Local Institutions for Subsistence Harvesting in Western Alaska: Assessing their Adaptive Role in the Context of Global Change
Bibliographic record
Abstract
This article identifies key types of local institutions rural Alaska Native communities use to manage subsistence resources such as fish, game, and edible plants. Local institutions are the informal rules and norms communities use to manage these and other natural resources. Other scholars have mostly discussed them in the context of how they help subsistence users cope with ecological fluctuations in the abundance of certain species. The study presented here discusses them within a larger context of social and economic change. These local institutions were identified based on personal interviews with 62 active subsistence users in six different Yup’ik communities in the Yukon-Kuskokwim Delta region of Western Alaska. Participant-observation in subsistence activities like fishing and gathering supplemented the interview material. The key local institutions involve resource harvesting, resource processing, and resource sharing. The analysis of interview and observation data show that local institutions help households and communities cope with fluctuations in harvest amounts due to ecological perturbations, formal management regulations, and high fuel prices. Although local institutions can be fragile in the face of market pressures, and rationale for some institutions are not known by the younger generation, the strong role of sharing suggests that Yup’ik local institutions are expected to persist as climatic, environmental, economic, and social change continues.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".