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Record W4379741116 · doi:10.4337/9781800881136.00018

Environmental inequality and rights of nature among Indigenous Peoples in North America

2023· book-chapter· en· W4379741116 on OpenAlexaboutno aff
Julie Schweitzer, Olivia M. Fleming, Tamara L. Mix

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousSovereigntyEnvironmental justiceColonialismEquity (law)InequalityPersonhoodScholarshipEnvironmental ethicsIndigenous rightsPolitical scienceEnvironmental lawEconomic JusticeSociologyPolitical economyLaw and economicsLawEcologyPolitics

Abstract

fetched live from OpenAlex

Colonial-capitalist systems promote structural environmental inequalities that disproportionately impact Indigenous Peoples and ancestral territories. We examine the role of a Rights of Nature (RoN) framework in articulating responses to environmental inequality through two cases of Indigenous Environmental Justice (IEJ) movements in Canada - the Idle No More (INM) movement and the Wet’suwet’en Nation’s protective actions. Building on previous RoN and IEJ scholarship, we ask: How is the RoN framework employed to address issues of environmental inequality? We find that INM relies on broad references to nature to respond to omnibus Bill C-45, adapting the Nature’s Rights Model, while Wet’suwet’en Nation’s actions align more closely with the Legal Personhood Model in organizing against the Coastal GasLink pipeline and encouraging recognition of Indigenous laws. Altogether enhancing sovereignty claims, we argue that RoN is a framework promoting environmental equity and a tool for resistance to and disruption of settler colonial translations of nature.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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.

Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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