Deliberation for wildfire risk management: Addressing conflicting views in the Chiquitania, Bolivia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wildfires are increasingly affecting forest landscapes around the world. In the Bolivian Chiquitania, southern Amazonia, large wildfires during recent droughts have intensified public debate around more systemic solutions to address the possible root causes. While the integration of different forms of fire knowledge is gaining acceptance as an approach to dealing with increasing wildfire risk, little attention has been given to this integration in the Amazonia. In fact, mismatches between policy, science and local realities have curtailed the success of fire risk strategies in the region. To address this challenge, we conducted interviews and focus group discussions with a wide range of actors in the Chiquitania to examine different forms of knowledge and views of fire, and the extent to which these were integrated in prevalent wildfire risk strategies. We found that the risk strategies were in tension between two conflicting understandings of fire. A conceptual framework was developed to capture the configuration of knowledge underpinning this tension. Adopting a more integrated and inclusive approach to manage wildfire risk will require overcoming first this tension through a more open deliberation process within a reflexive governance framework. We proposed three “deliberation arenas” to facilitate this process, which could ultimately support more systemic, inter‐cultural fire management in the Chiquitania and other landscapes with conflicting views in the Amazonia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it