Greening Garhwal through stakeholder engagement: the role of ecofeminism, community and the state in sustainable development
Bibliographic record
Abstract
Abstract This paper highlights the critical role played by ecofeminism and stakeholder engagement in the region to depict a symbiotic relationship between women and forests that is critical in sustaining human and non‐human life in the Garhwal Himalayan region of India. While it uses ecofeminism to demonstrate the positive role of community in sustainable forestry and development, the chief aim of the paper is to highlight the need to go beyond the ‘civil society’ versus ‘state’ debate that has become rather popular in the development studies discourse. Instead, the paper posits the need for the two to work in active collusion, not only to be successful but also because it is what the subject/agent needs and demands. This paper is the result of field research by the author in the summer of 2004 in the Garhwal Himalayan region of India. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".