Commercial fisher perceptions illuminate a need for social justice considerations in navigating climate change impacts on fisheries systems
Bibliographic record
Abstract
Climate change will amplify stress on marine systems already challenged by conflicts and inequities relating to fisheries access, management decisions, and ocean uses across sectors. Understanding how those most connected to fisheries perceive the risks associated with climate change is critical to developing effective responses and establishing management priorities. Adaptation planning efforts may be hindered by perceptions of unequal or unfair distribution of resources and the processes in place to manage them. In contrast, adaptation planning that is more inclusive, transparent, and addresses social dimensions and perceptions of fisheries is more likely to garner support from fishers and fishing communities broadly. We elicited fisher perceptions of climate change impacts on fisheries, and responses to these impacts, through an online survey of commercial fishers in Canada’s Pacific region. The survey highlights substantial concern for climate change, the impacts it will have on fishers’ livelihoods and well-being, and some of the key challenges that may interfere with the ability of fishers and fisheries management to adapt. We frame the findings of the survey drawing from concepts of social justice, focusing on distributive and procedural justice, as necessary considerations, and context for climate change adaptation planning. Developing plans and processes to respond to climate change impacts on fisheries requires not only understanding ecological impacts and challenges, but also the social and institutional considerations that could help or hinder efforts to respond effectively and equitably to a changing ocean.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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 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".