“We are all just humans participating”: the role of an embodied approach, virtual space and artistic media in shaping participants’ experience in a co–design process
Bibliographic record
Abstract
Integrating multiple perspectives is key to successful co-design, yet often hampered by communication gaps arising from different epistemological backgrounds and lived experiences. This challenge is amplified when the design problem centres around experiences that are difficult articulate in words, such as those in Parkinson’s disease (PD). To explore alternative strategies for communication between diverse PD stakeholders, Piece of Mind brought together neuroscientists, performing artists and individuals with lived experience to co-create an interdisciplinary performance grounded in scientific and experiential knowledge. Participants met on Zoom over nine months, in which creative, embodied approaches were used to share scientific concepts, facilitate discussion, and identify key issues for the performance. We built on emergent themes through virtual and in-studio collaborations, culminating in a 45-min filmed and live performance. We conducted semi-structured interviews with a subset of participants regarding their co-design experience and take-aways, to identify elements of process, space and materials contributing to its success. We found that an embodied approach, in virtual space and incorporating multiple artistic media, enabled participants to leave their comfort zones and disciplinary boundaries to engage with one another through curiosity and generosity – and consider how these conditions facilitated disparate starting points to converge towards a common goal.
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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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".