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Record W2338999040 · doi:10.1177/2056305116641706

Making the Cut: An Agential Realist Examination of Selfies and Touch

2016· article· en· W2338999040 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

VenueSocial Media + Society · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsKwantlen Polytechnic University
Fundersnot available
KeywordsSelfiePhenomenonRealismAestheticsPresumptionEpistemologySociologyArtVisual artsPhilosophy

Abstract

fetched live from OpenAlex

This article leverages the work of Karen Barad to analyze digital self-imaging research. Drawing on findings from four interviews with avid selfie authors, this article argues that agential realism can provide a rich ontological framework for examining selfies that goes beyond the representational paradigm in some studies of socially mediated digital images. Rather than beginning the study with the presumption that bodies, photos, cameras, and expressed selves are distinct and pre-existing entities that then interact with one another, or touch, selfies here are construed as networked material–discursive entanglements wherein bodies, photos, cameras, and expressed selves are always and already touching. Within this entangled phenomenon, then, this article suggests that what reads as touch (images that grab or repulse/efface) is in a sense the opposite of touch—it is a pulling apart of the entangled phenomenon wherein agential cuts demarcate the desired boundaries of entities like bodies, images, and self. This article further suggests that what makes and doesn’t make the “cut” is not natural but emerges within gendered apparatuses of bodily production.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.864

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 studies0.0010.001
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 head0.096
GPT teacher head0.356
Teacher spread0.260 · 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