What is the problem of inequality, and can we solve it? Participatory theatre and SDG10
Bibliographic record
Abstract
The purpose of this essay is to consider how, if at all, participatory theatre serves the Sustainable Development Goal number 10: Reducing Inequality (SDG10). The paper draws on policy analysis methodology What’s the Problem Represented to be? (Bacchi 2009) to critically consider how inequity as a solvable social and/or economic problem is represented by SDG10. I then draw on two previous research projects, one conducted by myself and colleagues (2018) and one conducted by Masso-Guijarro and colleagues (2021) that explicitly explore how scholarship in participatory theatre orient to social change agenda to understand how participatory theatre represents the problem of inequality and how, if at all, this relates to SDG10. Finally, I recruit key participatory theatre projects from Denmark, Canada, Chile and New Zealand to consider practical ways of understanding how participatory theatre may contribute to combating inequality through its attention to the lived experiences of inequality, the potential for making changes to individual lives, and its orientation to hope. In doing this, I hope to contribute new perspectives on drama and equity that present a nuanced and critical consideration the relationship between public discourses, policy and practice.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.069 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".