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Record W4410080939 · doi:10.25071/fjkaz950

Reflecting on a panel on Indigenous rights, environmental injustice, and the role of activism

2025· article· en· W4410080939 on OpenAlexaffabout
Élisabeth Abergel

Bibliographic record

VenueCanada Watch · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsInjusticeIndigenousEnvironmentalismPolitical scienceEnvironmental justiceIndigenous rightsEnvironmental ethicsHuman rightsLawPoliticsEcologyPhilosophy

Abstract

fetched live from OpenAlex

he intersection of Indigenous rights, environmental activism, and the complex political landscape of Canada has been brought into stark relief by the controversy surrounding the Coastal GasLink pipeline project.The pipeline, set to traverse the traditional lands of the Wet'suwet'en people in British Columbia, has sparked significant resistance from Indigenous communities, environmental activists, and settler-colonial critics alike.As an academic deeply embedded in the study of environmental justice, political ecology, and the sociopolitical dynamics that shape the environmental crisis, I find this case to be a poignant reflection of the broader challenges facing contemporary Indigenous activism and the ongoing struggles for land and resource sovereignty, and as a continuation and deepening of colonial dynamics pitting evermore destructive extractivist logics against Native survival and its rootedness in the land.As a non-Indigenous person, I feel a strong responsibility to share information about environmental injustices in a way that directly addresses how settlers, including myself, have benefited-and continue to benefit-from the challenges and hardships faced by Indigenous peoples in Canada.

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)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.082
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0350.020
Scholarly communication0.0190.005
Open science0.0030.006
Research integrity0.0150.019
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.290
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes2
Has abstractyes

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