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Record W2066863660 · doi:10.1080/15299732.2012.757714

Exposing Shame in Dancers and Athletes: Shame, Trauma, and Dissociation in a Nonclinical Population

2013· article· en· W2066863660 on OpenAlexaff
Paula Thomson, S. Victoria Jaque

Bibliographic record

VenueJournal of Trauma & Dissociation · 2013
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsThe Wilson CentreYork University
Fundersnot available
KeywordsShamePsychologyDissociativeClinical psychologyDissociation (chemistry)Dissociative Experiences ScalePopulationDissociative disordersPsychiatrySocial psychologyCognitionMedicine

Abstract

fetched live from OpenAlex

The relationship between shame, past traumatic events, and dissociation in a nonclinical university and community sample of pre-professional/professional dancers (n = 140) and recreational/competitive athletes (n = 99) was investigated in this cross-sectional study, which was approved by an institutional review board. Participants completed 3 self-report measures (i.e., the Dissociative Experiences Scale, Internalized Shame Scale, Traumatic Events Questionnaire), and the analyses included correlation, multivariate analysis of variance, and a series of regression analyses. The investigation indicated that dancers had increased shame and dissociation in comparison to athletes, and males had more traumatic experiences and increased dissociation relative to females. In the regression analyses, being a dancer, traumatic experiences, and shame predicted dissociation. Clinical recommendations include integrating shame treatment with dissociative-disordered patients and noting that dancers may need more psychological skill training to manage shame and dissociation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.302
Teacher spread0.285 · 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.

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

Citations27
Published2013
Admission routes1
Has abstractyes

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