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Record W2174105454 · doi:10.5558/tfc2012-100

Crown–Coastal First Nation governance of the Great Bear Rainforest: An introduction to my research

2012· article· en· W2174105454 on OpenAlexvenueno aff
Laura Marie Bird

Bibliographic record

VenueThe Forestry Chronicle · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Corporate governanceGeographyEnvironmental resource managementResource management (computing)Environmental planningEcosystem-based managementRainforestResource (disambiguation)Political scienceBusinessEcosystemEcologyEnvironmental science

Abstract

fetched live from OpenAlex

This article introduces a 2011 Master’s thesis that undertook two objectives. First, it assesses whether the Coastal First Nations, a coalition of First Nations on the coast of British Columbia, have acquired a share of governmental decision-making authority for three types of decisions: land use zones, ecosystem-based management (EBM) operating rules, and approval of operational plans. Second, it provides an overview of the unique government-to-government process that evolved for the resource management for British Columbia’s North and Central Coast, and the framework for shared decision-making that has been established between the Crown and the Coastal First Nations regarding the three land use planning decisions under investigation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.008
Scholarly communication0.0080.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.032
GPT teacher head0.304
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2012
Admission routes1
Has abstractyes

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