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Record W1821252514 · doi:10.22230/jem.2002v2n1a222

Natural resource information needs of Aboriginal communities in the Southern Interior of British Columbia

2002· article· en· W1821252514 on OpenAlexaboutno aff
H García Michel, Angus Dickie, Chris Hollstedt

Bibliographic record

VenueJournal of Ecosystems and Management · 2002
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipNatural resourceEnvironmental resource managementInformation needsNatural resource managementResource (disambiguation)BusinessNeeds assessmentGeographyEnvironmental planningPolitical scienceLibrary scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

This paper describes the First Nations Community Needs Analysis Process that FORREX–Forest Research Extension Partnership (formerly SIFERP, the Southern Interior Forest Extension and Research Partnership) undertook in 1999/2000 to identify and analyze the land and natural resource management information needs of the First Nations' communities in the Southern Interior of British Columbia. It also responds to the outcomes of the information needs assessment by presenting a “Framework for Action,” part of which includes establishing the Partnership's Aboriginal Forestry Extension Program.Based on the results of the information needs assessment, First Nations' communities in the Southern Interior of British Columbia clearly have a need and a desire to participate in forestry extension services. The information needs assessment also revealed and expanded on several issues that must be considered in the provision of extension services to First Nations' communities.With incentive from its Aboriginal partners, FORREX has taken a leadership role in providing extension services and has undertaken the responsibility of working with its Aboriginal partners to identify the information and research needs in their communities. The needs analysis process has also provided direction for including traditional ecological knowledge in natural resources management and policy 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 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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.964

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 science0.0000.000
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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 teacher head, 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

Citations3
Published2002
Admission routes1
Has abstractyes

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