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Record W1967347404 · doi:10.5558/tfc80229-2

Protecting culturally significant areas through watershed planning in Clayoquot Sound

2004· article· en· W1967347404 on OpenAlexvenueno aff
Holly Spiro Mabee, George Hoberg

Bibliographic record

VenueThe Forestry Chronicle · 2004
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)Government (linguistics)WatershedEnvironmental resource managementForest managementProcess (computing)GeographyBusinessKey (lock)Environmental planningPolitical scienceForestryEconomicsComputer scienceComputer security

Abstract

fetched live from OpenAlex

Through the Scientific Panel Planning process, First Nations in Clayoquot Sound have had the opportunity to identify and map their culturally significant areas in order to ensure their protection in forest management activities. In this study, individuals involved in forest management from government, industry, and First Nations sectors were interviewed to measure the success of this undertaking. It was found that despite many challenges, First Nations cultural values mapping in Clayoquot Sound has been beneficial for all parties involved in forest management. Key benefits has been an improvement in consultation effectiveness for all parties, and increased confidence among First Nations that their values are being protected. Funding should be provided to allow this process to be completed for the remainder of the landbase. Key words: First Nations, cultural values mapping, British Columbia, Nuu-chah-nulth

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: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.061
GPT teacher head0.365
Teacher spread0.304 · 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

Citations6
Published2004
Admission routes1
Has abstractyes

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