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Record W4244732271 · doi:10.1162/dram_a_00567

Who Knows

2016· article· en· W4244732271 on OpenAlexaboutno aff
Tim Etchells

Bibliographic record

VenueTDR/The Drama Review · 2016
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsRepetition (rhetorical device)VerbState (computer science)Set (abstract data type)Need to knowLinguisticsSimple (philosophy)JargonHistoryAestheticsComputer scienceArtEpistemologyPhilosophyComputer securityAlgorithmProgramming language

Abstract

fetched live from OpenAlex

Who Knows (2014) is an installation comprising 12 pairs of colored neon phrases, modeled on the declension of the verb “to know” which moves though a simple set of variations and reversals. Like much of Etchells’s work Who Knows reveals a fascination with rules and systems in language and in culture, especially in the way these structures are both productive and constraining. The work’s repetition and recombination of individual phrases — “I know,” “You know,” “We know,” “They know”— produces a playful paranoia, nodding to the prescient topics of state and corporate surveillance, snooping and data-harvesting. Who Knows was first shown at Contemporary Art Gallery, Vancouver, as part of a collaboration with the PuSh Festival.

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)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.128
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1280.035

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 head0.020
GPT teacher head0.250
Teacher spread0.229 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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