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Record W2900566377 · doi:10.1002/fee.1974

Responding to climate change in forest management: two decades of recommendations

2018· review· en· W2900566377 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2018
Typereview
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaGenome Canada
KeywordsLatin AmericansCorporate governanceDiversification (marketing strategy)Climate changeGeographyEnvironmental resource managementPsychological interventionAdaptation (eye)Political scienceEnvironmental planningEcologyBusinessPsychologyEconomics

Abstract

fetched live from OpenAlex

Recommendations for responding to climate change in forest management have proliferated over the past two decades. A systematic review of the scientific literature revealed that the majority of such recommendations (86%) focused primarily on maintaining existing ecological patterns and processes via either passive or active adaptation approaches, while 14% focused on transformation to new system configurations through active interventions. Most recommendations (69%) were general, non‐specific principles and derived from research conducted in North America or Europe. These findings highlight the need for (1) more actionable recommendations and diversification in geographic inquiry, specifically in Asia, Africa, Oceania, Latin America, and the Caribbean; (2) increased contributions from social science and mixed social–ecological inquiry; and (3) governance processes that enhance dialogue among stakeholders to better anticipate and navigate the trade‐offs implied by potential future forests in the decades to come.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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