Playbuilding as Arts-Based Research Health, Wellness, Social Justice and Higher Education (2nd ed., 2024) by Joe Norris, Kevin Hobbs, & Mirror Theatre
Bibliographic record
Abstract
Kevin Hobbs, whose research examines the pedagogical possibilities of improvisation and role-play in the fields of health and medicine.Hobbs and Norris also name the Mirror Theatre company, as a third and final authorship attribution.Mirror Theatre was originally developed by Norris at The University of Alberta.The program was later reimagined at Brock University in Ontario when Norris moved academic positions.Mirror Theatre-its methods, social issue productions, participants and audiences and evolution-is the source material for this productive investigation of playbuilding as a qualitative, arts-based research method.I come to my review of this text with knowledge of Norris's methods.As a US academic, I use Norris's first edition, Playbuilding as Qualitative Research, in my own graduate-level research methods course.I find the original text to be an effective, cogent way to introduce nascent graduate student researchers to theatrical devising as participatory action research.My MFA students have cited and used Norris's explication of playbuilding as theoretical and practical grounding for their theatre for social change devising practice with youth and communities.With this history in hand, I am pleased to report that Playbuilding as Arts-Based Research offers a purposeful improvement to the original source material.The numerous second edition shiftsupdates to the theoretical methodology, an explicitly curated typology of the five research dimensions engaged through playbuilding, timely inclusion of digital methods and archival examples, expanded script source material, additional insights from scholars working with similar methods, and a brief section on program impact-are excellent.Norris et al.'s new text gives students, teaching artists, academics, and researchers working across the fields of health, social work, education, and the arts a more substantive grounding in the theory and practice of
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".