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Record W2023414998 · doi:10.1002/meet.2009.1450460389

Documenting and researching the performing arts

2009· article· en· W2023414998 on OpenAlexaff
Francesca Marini

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThe artsDocumentationPerforming artsSection (typography)Context (archaeology)Theme (computing)Visual artsArts in educationArts administrationComputer scienceSociologyWorld Wide WebHistoryArt

Abstract

fetched live from OpenAlex

Abstract This poster addresses documentation of and research in the performing arts. The discussion is based on research conducted by the author in recent years and currently under way, and on other sources. The poster contains: a brief definition and explanation of performing arts; a section on how performing arts materials are created; a section on how the performing arts are documented; a brief discussion of the characteristics of information in the performing arts context; and a section on the use of performing arts materials for research purposes, with a specific focus on theatre scholars and their information behavior. This poster addresses the topic of information created by or related to the performing arts, which is complex and dynamic. This topic is relevant to the overarching conference theme, and related to two of the suggested topics: “Information behavior in diverse contexts” and “Knowledge management in diverse contexts.”

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)0.013
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0050.006
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0330.008

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 head0.019
GPT teacher head0.274
Teacher spread0.256 · 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.

Study designQualitative
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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the American Society for Information Science and TechnologySame topicTheatre and Performance StudiesFrench-language works237,207