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Record W2125534804 · doi:10.5751/es-02955-140205

Growth and Collapse of a Resource System: an Adaptive Cycle of Change in Public Lands Governance and Forest Management in Alaska

2009· article· en· W2125534804 on OpenAlexvenueno aff
Colin M. Beier, Amy Lauren Lovecraft, F. Stuart Chapin

Bibliographic record

VenueEcology and Society · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersPacific Northwest Research StationU.S. Department of AgricultureU.S. Forest ServiceNational Science Foundation
KeywordsCorporate governanceAdaptive managementResource (disambiguation)Environmental resource managementResource management (computing)BusinessEcologyGeographyPolitical scienceEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Beier, C., A. L. Lovecraft, and T. Chapin. 2009. Growth and collapse of a resource system: an adaptive cycle of change in public lands governance and forest management in Alaska. Ecology and Society 14(2): 5. https://doi.org/10.5751/ES-02955-140205

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)0.001
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 score0.036
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.036
GPT teacher head0.309
Teacher spread0.273 · 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

Citations60
Published2009
Admission routes1
Has abstractyes

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