Museum as a Mutual Learning Space for Artists with Intellectual and Developmental Disabilities and University Students
Bibliographic record
Abstract
Using a university museum as a mutual learning space, guided by the core principles of multivocality and inclusive arts practice, six adult artists with intellectual disability and 16 undergraduate students collaborated to plan a public art exhibition. In this article, we describe the facilitation of the 6-week group process with artists with intellectual disability who have varied cognitive and communication abilities, to curate their own stories and prepare for a public art exhibition, and students to gain field experiences as community art educators, working with a community artist group. By using the expressive arts as a core communicative tool, artists with intellectual disability led small group conversations about a shared life topic of grief with university undergraduate students. In return, the students facilitated the curating process for the artists with intellectual disability, being able to transform their personal bereavement stories into a public exhibition. Evaluation of artefacts, observations and survey data demonstrated significant and positive influence on artists to synthesize their detailed stories in their works of art through creative and art-based group dialogues, and students’ skills to facilitate multivocality of practice. The results also confirmed that, with shared values of respecting diverse voices of people, creativity and reflectivity, multivocality and inclusive arts practice are compatible frameworks for setting up an inclusive community project.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.034 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".