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Record W4224239401 · doi:10.21476/pp.2022.71381

Another Image of Existence

2022· article· en· W4224239401 on OpenAlexaff
Denise Ferreira da Silva, Valentina Desideri, Georg Döcker, Eve Katsouraki

Bibliographic record

VenuePerformance Philosophy · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArts and Performance Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubject (documents)SalonCoronavirus disease 2019 (COVID-19)OntologyPoetryPoliticsPower (physics)Image (mathematics)Sociology2019-20 coronavirus outbreakEpistemologyArtArt historyPhilosophyLiteratureComputer sciencePolitical scienceLawArtificial intelligenceLibrary scienceMedicine

Abstract

fetched live from OpenAlex

Since 2015/2016, Denise Ferreira da Silva and Valentina Desideri have been engaging in a joint practice of so-called Poethical Readings, a device that engages the poetic and the ethical at the limits of the epistemology and ontology of the modern Subject. In this interview, Ferreira da Silva and Desideri provide insight into the singular and theatrical dynamics of Poetical Readings, as well as The Sensing Salon, a format for the collective exercise of Poethical Readings. They consider their practice with respect to the issue of power and the image of existence that undergirds modern politics, suggesting that Poethical Readings partake in the construction of a different image of existence no longer founded on the violent operations of the Subject. Having taken place in the autumn of 2020, that is, in the first year of the COVID-19 pandemic, the interview is framed by and addresses these issues through the discussion of the social ramifications of the corona crisis.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.042
Scholarly communication0.0080.010
Open science0.0010.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.049
GPT teacher head0.221
Teacher spread0.171 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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