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Record W1644267824 · doi:10.22230/jem.2012v13n2a165

Non-Timber Forest Products in British Columbia: Management Framework and Current Practices

2012· article· en· W1644267824 on OpenAlexaffabout
Evelyn Hope Hamilton

Bibliographic record

VenueJournal of Ecosystems and Management · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsBusinessForest managementContext (archaeology)Environmental resource managementLegislatureResource management (computing)Forest productProduct (mathematics)Environmental planningLoggingGeographyForestryEconomicsComputer science

Abstract

fetched live from OpenAlex

This article outlines British Columbia's forest resource management system and legislative framework in relation to non-timber forest product (NTFP) management. It provides an overview of what NTFPs are and discusses the history related to their use as well as associated rights and regulations. It outlines the BC context in terms of land ownership, the resource management system, management objectives, socio-economic factors, and current trends. The article also describes decision-making as well as planning processes and legal requirements for forest managers, identifies the values forest managers must manage for, and assesses the implications for NTFPs. Finally, the article provides a summary of the current status of management for NTFPs. Opportunities to improve the socio-economic benefits associated with NTFPs are identified and recommendations for future actions are provided.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.479

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.010
Science and technology studies0.0060.003
Scholarly communication0.0070.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.014
GPT teacher head0.252
Teacher spread0.239 · 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 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

Citations2
Published2012
Admission routes2
Has abstractyes

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