Examining the adaptation of dance for people with Neurodevelopmental Disability: A multiple-methods approach
Bibliographic record
Abstract
Dance has an ableist history that has defined who is a dancer, what dance looks like, and how dance is taught and performed. Dance can also enhance and promote physical and social development for persons with neurodevelopmental disability (NDD) when it is adapted to the capabilities of the individual dancer. However, dance educators are not required to complete training on adapting movement for persons who live with NDD, nor how to create inclusive and adaptive dance environments. I used a multiple methods approach to gain a deeper understanding of how adaptive dance programming and environments may impact dancers who live with NDD (dancers) and to make recommendations for practice. This thesis includes three linked studies. The first study examined the literature specific to adults who live with NDD to determine the characteristics of, and common instructional strategies used in, dance interventions. The study synthesizes the outcome measures used and considers the relationship between outcomes and the characteristics of the dance interventions. The second study considers the perspectives of dancers through semi-structured interviews to better understand both the perspectives and experiences of dancers in dance. The third study used a Hybrid-Delphi technique to gather expert community, dance, and rehabilitation perspectives on adapting dance and dance environments to formulate a set of prioritized recommendations for dance educators.The results of these studies are organized in a manuscript-style thesis. The results of the first study indicated that literature often focuses on reducing or changing of the behaviours and ‘symptoms’ related to NDD. The findings indicated that details of how dance interventions were adapted to dancers’ functional levels and the specific details of interventions were scarce. In the second study the dancers shared that they gained a sense of purpose and belonging, as well as and interpersonal skills that apply to daily life when holistic approaches to dance instruction were used. The third study resulted in the formulation of a comprehensive list of recommendations that prioritizes the perspectives of the dancers and applies to a variety of movement settings. Based on these findings future research will evaluate the dissemination of the findings in the dance community broadly.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.071 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".