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Record W2082148320 · doi:10.5038/2162-4593.15.1.2

Local Institutions for Subsistence Harvesting in Western Alaska: Assessing their Adaptive Role in the Context of Global Change

2012· article· en· W2082148320 on OpenAlexaboutno aff
Colin West, Connor Ross

Bibliographic record

VenueJournal of Ecological Anthropology · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsSubsistence agricultureContext (archaeology)Natural resourceResource (disambiguation)Participant observationBusinessEnvironmental resource managementGeographyNatural resource economicsEcologyEconomic growthSociologyEconomicsAgricultureSocial scienceArchaeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.233
GPT teacher head0.454
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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