modern Urban Performance Michael McKinnie, Queen Mary University of London, UK 2 Social Functions: Consumers and Producers Nicholas Ridout, Queen Mary University of London, UK 3 Sexuality and Gender: New Stories and New Spaces on the Modern Stage Kirsten Pullen, Texas A&M University, USA 4 The Environment of Theatre: 'Home' in the Modern Age Kim Solga, Western University, Canada and Joanne Tompkins, The University of Queensland, Australia 5 Circulations: Visual Sovereignty, Transmotion, and Tribalography Jill Carter, University of Tornoto, Canada, Heather Davis-Fisch,University of the Fraser Valley, USA and Ric Knowles, University of Guelph, Canada 6 Interpretations: The Stakes of Audience Interpretation in Twentieth-Century Political Theatre Dassia N. Posner, Northwestern University, USA 7 Communities of Production: A Materialist Reading with an Offstage View Christin Essin,Vanderbilt University, USA and Marlis Schweitzer, York University, Canada 8 Genres and Repertoires: Redressing the Nation in Ireland and Japan Michelle Liu Carriger,University of California, Los Angeles , USA and Aoife Monks, Queen Mary University of London, UK 9 Technologies of Performance: Machinic Staging and Corporeal Choreographies Ashley Ferro-Murray, University of California, Berkeley, USA and Timothy Murray, Cornell University, USA 10 Knowledge Transmission: Media and Memory Sarah Bay-Cheng, Bowdoin College, USA Notes Bibliography Index

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.124
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.007
Scholarly communication0.0100.009
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1240.020

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 head0.057
GPT teacher head0.272
Teacher spread0.214 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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