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Record W2800286067 · doi:10.7936/k7p26xk6

Participation in Governance and Well-Being in the Yukon Flats

2017· article· en· W2800286067 on OpenAlexaboutno aff
Jessica C. Black

Bibliographic record

VenueOpen Scholarship Institutional Repository (Washington University in St. Louis) · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersUniversity of WashingtonCouncil on Social Work Education
KeywordsCorporate governancePolitical scienceEnvironmental planningGeographyPublic administrationBusiness

Abstract

fetched live from OpenAlex

This dissertation explains the relationship between participation in governance and well-being in the Yukon Flats. To garner a deeper understanding of this relationship, definitions of governance and well-being are sought from the participants, thus providing holistic, Indigenous definitions of these concepts. Both formal and informal governance are also explored to understand the important institutions that underpin these larger relationships. Lastly, this dissertation investigates the relationship between participation in traditional hunting, fishing, and gathering and well-being in the Yukon Flats. Qualitative methods, including semi-structured interviews, observations, and photographs are all used to document these relationships. Applied thematic analysis is used due to its efficacy when conducting team research and also because of its effectiveness in presenting stories and experiences of participants truthfully and inclusively. These methods are also culturally congruent with Alaska Native epistemologies. This research has relevancy for Alaska Native and American Indian communities, policymakers, and state and federal officials who are all charged with sustaining natural resources and simultaneously creating healthy communities where people are well in all aspects of their life.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.046
GPT teacher head0.365
Teacher spread0.318 · 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.

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

Citations5
Published2017
Admission routes1
Has abstractyes

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