MétaCan
Menu
Back to cohort
Record W283790263

Le son dans l'art contemporain canadien = Sound in Contemporary Canadian Art

2003· book· fr· W283790263 on OpenAlexaboutno aff
Nicole Gingras, Jocelyn Robert, R. Murray Schafer, Raymond Gervais, Christof Migone, Gordon Monahan, Michèle Waquant, Colin Griffiths, Hildegard Westerkamp, Steve Heimbecker, Gayle Young, Nicolas Reeves, Hélène Prévost, Tagny Duff, Diana Burgoyne, Tom Sherman

Bibliographic record

VenueÉditions Artextes eBooks · 2003
Typebook
Languagefr
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsnot available
Fundersnot available
KeywordsSilenceSound (geography)Active listeningVisual artsSound artDocumentationThe artsArtPerformance artSociologyArt historyAestheticsAcousticsCommunicationComputer science
DOInot available

Abstract

fetched live from OpenAlex

Stemming from a research residency at Artexte Information Centre, Gingras has assembled this anthology of texts by 18 artists and authors, creating a forum for a discussion of sound in the visual and media arts in Canada from 1980 to the present. Focusing on a specific work or artist, or while discussing their own practice through writing or in interview, the authors reflect on different experiences of listening and hearing, on sound objects and acoustic bodies, broadcasting devices, interdisciplinarity, and the role of silence. Gingras’ essays encompass the artists who inspired this project, as well as issues involved in the creating, dissemination, reception and documentation of works of sound. The accompanying audio CD contains various sound recordings by 16 artists. Gingras’ texts in French and English; other texts in the language of the author. Biographical notes on the authors and on the artists represented on the CD. Circa 75 bibl. ref.

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 score0.089
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0290.017
Scholarly communication0.0120.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.001

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 head0.048
GPT teacher head0.257
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
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

Citations2
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueÉditions Artextes eBooksSame topicArtistic and Creative ResearchFrench-language works237,207