Interagency Trust and Communication in the Transboundary Governance of Pacific Salmon Fisheries
Bibliographic record
Abstract
The transboundary governance of Pacific salmon fisheries requires interactions between institutions that can enable collective action, collaboration, and continuous learning. However, relatively little is known concerning how civil servants in different institutions and jurisdictions interact with each other within transboundary policy settings. In this paper, we explore the interactions of civil servants from agencies in five jurisdictions: United States (federal), Canada (federal), British Columbia, Yukon, and Alaska, to assess the extent to which they interact within the Pacific salmon policy network and also the social capital (i.e., formal and informal communication and trust) present among these working relationships. Our results reveal patchy patterns of interagency communication, and relatively low levels of interagency trust between jurisdictions, suggesting the potential for improved collaboration on Pacific salmon governance. Our analysis also revealed that the binational Pacific Salmon Commission had the highest levels of trust within the network, suggesting it is likely well placed to foster collaboration.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".