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Record W94578531 · doi:10.7202/1084104ar

A Review of Traditional Environmental Knowledge: An Interdisciplinary Canadian Perspective

2021· review· en· W94578531 on OpenAlex

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

VenueCulture · 2021
Typereview
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of GuelphToronto Metropolitan University
Fundersnot available
KeywordsNatural resourcePerspective (graphical)Traditional knowledgeSociology of scientific knowledgeContext (archaeology)Natural resource managementEnvironmental ethicsResource (disambiguation)Value (mathematics)SociologyPolitical scienceEnvironmental resource managementKnowledge managementSocial scienceGeographyEcologyLawComputer scienceArchaeology

Abstract

fetched live from OpenAlex

Over the past fifteen years there has been increasing interest in the nature and application of Traditional Environmental Knowledge (TEK) in Canada. This lias coincided with the settlement of land claims, the emergence of comanagement regimes, and the ascendancy of First Nation power and influence in formal decision making processes. Discourses on actual and potential applications of TEK in land and resource management are the focus of this paper. TEK is the outcome of complex interactions between a culture and the natural environment. Although there are different cosmologies and adaptations, common themes emerge in the way knowledge is acquired and communicated. There is also a great deal of value in its application. However, a number of issues remain to be resolved such as the compatibility between Western scientific knowledge and TEK, and the acquisition and application of TEK by "outsiders." As knowledge is taken from its immediate context it is "abstracted" to conform with the needs of the user and to the scale at which it is being applied. Two subsequent issues emerge. First, TEK is transformed as it is removed from its original context, and second, it may be co-opted in the name of resource and land management decisions that do not necessarily serve First Nations’ interests.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.125
GPT teacher head0.480
Teacher spread0.355 · 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