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Record W3180899341 · doi:10.1002/2688-8319.12085

Bridging Indigenous and Western sciences in freshwater research, monitoring, and management in Canada

2021· article· en· W3180899341 on OpenAlex
Steven M. Alexander, Jennifer F. Provencher, Dominique Henri, Lushani Nanayakkara, Jessica J. Taylor, Albana Berberi, Jed Lloren, Jay T. Johnson, Myrle Ballard, Steven J. Cooke

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcological Solutions and Evidence · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of ManitobaUniversity of LethbridgeCarleton UniversityEnvironment and Climate Change CanadaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsIndigenousTraditional knowledgeGeographyEnvironmental resource managementNatural resourceResource (disambiguation)Natural resource managementEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Mutually respectful and reciprocal relationships between people and their environment is a central tenet of many Indigenous worldviews. Across the Americas, this relational connection is particularly evident when it comes to freshwater ecosystems. However, there are numerous threats to these central relationships between Indigenous peoples and their environment. Using all available ways of knowing to conserve, prioritize, and restore relationships between Indigenous peoples and the environment they live in, and are a part of, is critical. Despite legislative requirements and policy commitments, developing and implementing inclusive approaches that bridge multiple ways of knowing remains a challenge. This systematic map examines the extent, range, and nature of published case studies that seek to bridge Indigenous and Western sciences in ecological research, monitoring, or natural resource management across Canada's freshwater aquatic ecosystems. A total of 74 Canadian case studies from 72 articles were included in the systematic map. There were 30 distinct species of focus across the collection of case studies. This systematic map highlights the diversity of ways knowledge systems can be woven, but that the application of these approaches is limited to some key regions (the Pacific and northern regions) and species (whitefish and salmon). The extent and nature of information provided with regards to demographics (e.g., gender, age) of Indigenous knowledge holders contributing to the studies varied widely and in general was poorly reported. Across all of the case studies included in the systematic map there were 78 distinct Indigenous knowledge systems represented. Fifteen different methodological approaches were identified with community‐based participatory research being the most prevalent approach. The presence and diversity of Indigenous methodologies employed was also notable and was greater as compared to a previous study of Canada's coastal marine regions. Collectively, these findings point to a potential emerging transformation in research focused on freshwater ecosystems, habitats, and species to a practice that elevates the role of Indigenous communities, centres Indigenous science and knowledge, and is informed by Indigenous ways of being and doing.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.234
GPT teacher head0.443
Teacher spread0.210 · 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