Bibliographic record
Abstract
Over the past two decades, methodological approaches that operate at the intersection of theater and ethnography have gained both popularity and critical attention. However, given the newness of these endeavors, certain methodological and theoretical elements of such approaches remain unexplored. This is particularly the case in fields such as health research, where people often use theater as a tool of knowledge translation. This article aims to broaden and enrich the growing canon of work in this area in two directions. First, it provides an empirical example of a theatrical script that emerged from a health research project informed both by ethnographic and creative, performance-based practices. In this project the authors used fictionalized accounts of history to help audiences engage with contemporary cultural/ethical issues regarding pandemic planning and response. Second, the authors theorize that this project can be usefully understood as having incorporated a hermeneutic approach to inquiry, and we introduce the notion of mimetic distance as a means of making sense of this project’s success. This article asserts that these theoretical contentions provide further interpretive and creative scope for ethnographic research–based theater and, thus, can usefully expand this growing field.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.031 |
| Scholarly communication | 0.012 | 0.026 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".