Can Research Become Ceremony? Performance Ethnography and Indigenous Epistemologies
Bibliographic record
Abstract
Pioneered by Victor Turner and further developed by Dwight Conquergood and Norman K. Denzin, performance ethnography foregrounds the experiential, reflexive, intersubjective, and embodied dimensions of performance. Moreover, performance ethnography proposes to integrate the Indigenous critique of Euro-American research, and supports collaborations between Indigenous and non-Indigenous scholars. How, then, might Indigenous epistemologies and methodologies rooted in traditional cultural practices contribute to the future(s) of performance ethnography? Decolonizing performance ethnography necessarily entails redefining both ethnographic research, shaped by the contested discipline of anthropology, and performance practice, linked to Euro-American conceptions of theatre. Drawing from the work of Linda Tuhiwai Smith, Manulani Aluli Meyer, Shawn Wilson, and Floyd Favel, the author asks whether performance ethnography, informed and possibly transformed by Indigenous perspectives, can become a way of engaging in research that contributes not only to our survival, but to the survival of all living species and of the natural world which we co-inhabit.
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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 | 0.021 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.008 | 0.037 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".