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Record W2326392999 · doi:10.1177/1357034x15604030

Bodily Intra-actions with Biometric Devices

2015· article· en· W2326392999 on OpenAlex
Paula Gardner, Barbara Jenkins

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

VenueBody & Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsWilfrid Laurier UniversityOntario College of Art and Design
Fundersnot available
KeywordsEmbodied cognitionSubjectivityRepresentation (politics)NarrativeReductionismMeaning (existential)Process (computing)Cognitive sciencePsychologyBiometricsCommunicationHuman–computer interactionEpistemologyComputer scienceAestheticsArtificial intelligencePhilosophyLinguistics

Abstract

fetched live from OpenAlex

We investigated the interface between biomedia and humans by inviting participants to interact with biometric devices that measured and visualized their body data. At first, they struggled with the alienating and disembodying nature of the devices and the constrained, reductionist representation of data. Through their bodily interactions with these devices, however, participants reframed the data and inserted their bodies into the process of data collection. Drawing on the ideas of Bergson, Grosz, Merleau-Ponty and Bachelard, we argue that by working with their subjectivity in a mediated process of becoming, participants ‘filled in the intervals’ of the visual representations of their bodies to interpret them in ways that marked the duration and meaning of their selves. We conclude that even when presented with artificial representations, individuals convert the representation of the data into narratives inspired by their embodied experience, and the ‘virtual’ pasts of their own lives.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.357
Teacher spread0.259 · 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