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Record W4390898523 · doi:10.7202/1108274ar

XO (Expanded Opera). Une cartographie de la scène reconfigurée par les technologies

2023· article· fr· W4390898523 on OpenAlexvenueno aff
Olivier Asselin

Bibliographic record

VenueRevue musicale OICRM · 2023
Typearticle
Languagefr
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhysics

Abstract

fetched live from OpenAlex

Historiquement, les arts de la scène sont définis par la rencontre entre des artistes et un public, dans un lieu précis, pour un temps donné. Ils présupposent ainsi une production et une réceptionsimultanées, une communautécoprésente. Mais aujourd’hui, la scène ne va plus de soi, pour toutes sortes de raisons historiques – surtout technologiques. Je me propose de faire ici l’ébauche d’une cartographie de cette scène reconfigurée par les technologies. L’objectif est d’esquisser un cadre théorique, avec une portée descriptive – qui permette d’analyser les oeuvres – mais aussi une portée prospective – qui permette d’envisager d’autres possibilités.

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 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: Other · Consensus signal: Other
Teacher disagreement score0.349
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3490.075

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 head0.051
GPT teacher head0.300
Teacher spread0.250 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevue musicale OICRMSame topicVirtual Reality Applications and ImpactsFrench-language works237,207