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Record W3191436871 · doi:10.1145/3465624

Reversal, Disconnect, and Proposition

2021· article· en· W3191436871 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the ACM on Computer Graphics and Interactive Techniques · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Technology, and Culture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExploitNormativeBig dataPropositionEveryday lifeData scienceSociologyPoliticsComputer scienceEpistemologyAestheticsHuman–computer interactionMedia studiesPolitical scienceComputer securityArtLawData mining

Abstract

fetched live from OpenAlex

This paper examines the potential countertactics of contemporary interactive media art to interrogate the data-mining practices that encode the everyday and exploit user data in the big data economy. It argues that noise is the "other" of information, a way to counter the operation of turning the world into data commodities. Through a Brechtian methodology informed by philosophy and critical theories of media and technology, the paper suggests that amplifying the "noise" of the digital media assemblages deviates from their everyday normative functions and estranges our relationship to them, inviting critical ways of understanding, relating to, and engaging these ubiquitous systems. All three noted artworks destabilize the protocols of data-mining to examine data politics. Specifically, the paper looks at three different tactics that amplify the "noise" of digital culture in different ways: reversing roles, disconnecting, and proposing viable alternatives.

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.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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