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Record W4399180243 · doi:10.1515/9781800732858-002

CHAPTER 1 Mino-Mnaamodzawin Achieving Indigenous Environmental Justice in Canada

2022· book-chapter· en· W4399180243 on OpenAlex
Deborah McGregor

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBerghahn Books · 2022
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEconomic JusticeEnvironmental justicePolitical scienceGeographyEnvironmental ethicsPhilosophyLawEcologyBiology

Abstract

fetched live from OpenAlex

To think that Indigenous concepts of justice do not exist is Eurocentric thought." -Wenona Victor Environmental justice (EJ) has several definitions but can generally be thought of as the equitable distribution of environmental burdens and benefits across racial, ethnic, and economic groups.Despite well-documented cases of environmental injustice in Canada, particularly involving Indigenous peoples (Agyeman et al. 2009;Dhillon and Young 2010;Draper and Mitchell 2001;Walkem 2007), the country lags significantly behind in scholarship and policy innovations on this issue compared with the United States (Haluza-Delay 2007).In the United States, an EJ policy framework, including a unique Indigenous and tribal component, has existed now for two decades.Having said this, US policies have thus far failed to adequately address environmental injustices in many instances, as aptly demonstrated in the case of the Dakota Access Pipeline project noted by Kyle Whyte (2017) and other contributors to this volume.Criticisms and limitations of EJ efforts in the United States have been well documented by Indigenous peoples and other groups (Trainor et al. 2007).Various US tribes have asserted that their unique legal-political status affords them a set of considerations that are clearly not accommodated in the current EJ framework.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0230.001

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 head0.030
GPT teacher head0.275
Teacher spread0.244 · 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