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Record W4206755766 · doi:10.1371/journal.pone.0247651

Dancing in a culture of disordered eating: A feminist poststructural analysis of body and body image among young girls in the world of dance

2022· article· en· W4206755766 on OpenAlexafffundabout
Nicole Doria, Matthew Numer

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchNova Scotia Health Research Foundation
KeywordsDanceInfluencer marketingEating disordersDisordered eatingGender studiesPsychologyHuman physical appearanceSociologyDevelopmental psychologyClinical psychologyArtVisual arts

Abstract

fetched live from OpenAlex

Eating disorders among adolescent girls are a public health concern. Adolescent girls that participate in aesthetic sport, such as dance, are of particular concern as they experience the highest rates of clinical eating disorders. The purpose of this study is to explore the experiences of young girls in the world of competitive dance and examine how these experiences shape their relationship with the body; feminist poststructural discourse analysis was employed to critically explore this relationship. Interviews were conducted across Canada with twelve young girls in competitive dance (14-18 years of age) to better understand how the dominant discourses in the world of competitive dance constitute the beliefs, values and practices about body and body image. Environment, parents, coaches, and peers emerged as the largest influencers in shaping the young dancers' relationship with their body. These influencers were found to generate and perpetuate body image discourses that reinforce the ideal dancer's body and negative body image.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.283
Teacher spread0.264 · 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

Citations24
Published2022
Admission routes3
Has abstractyes

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Same venuePLoS ONESame topicEating Disorders and BehaviorsFrench-language works237,207