Bilateral and Trilateral Natural Resource and Biodiversity Governance in<scp>N</scp>orth<scp>A</scp>merica: Organizations, Networks, and Inclusion
Bibliographic record
Abstract
Abstract This special issue represents an assessment of international organizations and transboundary networks governing natural resource and biodiversity issues in and amongCanada,Mexico, and theUnitedStates. The management of natural resources and protection of biodiversity is a highly technocratic process requiring collaboration and information sharing among a diversity of actors to facilitate the development and coordination of policy addressing complex and multisectoral issues. Numerous bilateral and trilateral organizations exist to ostensibly facilitate transboundary governance, yet the scholarly knowledge of their respective roles has many gaps. In this introductory article, we propose a typology of international environmental organizations based on two dimensions: (1) whether their activities center primarily on capacity building or regulation, and (2) the extent to which they exemplify the “bureaucratic” or “post‐bureaucratic” model of governance. Using this typology we provide an overview of the special issue's contributions in terms of their assessment ofNorthAmerican bilateral and trilateral environmental organizations and transboundary networks.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".