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Record W2139724335 · doi:10.1080/02604020590902362

EVOLVING APPROACHES TO CONSERVATION: INTEGRAL ECOLOGY AND CANADA'S GREAT BEAR RAINFOREST

2005· article· en· W2139724335 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Futures · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental, Ecological, and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRainforestEcologyGeographyPoliticsDisciplineTropical rainforestEnvironmental resource managementEnvironmental ethicsSociologyPolitical scienceSocial scienceBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract This case study applies Integral Ecology to analyze the broad range of strategies environmentalists have undertaken to create protected areas and change forest practices in the Great Bear Rainforest, British Columbia, Canada. Rainforest conservation efforts in the region promoted holistic, trans-disciplinary solutions and fostered agreement among diverse stakeholders, modeling an Integral Ecology approach. Environmentalists worked locally and globally, engaging with economic, cultural, political, and scientific systems to create change. The campaign involved transformations at personal and cultural levels that have enabled negotiated solutions involving over twenty million acres of rainforest on British Columbia's coast.

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)0.000
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 score0.782
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.046
GPT teacher head0.241
Teacher spread0.195 · 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