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Record W3135173737 · doi:10.3390/w13050709

Beyond Institutional Ethics: Anishinaabe Worldviews and the Development of a Culturally Sensitive Field Protocol for Aquatic Plant Research

2021· article· en· W3135173737 on OpenAlexafffundabout
Brittany Luby, Samantha Mehltretter, Robert L. Flewelling, Margaret Lehman, Gabrielle Goldhar, Elli Pattrick, Jane Mariotti, Andrea Bradford

Bibliographic record

VenueWater · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaRoyal Bank of Canada
KeywordsIndigenousHarmResearch ethicsField researchEnvironmental ethicsPolitical scienceSociologyEnvironmental resource managementEngineering ethicsLawSocial scienceEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2) guides knowledge production and dissemination in Canada. While it is intended to protect vulnerable populations from harm, it fails to consider Anishinaabe worldviews and, by extension, to effectively direct ethical water research with aquatic plant life. Using Anishinaabe oral testimony and oral stories, Niisaachewan Anishinaabe Nation (NAN) and the University of Guelph (UofG) co-developed a culturally sensitive field protocol to respect Manomin (Wild Rice) as an other-than-human being and guide research into Manomin restoration. By illuminating key directives from NAN, this article showcases the limitations of institutional ethics in Canada. It concludes with recommendations to broaden TCPS2 to better address Anishinaabe teachings about plant and animal relations, but ultimately challenges institutional Research Ethics Boards (REBs) to relinquish control and respect Indigenous Nations’ right to govern research within their territories.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.214

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 studies0.0000.000
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 head0.076
GPT teacher head0.348
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes3
Has abstractyes

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