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Record W2781033852 · doi:10.5206/fpq/2017.4.3

Resisting Body Oppression: An Aesthetic Approach

2017· article· en· W2781033852 on OpenAlexvenueno aff
Sherri Irvin

Bibliographic record

VenueFeminist Philosophy Quarterly · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsInjusticeOppressionDehumanizationSocial psychologyPsychologyIdentity (music)AestheticsAttractivenessEconomic JusticeSociologyPolitical science

Abstract

fetched live from OpenAlex

This article argues for an aesthetic approach to resisting oppression based on judgments of bodily unattractiveness. Philosophical theories have often suggested that appropriate aesthetic judgments should converge on sets of objects consensually found to be beautiful or ugly. The convergence of judgments about human bodies, however, is a significant source of injustice, because people judged to be unattractive pay substantial social and economic penalties in domains such as education, employment and criminal justice. The injustice is compounded by the interaction between standards of attractiveness and gender, race, disability, and gender identity. I argue that we should actively work to reduce our participation in standard aesthetic practices that involve attractiveness judgments. This does not mean refusing engagement with the embodiment of others; ignoring someone’s embodiment is often a way of dehumanizing them. Instead, I advocate a form of practice, aesthetic exploration, that involves seeking out positive experiences of the unique aesthetic affordances of all bodies, regardless of whether they are attractive in the standard sense. I argue that there are good ethical reasons to cultivate aesthetic exploration, and that it is psychologically plausible that doing so would help to alleviate the social injustice attending judgments of attractiveness.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.993

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 studies0.0080.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.048
GPT teacher head0.331
Teacher spread0.283 · 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 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

Citations68
Published2017
Admission routes1
Has abstractyes

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