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Record W2110223646 · doi:10.22230/jem.2001v1n1a215

"Doing it right": Issues and practices of sustainable harvesting of non-timber forest products relating to First Peoples in British Columbia

2001· article· en· W2110223646 on OpenAlexafffundabout
Nancy J. Turner

Bibliographic record

VenueJournal of Ecosystems and Management · 2001
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsOverexploitationBusinessAgroforestrySustainabilitySustainable managementNatural resource economicsGeographyEconomicsEcology

Abstract

fetched live from OpenAlex

This paper addresses concerns about commercial harvesting of non-timber forest products (NTFPs) that relate to First Peoples in British Columbia. Many of the species identified as being significant, or having potential significance as NTFPs, are culturally important to First Peoples as sources of food, material, and medicines, or for their spiritual values. While there may be potential for First Peoples to develop local economies from the harvesting, processing, and marketing of NTFPs, there also is widespread concern that traditional values may be lost, and traditional plant resources treated as commodities and exploited by commercial interests. Previous experiences with overharvesting cascara and Pacific yew bark lend substance to this concern.Aboriginal peoples have a long history of sustainable management of their lands and resources. Any proposed harvest and use of traditional resources should be under the control of, or in collaboration with, those First Peoples within whose traditional territory the resources are to be harvested. Applications of traditional management methods for NTFPs should be explored, but this should be done in collaboration with First Peoples and with full respect for their intellectual property rights.Principles of sustainable harvesting of NTFPs are presented that may prove useful in ongoing deliberations about how, or even whether, communities should pursue non-timber forest productsas a means of economic development.

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)0.002
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0390.013
Scholarly communication0.0060.002
Open science0.0020.005
Research integrity0.0020.003
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 head0.021
GPT teacher head0.333
Teacher spread0.312 · 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

Citations16
Published2001
Admission routes3
Has abstractyes

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