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Record W2986879533 · doi:10.1007/s10465-019-09311-9

Breaking Free: One Adolescent Woman’s Recovery from Dating Violence Through Creative Dance

2019· article· en· W2986879533 on OpenAlexafffund
Indrani Margolin

Bibliographic record

VenueAmerican Journal of Dance Therapy · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of Northern British Columbia
FundersVancouver Foundation
KeywordsDancePsychologyThe artsHealth psychologyMental healthPsychotherapistSocial psychologyDevelopmental psychologyVisual artsPublic healthMedicineArt

Abstract

fetched live from OpenAlex

Abstract Dating violence against adolescent women can devastate their health and long-term quality of life. While high school programs have been developed to address this worldwide epidemic, somatic antidotes are still not widely utilized despite evidence from the psychophysiology of relational violence trauma that there is an inextricable link between the body and mind and effective recovery requires a holistic approach. Creative dance, derived from dance education, can support female adolescent trauma victims of dating violence to reconnect with physical, mental, and emotional experiences that were severed during traumatic exposure. This qualitative arts-based case study narratively explores one adolescent woman’s experience of creative dance as an intervention for survivors of dating violent relationships. Conceptually, I draw from dance education, Authentic Movement, and Amber Gray’s Restorative Movement Psychotherapy. A feminist lens is utilized in an attempt to address calls to action from previous DMT researchers to tackle oppressive structural forces and increase activism in dance/movement therapy. Findings show that inner-directed dance can therapeutically facilitate restoration after trauma by recovering the social engagement system and decision-making capacity, reducing social isolation, and increasing bodily self-awareness, and self-esteem.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.033
GPT teacher head0.276
Teacher spread0.243 · 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 designOther design
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

Citations20
Published2019
Admission routes2
Has abstractyes

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