Improvisational Drama as Inquiry: The Role of the Simulated-Actual in Meaning Making
Bibliographic record
Abstract
Based upon more than 25 years as a director of ensembles of performative research, I provide example of improvisational approaches that I have taken to explore a range of social interactions including the teacher/student relationship, subtle differences among need/want/desire, practicum politics, trust, reading power in gender, judging strangers, locus of control, homelessness, and aging parents. Techniques have included image theater, hot-seating, manipulation of objects, trust falls, music, and metaphorical roles. Theoretical discussions include an unpacking of truth claims in imaginative endeavors that explore the plausible, the false separation of truth and fiction, re-examining what makes research empirical, ways of generating information other than the traditional questionnaire, and/or interview and dialogic audience participation. In addition to justifying this approach for performative research practitioners, it provides a variety of possibilities for those who seek other means to critically and imaginatively examine the human condition.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.087 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".