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Record W2623405975 · doi:10.5539/enrr.v7n3p1

Managed Migration of Coast Redwoods: Subjectivity of Stakeholders in Oregon’s Land Use Planning Community

2017· article· en· W2623405975 on OpenAlexvenueno aff
Jeffrey Jenkins, Michael W. Jenkins

Bibliographic record

VenueEnvironment and Natural Resources Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPopulationHabitatLand useEcologyPoliticsEnvironmental resource managementEnvironmental ethicsEnvironmental planningPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

The Earth’s climate is changing at a faster pace than the slow natural adjustment rates of most species to their rapidly shifting habitat conditions, especially for long-lived tree species, such as the iconic coast redwood Sequoia sempersqvirens. This may leave some species stranded in less than optimal environments, resulting in population extinctions and/or the need for human-assisted migration. However, the implementation of assisted migration does not come without economic, legal, political, ecological, and ethical issues. One of the most important and complex social questions regarding assisted migration is that of the land use planning community in the area being considered. This article explores the subjective beliefs among these stakeholders regarding managed migration of coast redwood trees into suitable habitats in Oregon. Q-methodology was used to structure the complexity of participants’ subjective beliefs into a few manageable themes to reveal broader socio-economic and environmental perspectives and shared ways of perceiving and valuing the relationship between social, economic, and environmental concerns. The findings of this study suggest two main factors 1) positively ranked values that align on new perspectives of utilitarian ecological values, and 2) positively ranked values that align on a land based communitarian perspective. This convergence suggests an ecologically aware land management ethos as opposed to the view of favoring human’s dominion over nature, and therefore bolsters the potential for the future success of managed migration of coast redwoods into suitable habitats in Oregon given the state’s existing land use policy.

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)0.000
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 score0.008
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.113
GPT teacher head0.318
Teacher spread0.206 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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