Inclusion in Global Environmental Governance: Sustained Access, Engagement and Influence in Decisive Spaces
Bibliographic record
Abstract
With increased participation of non-state actors in global governance, the inclusion of vulnerable groups in making sustainability regulations remains a relevant challenge requiring more research. Based on an ethnographic study on creating the Nagoya Protocol on Access and Benefit-Sharing of biological resources and knowledge, we advance a new multi-dimensional view of inclusion that integrates sustained access, involvement, and influence in the intergovernmental negotiation meetings. We elaborate the concept of decisive spaces, that is, less accessible settings where diverse actors interact in a deliberative way to co-produce recommendations and solutions to an issue that highly influence the regulatory and governance decisions. We argue that the inclusion of vulnerable actors depends on their continuous access to and involvement in these decisive spaces for creating and implementing transnational regulations. Our findings advance the understanding of inclusion for addressing challenges facing transnational governance of environmental, equity, and social justice issues.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".