Mismatches in salmon social–ecological systems: Challenges and opportunities for (re)alignment in the Skeena River watershed
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
Mismatches between institutions and social–ecological systems (SESs) are one of the foremost challenges in natural resource management. However, while mismatches are often cited in the literature as a major challenge, empirical evidence of mismatches and their consequences is limited. This is particularly true for complex SESs, such as on the Pacific Coast of North America, where salmon drive interactions across multiple environments, jurisdictions, and scales. Here, I use the theoretical concept of fit to examine institutional alignment in a large-scale Pacific salmon SES, the Skeena River watershed in British Columbia, Canada. Utilizing Canadian federal environmental assessments as a proxy for colonial environmental governance institutions, I describe the common causes and consequences of mismatches between institutions and salmon SESs. This case study suggests that mismatches are threatening salmon sustainability and negatively affecting Indigenous People’s rights, livelihoods, and approaches to resource management and stewardship. I argue that improving social–ecological fit in salmon SESs will require new or revitalized forms of environmental governance that consciously fit the underlying social–ecological dynamics. While these findings are based on the Skeena River watershed, they may be generalizable to other salmon SESs in which mismatches between social and ecological processes and institutions exist.
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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 | 0.001 | 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