Pedagogies of Praxis: Exercises in Embodying Social Justice for Performance Studies Seminars
Bibliographic record
Abstract
This article discusses my pedagogies of praxis in the performance studies classroom focused on identity, inclusion, and social justice. I especially consider methodologies I employ in seminars focused on analyzing and making social justice performances such as Performing Human Rights and Performing Activism. This discussion explores the significance of embodied ways of learning and the materialities of the performance studies classroom. I argue that such praxis—which combines foundational and cutting-edge theories in the field, analysis of sites of performance that exemplify such work, and affective exercises that allow students to embody these theories through their lived experience—creates the most meaningful learning outcomes. I discuss various exercises I developed which offer up a material trace of the embodied, praxis-oriented pedagogy that I centre in my seminars focused on analyzing and making social justice performances.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".