Playbuilding as Qualitative Research: A Participatory Arts-Based Approach
Bibliographic record
Abstract
Norris' AERA award-winning book Playbuilding as Qualitative Research: A Participatory Arts-Based Approach is a welcomed research text which makes a valuable contribution for researchers, artists and educators interested in using theatre to engage in arts-based research. His book comes at a time when a number of important international scholars interested in applying theatre as a research methodology are sharing book length works: Judith Ackroyd & John O'Toole (2010) Performing Research: Tensions, Triumphs and Trade-offs of Ethnodrama; Tara Goldstein (2011) Staging Harriet's House: Writing and Producing Research-informed Theatre; and Johnny Saldana (2011) Ethnotheatre: Research from Page to Stage. These scholars respectively provide their valuable and insightful perspectives on theatre's potential to inform/enhance research. For his part, Norris clearly articulates how and why playbuilding (based upon collective creation) can be an insightful and valid approach for researchers and artists to consider for their work.
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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 | 0.139 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".