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Record W3109006660 · doi:10.1080/14647893.2020.1853693

May I have this dance: examining a community based dance program for people living with Parkinson’s disease

2020· article· en· W3109006660 on OpenAlexafffund
Julia Brook, Amy Booth

Bibliographic record

VenueResearch in Dance Education · 2020
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDancePsychologySittingDance educationInterpersonal communicationClass (philosophy)Interpersonal relationshipDance therapySpace (punctuation)Variety (cybernetics)Session (web analytics)PedagogySocial psychologyVisual artsMedicineAdvertising

Abstract

fetched live from OpenAlex

This case study examined the contents and experiences of people participating in a weekly leisure dance class geared towards people with Parkinson’s disease. Using critical geragogy as a conceptual framework, we examine how the conditions of this program support lifelong learning through both the content and the learning environment. Participants performed a variety of dances in seated and standing positions. The class began with a seated warm up followed by standing exercises that eventually moved thorough space. Each session by concluded by standing or sitting in a circle where they connected with one another through a dance-based interaction. This time of physical interaction honoured and supported peer connections. Interpersonal relationships were also enriched in the ‘in-between times’ of sessions, such as the conversations before and after class. Findings from this research demonstrate how designing an accessible environment allowed for participants to move in new, unimagined ways. It also facilitated a positive space for people to feel beautiful and to meet other people who are going through similar experiences.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.060
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.217
GPT teacher head0.454
Teacher spread0.236 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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