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Record W1992657580 · doi:10.1505/ifor.8.4.406

The importance of climate change when considering the role of forests in the alleviation of poverty

2006· article· en· W1992657580 on OpenAlex
John L. Innes, Gordon M. Hickey

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.

Bibliographic record

VenueThe International Forestry Review · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsClimate changePovertyNatural resource economicsEnvironmental resource managementEconomicsEcologyEconomic growthBiology

Abstract

fetched live from OpenAlex

SUMMARY Forests could play a major role in the alleviation of poverty in many different parts of the world. However, forests are dynamic, and their rate of change is accelerating as a result of anthropogenic activities. Climate change, for example, will alter the nature of many protection forests in mountainous areas, exposing the inhabitants to increased risk from natural hazards. It will also affect the viability of plantation forests established in drier areas to combat desertification. Many forests are showing increased productivity, although the causes remain unclear. Sea-level change will destabilize coastal forests, particularly mangroves, reducing their effectiveness in coastal protection. Air pollution has already destabilized many forests, and is likely to be an increasing problem in the forests surrounding urban areas in developing countries. Many impacts remain uncertain, and there remains a great need to integrate the biophysical knowledge that currently exists with socioeconomic information associated with the impact on forest-dependent communities.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.163

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 science0.0010.000
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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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