MétaCan
Menu
Back to cohort
Record W3023751117 · doi:10.5751/es-11503-250210

A review of Indigenous knowledge and participation in environmental monitoring

2020· review· en· W3023751117 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEcology and Society · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsUniversity of Victoria
FundersJacobs Research FundsUniversity of Victoria
KeywordsEnvironmental resource managementIndigenousCitizen scienceEnvironmental planningTraditional knowledgeEnvironmental monitoringGeographyPolitical scienceBusinessEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

There is a growing interest by governments and academics in including Indigenous knowledge alongside scientific knowledge in environmental management, including monitoring. Given this growing interest, a critical review of how Indigenous peoples have been engaged in monitoring is needed. We reviewed and analyzed the academic literature to answer the following questions: How have Indigenous peoples participated in environmental monitoring, and how has their participation influenced monitoring objectives, indicators, methods, and monitoring outcomes? We also summarized how this literature discussed power, governance, and the use of both Indigenous and scientific knowledge in environmental monitoring efforts. We found that the literature most often characterized participation as data collection, and that higher degrees of participation and power held by Indigenous peoples in environmental monitoring leads to initiatives that have different objectives, indicators, and outcomes than those with heavier involvement of external groups. Our review also showed that a key challenge of conducting effective monitoring that leverages both Indigenous knowledge systems and science is the power imbalances that uncouple Indigenous monitoring efforts from management. We encourage future initiatives to carefully consider the ways in which power and governance shape their programs and the ability of their monitoring to lead to meaningful management actions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.280
Teacher spread0.256 · 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