Interagency Trust and Communication in the Transboundary Governance of <scp>P</scp>acific Salmon Fisheries
Bibliographic record
Abstract
Abstract The transboundary governance of P acific 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: U nited S tates (federal), C anada (federal), B ritish C olumbia, Y ukon, and A laska, to assess the extent to which they interact within the P acific 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 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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".