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Record W4311715138 · doi:10.31182/cubic.2022.5.45

On the Question of Objects –“Imagined Field from the Deconstruction of an Apparatus”

2022· article· en· W4311715138 on OpenAlexfundno aff
Ben Bogart

Bibliographic record

VenueCubic Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsnot available
FundersTRIUMF
KeywordsAmbiguityRealismDeconstruction (building)AbstractionField (mathematics)Boundary (topology)EpistemologyComputer scienceSociologyAestheticsArtificial intelligencePhilosophyMathematicsPure mathematicsEngineering

Abstract

fetched live from OpenAlex

This text is an artistic companion to the accompanying collages where complexity, ambiguity, emergence, and abstraction are emphasised. Through artistic practice I investigate the primacy of objects and their relations. Consistent with Barad’s Agential Realism, objects are constructed through their relations. This conflicts with a capitalist and colonialist view where objects pre-exist relations and are that which can be extracted, used and/or consumed. The images herein are composed from fragments of photographs taken at a particle accelerator facility where fragment boundaries are constructed by a machine learning algorithm. Images are composed by placing fragments according to their relationships using a second machine learning algorithm that emphasises some boundaries and dissolves others. These layers of boundary-making are analogous to cognitive processes where the objects of thought are proxies for complex relations. This is the crux of our contemporary era; social and material complexity cause us to attend to objects at the detriment of the systems that allows those objects to be.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.329
Teacher spread0.302 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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