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Record W2996083675 · doi:10.53841/bpssex.2016.7.2.63

Through thick and thin: Storying queer women’s experiences of idealised body images and expected body management practices

2016· article· en· W2996083675 on OpenAlexaboutno aff
Jen Rinaldi, Carla Rice, Andrea LaMarre, Karleen Pendleton Jiménez, Elisabeth Harrison, May Friedman, Deborah McPhail, Margaret Robinson, Tracy Tidgwell

Bibliographic record

VenuePsychology of Sexualities Review · 2016
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsQueerNegotiationResistance (ecology)EmpathyGender studiesThe artsSociologyIdentity negotiationAestheticsPsychologyVisual artsSocial psychologyArtSocial science

Abstract

fetched live from OpenAlex

In this study we examine how discourses of obesity and eating disorders reinforce cissexist and heteronormative body standards. Sixteen queer women in Canada produced autobiographical micro-documentaries over the course of two workshops. We identified three major themes across these films: bodily control, bodies as sites of metamorphosis, and celebration of bodies. Such films can be memorable, cultivate empathy, disrupt misunderstanding of queer bodies, and inform medical practice. Our analysis suggests that research and policy on ‘disordered’ bodies must better account for how people negotiate discourses around body shape and size, how shaming is internalised, how regulation can function as resistance, and how variant bodies can be embraced, desired, and celebrated. Community-grounded, arts-based research points to new ways of gathering and producing knowledge.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.064
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.021
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.119
GPT teacher head0.512
Teacher spread0.392 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations15
Published2016
Admission routes1
Has abstractyes

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