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Record W2073971510 · doi:10.1080/00958961003676314

Aboriginal Environmental Wisdom, Stewardship, and Sustainability: Lessons From the Walpole Island First Nations, Ontario, Canada

2010· article· en· W2073971510 on OpenAlexafffundabout
Clinton L. Beckford, Clint Jacobs, Naomi Williams, Russell Nahdee

Bibliographic record

VenueThe Journal of Environmental Education · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsCanadian HeritageUniversity of Windsor
FundersSuncor Energy Incorporated
KeywordsEnvironmental stewardshipIndigenousStewardship (theology)Environmental educationEnvironmental ethicsPanacea (medicine)SustainabilityContext (archaeology)SociologyTraditional knowledgeMainstreamArgument (complex analysis)Social sciencePolitical scienceEnvironmental resource managementGeographyPedagogyEcologyPoliticsLawArchaeology

Abstract

fetched live from OpenAlex

Generally speaking, environmental education teaching, research, and practice have been informed by the traditions of western, Euro-centric culture. In this context indigenous perspectives are often marginalized, maligned, and perceived to be unscientific and therefore inferior. This essay adds to the growing body of literature exploring aboriginal indigenous environmental epistemologies and responsible human interactions with the natural environment. The paper provides a Canadian context as it examines the environmental philosophy and attitude of a Canadian First Nations community to the natural environment grounded in the lived experiences of adults, children and elders from the Walpole Island First Nation. We make the argument that while not a panacea, Aboriginal environmental epistemologies hold lessons for teaching environmental stewardship and sustainability behavior in mainstream classrooms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0340.006
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.003
GPT teacher head0.189
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations137
Published2010
Admission routes3
Has abstractyes

Explore more

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