‘TRANSFORMING IDEAS AND INSTITUTIONS’: ENVIRONMENTAL GRASSROOTS ORGANISATIONS, COLLECTIVE ACTION AND COMMUNITY-BASED CONSERVATION IN INDIA
Bibliographic record
Abstract
Environmental non- governmental organizations (ENGOs) have been stylised as bearers of hope for social changes. Nevertheless, they also have been criticised for their lack of capacity to truly reflect local needs and enhance participation. This paper provides a contribution to the debate of the role of the ENGOs by analysing Tarun Bharat Sangh (TBS), a well known environmental grass-roots organisation in India. The paper examines up to which extend an equitable decision making process has been adopted by this grassroots organization as well as its capacity to fuel collective action. Data came from individual and group interviews with multiple stakeholders and informal interviewing. In total, 32 semi-structured interviews were carried out. The paper illustrates that environmental collective action has diverse important functions which include promotion of participatory processes among community members, equity in decision-making processes, and mobilisation of social innovation through village institutions For policies to increase community participation in natural resources management and to succeed, a better understanding of the factors that facilitate and inhibit community participation is needed. The challenges for participatory development initiatives require an approach which takes into account the dynamics of power relationionship existing between the different stake-holders involved.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".