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Record W3214075403 · doi:10.1002/fee.2435

Contributions of Indigenous Knowledge to ecological and evolutionary understanding

2021· review· en· W3214075403 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2021
Typereview
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsRaincoast Conservation FoundationUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of VictoriaWilburforce Foundation
KeywordsIndigenousEnvironmental ethicsEcologyTraditional knowledgeDutySociologyInjusticePolitical scienceBiologyLaw

Abstract

fetched live from OpenAlex

Indigenous Knowledge (IK) is the collective term to represent the many place‐based knowledges accumulated across generations within myriad specific cultural contexts. Despite its millennia‐long and continued application by Indigenous peoples to environmental management, non‐Indigenous “Western” scientific research and management have only recently considered IK. We use detailed and diverse examples to highlight how IK is increasingly incorporated in research programs, enhancing understanding of – and contributing novel insight into – ecology and evolution, as well as physiology and applied ecology (that is, management). The varied contributions of IK stem from long periods of observation, interaction, and experimentation with species, ecosystems, and ecosystem processes. Despite commonalities between IK and science, we outline the ethical duty required by scientists when working with IK holders. Given past and present injustice, respecting self‐determination of Indigenous peoples is a necessary condition to support mutually beneficial research processes and outcomes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.895
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.049
GPT teacher head0.355
Teacher spread0.306 · 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