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Record W4404676058 · doi:10.7202/1114715ar

Body Modification as Body Art

2024· article· en· W4404676058 on OpenAlexaff
Jessica J. Cameron

Bibliographic record

VenueAtlantis Critical Studies in Gender Culture & Social Justice · 2024
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In this article, I discuss my “anti-aging” body modification practices as body art. The art documents my bodybuilding programs, self-administered neurotoxin (Botox) injections, and skin resurfacing treatments. Susan Pickard (2020) argues that femininity and aging are associated with the abject. She maps the abject and non-abject onto Simone de Beauvoir’s distinction between immanence and transcendence. Because “abjection should always be understood as an element of [...] oppression” (Pickard 2020, 159), my art practice could be read as an anti-feminist, ageist attempt to expel the abject. After offering a counter-argument that positions my practice as feminist, I use Kathy Acker’s (1993) writing on bodybuilding to offer a third reading. Muscles grow when they are worked until failure. This practice of constantly coming up against the body’s limits is a rehearsal for the ultimate failure of the body: death (Acker 1993). If thanatology is the study of death and dying, bodybuilding is autothanatology. My “anti-aging” interventions are similar; they are inevitable failures that cannot stop the aging process. In this way, my practice is a reminder that the body exists in a state of immanence, even while I may attempt to frame my immanence along transcendental terms.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.106
GPT teacher head0.456
Teacher spread0.350 · 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.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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