MétaCan
Menu
Back to cohort
Record W4240831697 · doi:10.32920/ryerson.14667054

The pas de trois of disability, dance and social work: dance/movement therapy as point of access for recreational dance

2021· preprint· en· W4240831697 on OpenAlexaff
Geneviève Elitha Margaret Roots

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsCarleton UniversityToronto Metropolitan University
Fundersnot available
KeywordsDanceRecreationParallelsPsychologySociologyDance therapyVisual artsPolitical scienceArtEngineering

Abstract

fetched live from OpenAlex

Individuals with disabilities are left out of recreational programs at a much higher rate than individuals with no disabilities. Seeking to rid barriers created by inaccessible recreational dance spaces, dance/movement therapy (DMT) offers a potential solution. This research explores how DMT can inspire a model for accessible recreational dance spaces for individuals with varying abilities, how this therapeutic practice can translate into a recreational dance atmosphere, and the role of social workers herein. The research takes the form of a content analysis via hermeneutic phenomenology of a six-week DMT-inspired pilot program developed by the researcher, and is informed by critical disability and structural social work theories. Findings highlight the parallels between DMT and recreational dance, making possible their fusion to create a space for ‘everyone and anyone’, and emphasize a social work presence. A logic model resulted, guiding how accessible recreational dance programs may be designed, based on DMT.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0050.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.106
GPT teacher head0.385
Teacher spread0.279 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicDiversity and Impact of DanceFrench-language works237,207