Stakeholders’ involvement and reflections on preserving sacred swamps in the Western Ghats, India, as revealed by participatory visioning
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
Abstract Lack of a shared vision has been identified as a major obstacle in transdisciplinary research involving both scientists and other stakeholders. Without a shared vision, the implementation of scientific findings is difficult. The diverse partners of collaborative research, however, imply a plurality in the valuation of nature and a need for deliberative mechanisms. If visioning processes are to do justice to local contexts, research must apply deliberative mechanisms to cover the plurality in the valuation of nature. This paper proposes a visioning approach for local communities, based on prior transdisciplinary research. This participatory workshop method invites stakeholders to approach nature conservation and livelihoods via a deliberation of desirable futures, barriers for achieving them and associated responsibilities for taking action. The paper explores this method via a case study of visioning workshops on sacred swamps in the Western Ghats (India), and their role for both freshwater swamp protection and livelihoods. The visioning exercise offered discussion opportunities facilitating conscientization, conciliation and collaboration in local bottom-up nature conservation. For conserving the tropical freshwater swamps, the results show the need for a more participatory forest governance, providing space for shared value creation. They also point to the need for further research on inter-faith nature conservation possibilities, along with innovations on value addition and value chain development for livelihood promotion and protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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