Transitions Theatre: Creating a Research-Based Reader’s Theatre With Disabled Youth and Their Families
Bibliographic record
Abstract
Transition to adult life can be a challenging time for disabled youth and their families. This article describes the collaborative creation of Transitions Theatre, a research-based reader’s theatre activity based on narrative interviews with eight disabled youth (aged 17–22) and seven parents. Analysis of these interviews generated two opposing yet interrelated themes. On one hand, youth and families felt lost in transition facing multiple gaps in healthcare, financial support, education, and opportunities for social participation after having “aged out” of the pediatric system. On the other hand, they started cripping “normal” adulthood to envision more inclusive futures wherein disabilities are understood as integral to society. These two themes were transformed into two reader’s theatre scripts, one featuring a youth, the other featuring a parent. Seven youth and four parents (six of them were original interview participants) then participated in a Transitions Theatre workshop to read the scripts together and discuss the authenticity and relatability of the scripts. Participant feedback suggested that the reader’s theatre method was effective in sharing findings with research participants and stimulating a critical dialogue on how to (re)imagine transition to adulthood. We discuss the importance of implementing inclusive design strategies to make reader’s theatre accessible to participants with diverse abilities and preferences.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".