The impacts of trust, cost and risk on collaboration in environmental governance
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 Collaborative approaches to environmental governance are drawing increased interest in research and practice. In this article we investigate the structure and functioning of actor networks engaged in collaboration. We specifically seek to advance understanding of how and why collaborative networks are formed as actors engage in addressing two broad classes of collective action problems: coordination and cooperation. It has been proposed that more risk‐prone cooperative problems favour denser and more cohesive bonding network structures, whereas less risky coordination problems favour sparser and more centralized bridging structures. Recent empirical findings, however, cast some doubts on these assumptions. In building on previous work we propose and evaluate a set of propositions in order to remedy these ambiguities. Our propositions build on the assumption that bridging structures could, if actors experience sufficient levels of trust in the collaborative process, adequately support both cooperation and coordination problems. Our empirical investigation of four UNESCO Man and Biosphere Reserves gives initial support for our assumptions, and suggests that bridging structures emerge when actors have trust in the collaborative endeavour, and/or when the cost of collaborative failure is deemed low. While caution is warranted due to data limitations, our findings contribute to improved policies and guidelines on how to stimulate and facilitate more effective collaborative approaches to environmental governance. A free Plain Language Summary can be found within the Supporting Information of this article.
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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 | 0.000 | 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 | 0.000 | 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