Women in Wildfire Crises: Exploring Lived Experiences of Conflict through Forum Theatre (Creative Intervention)
Bibliographic record
Abstract
Wildfires of exceptional intensity have been on the rise across the globe because of climate change and human activities (UNEP, 2022). In the Amazon basin of South America, the devastating effects of wildfires on natural ecosystems and human lives periodically attract international attention. News portraits of crises, however, tend to be short-lived. The spotlight typically shifts once the emergency has passed and rarely is there an attempt to know more about the ordinary strategies and organising of women and men living in the aftermath of crisis. This creative intervention draws on our recent work investigating the lived experiences of poor rural communities in Bolivia’s Chiquitania, a region deeply affected by wildfires in recent years. We share learning and materials from our project, Playing with Fire,1 situated at the interface of and combining Boal’s (1979, 2002) model of Forum Theatre and social science research. The aim and hope of the project were to use Forum Theatre to open up space for dialogue on the complex and entangled gendered, social and cultural politics of wildfires
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".