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Record W1969470624 · doi:10.1080/08941920801898341

Representing Traditional Knowledge: Resource Management and Inuit Knowledge of Barren-Ground Caribou

2008· article· en· W1969470624 on OpenAlex
Anne Kendrick, Micheline Manseau

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSociety & Natural Resources · 2008
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousTraditional knowledgeResource (disambiguation)Resource management (computing)WildlifeEnvironmental resource managementGeographyNatural resource managementWildlife managementEnvironmental planningNatural resourceEcologyComputer scienceEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Comanagement regimes in Canada's North rarely include indigenous systems for understanding the environment. Mapped representations and accompanying narratives illustrating the collective knowledge of indigenous hunters can make unique management contributions. Both the multigenerational knowledge of indigenous communities and opportunities allowing a discussion of diverse ways of interpreting environmental observations are crucial to involving indigenous learning systems within current regional wildlife management. It is not just the factual “data” of indigenous hunters that are relevant to resource management. It is the opportunities for social learning or for resource managers to understand how indigenous hunters learn about the environment that are directly relevant to resource management decision making.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.996

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 studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.050
GPT teacher head0.339
Teacher spread0.289 · 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