Deep Listening in a Feminist Popular Theatre Project: Upsetting the Position of Audience in Participatory Education
Bibliographic record
Abstract
Investigating the participatory, collaborative, and conflictual character of learning within feminist coalitions was the focus of an interdisciplinary community-based project that used popular theatre as the methodology. Popular theatre, with its creative approach to analyzing, naming, and acting on problems and working creatively with conflict, created a unique opportunity to enrich and complicate one's understanding of deep listening—an embodied and active stand-point for speaking and listening across difference. This article outlines some of the deeper under-standings about feminist politics, theatre processes, and the creation of democratic sites of learning that emerged from this study. The authors focus on theatre processes that created new opportunities for high-risk storytelling and deep listening. Insights from this study can be applied to the learning processes of movements for social justice, particularly feminist coalitions, and to the ways the participatory process and democratic intent of adult education class-rooms are understood.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".