Civil society for sustainable change: strategies of NGOs and active citizens to contribute to sustainability transitions
Bibliographic record
Abstract
According to the Kunming-Montreal Global Biodiversity Framework, a “Whole-of-Society” approach is needed to initiate transitions to a nature-positive society. Many look at civil society to initiate and accelerate such transitions. In this article, we investigate strategies from Civil Society Actors (CSAs) to contribute to transformative change, with specific focus on Tiny Forests and Beach Clean-Ups in the Netherlands. Results show that CSAs have a clear Theory of Change to achieve their goals, and act upon that vision through assembling power and resources, developing policy-relevant environmental knowledge, mobilising public support and media coverage and initiating innovative sustainable practices. Adopting mosaic governance approaches, CSAs strategically position themselves in social and institutional networks, connecting professionals and citizens for political leverage. However, our findings show that the step from local impact towards transition remains a large one and the contribution of CSAs should be valued as emergent, co-produced and part of a broader transition movement.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".