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Record W2256909571

Balancing Communities, Economies, and the Environment in the Greater Yellowstone Ecosystem

2014· article· en· W2256909571 on OpenAlexvenueno aff
Ryan D. Bergstrom, Lisa M. Butler Harrington

Bibliographic record

VenueJournal of rural and community development · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSocioeconomics of Resources and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityNational parkNatural resourceEnvironmental resource managementEcosystemPopulationEcosystem servicesResource (disambiguation)Natural resource managementEcosystem managementBusinessGeographyNatural resource economicsEnvironmental planningEcologyEconomicsSociology
DOInot available

Abstract

fetched live from OpenAlex

Balancing the needs of local communities, their economies, and associated natural resources is critical to the long-term success of individual communities and larger regions and ecosystems. This is especially true in mountain communities which are increasingly susceptible to land use and land cover changes, and where limited knowledge exists relating to these interactions and the perceptions of local stake holders and decision makers. The Greater Yellowstone Ecosystem (GYE), centered on Yellowstone National Park and extending through parts of Montana, Wyoming, and Idaho, is an ideal location to study the interrelations of economic growth and environmental protection due to the region's complex mosaic of private and public lands, competing natural resource uses, and rapid population growth. The objective of this study was to determine how residents of three communities within the GYE perceive, prioritize, and act upon issues of sustainability community development and natural resource management through key informant interviews. Keywords: sustainability, social-ecological systems, decision-making, perceptions, Greater Yellowstone Ecosystem

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)0.004
metaresearch head score (Gemma)0.000
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 score0.181
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.177
Teacher spread0.157 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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