MétaCan
Menu
Back to cohort
Record W7036921269

'Dear Friend, I Can No Longer Hear Your Voice' at Koffler Centre for the Arts, Toronto.

2023· other· en· W7036921269 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of the Arts London Research Online (University of the Arts London) · 2023
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionSiren (mythology)Public historyPerformance artSound (geography)
DOInot available

Abstract

fetched live from OpenAlex

SIREN was a exhibition by the Toronto-based interdisciplinary artist nichola feldman-kiss, which I was invited to contribute to by screening my film 'Dear Friend, I Can No Longer Hear Your Voice' (made originally for a solo exhibition at the Sir John Soane's Museum London). The overall exhibition and events were curated by Karen Alexander on concepts of diaspora, migration and displacement, the paradox of national boundaries and borders within an ecology of elemental flows. Alexander intended that in presenting Dear Friend... alongside eldman-kiss's work SIREN, ideas of on grief, keening, the relationship of the moving image to experimental approaches to sound and voice, especially female experiences of keening and song would become visceral and could be reflected upon. Dear Friend was presented twice by Alexander for a public event, along with a public discussion with Canadian cultural historian and curator Dr. Michael J. Prokopow responding to the work in March 2023 at the Koffler Centre for the Arts, Toronto, Canada. See also https://ualresearchonline.arts.ac.uk/id/eprint/20317/

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)0.000
metaresearch head score (Gemma)0.001
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 score0.596
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4490.115

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 head0.047
GPT teacher head0.253
Teacher spread0.205 · 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 venueUniversity of the Arts London Research Online (University of the Arts London)Same topicColeoptera Taxonomy and DistributionFrench-language works237,207