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Record W7027594915

Curious & curiouser

2021· other· en· W7027594915 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHaikuSound (geography)ChoirMovement (music)PoetryActive listeningSculptureSuite
DOInot available

Abstract

fetched live from OpenAlex

Curious & Curiouser is a dual-part project where listening happens in two different “spaces”: the choral composition and in an artist book. Each uses as source material haiku that the artist discovered on her walks through the industrial waterfront area of East Vancouver; the haiku are engraved on red dog tags and nailed to the wooden power poles she encountered along her path. The haiku texts are translated into two spatial forms that make visible the patterns of order in music, braiding visuality with aurality. The choral suite is a kaleidoscopic word painting—a sound sculpture in five movements—staging the sight of sound through choreographic gesture, movement and theatre; a poetry of motion. Composed as a postlude to the suite, the artist book is a part-score for performing listening, the graphic scores and listening events map sound out of sight—a question of how we hear what we see.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.364
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.001
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6360.325

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 head0.017
GPT teacher head0.228
Teacher spread0.210 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2021
Admission routes1
Has abstractyes

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