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Record W204088843 · doi:10.18584/iipj.2011.2.4.8

The Importance of Belief Systems in Traditional Ecological Knowledge Initiatives

2011· article· en· W204088843 on OpenAlexvenueno aff
Nicholas J. Reo

Bibliographic record

VenueInternational Indigenous Policy Journal · 2011
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTraditional knowledgeIndigenousResource (disambiguation)Natural resource managementNatural resourceEnvironmental resource managementKnowledge managementBelief systemBusinessEcologySociologyComputer science

Abstract

fetched live from OpenAlex

Resource managers are increasingly engaging with tribes and first nations and looking for methods to incorporate their perspectives, priorities and traditional ecological knowledge (TEK) into public land and resource management. Many initiatives that engage tribes and their TEK holders only seek tribal input, such as biological data, that is most easily integrated into existing management structures. Increasing attention on tribal belief systems would provide a more holistic understanding that could benefit TEK-related initiatives. Such a shift could reduce misunderstandings about tribal natural resource perspectives and lead to insights valuable for society at large.

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)0.045
metaresearch head score (Gemma)0.081
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 score0.045
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.081
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0080.035
Scholarly communication0.0120.011
Open science0.0020.012
Research integrity0.0030.006
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 head0.153
GPT teacher head0.423
Teacher spread0.269 · 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

Citations47
Published2011
Admission routes1
Has abstractyes

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