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Record W3184811330 · doi:10.3390/su13158382

Indigenous Environmental Justice and Sustainability: What Is Environmental Assimilation?

2021· article· en· W3184811330 on OpenAlexafffundabout
Stephen R. J. Tsuji

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousEnvironmental justiceLegislationSustainabilityEnvironmental lawPolitical scienceAssimilation (phonology)Environmental governanceTreatyEnvironmental planningEnvironmental impact assessmentEnvironmental resource managementEnvironmental protectionEnvironmental ethicsLawBusinessCorporate governanceGeographyEconomicsEcology

Abstract

fetched live from OpenAlex

Canada has a long history of assimilative efforts with respect to Indigenous peoples. Legal assimilation efforts occurred on two fronts: the voluntary and involuntary enfranchisement of First Nations people, and the dissolution of First Nations reserve lands. Cultural assimilation occurred through the residential school system, and the removal of Indigenous children from their homes by Canadian child welfare agencies in the “sixties scoop”. Another form of assimilation is through environmental assimilation. I define environmental assimilation as changes to the environment through development, to the extent whereby the environment can no longer support Indigenous cultural activities. Herein, I examine environmental assimilation in northern Ontario, Canada. The “taken-up” clause in Treaty No. 9, the “Exemption Orders” in the Far North Act, the “Except” stipulation in the Mining Amendment Act, and the unilateral streamlining of projects in the Green Energy Act and the COVID-19 Economic Recovery Act—these pieces of legislation pose threats to the environment and serve to facilitate the reality of contemporary environmental assimilation of First Nations.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.405

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0110.025
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0020.003
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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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 designTheoretical or conceptual
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

Citations22
Published2021
Admission routes3
Has abstractyes

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