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Record W2784255215 · doi:10.7202/1042776ar

“Sacrifice Zones” in the Green Energy Economy: Toward an Environmental Justice Framework

2018· article· en· W2784255215 on OpenAlexaffvenueabout
Dayna Nadine Scott, Adrian A. Smith

Bibliographic record

VenueMcGill Law Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsCarleton University
Fundersnot available
KeywordsEnvironmental justiceSacrificeCapitalismFraming (construction)GrassrootsResistance (ecology)Political economyPoliticsSociologyPolitical scienceEnvironmental ethicsLawGeographyEcology

Abstract

fetched live from OpenAlex

The environmental justice movement validates the grassroots struggles of residents of places which Steve Lerner refers to as “sacrifice zones”: low-income and racialized communities shouldering more than their fair share of environmental harms related to pollution, contamination, toxic waste, and heavy industry. On this account, disparities in wealth and power, often inscribed and re-inscribed through social processes of racialization, are understood to produce disparities in environmental burdens. Here, we attempt to understand how these dynamics are shifting in the green energy economy under settler colonial capitalism. We consider the possibility that the political economy of green energy contains its own sacrifice zones. Drawing on preliminary empirical research undertaken in southwestern Ontario in 2015, we document local resistance to renewable energy projects. Residents mounted campaigns against wind turbines based on suspected health effects and against solar farms based on arable land and food justice concerns, and in both cases, grounded their resistance in a generalized claim, which might be termed a “right to landscape”. We conclude that this resistance, contrary to typical framings which dismiss it as NIMBYism, has resonances with broader claims about environmental justice and may signal larger structural shifts worth devoting scholarly attention to. In the end, however, we do not wholly accept the sacrifice zone characterization of this resistance either, as our analysis reveals it to be far more complex and ambiguous than such a framing allows. But we maintain that taking this resistance seriously, rather than treating it as merely obstructionist to a transition away from fossil capitalism, reveals a counter-hegemonic potential at its core. There are seeds in this resistance with the power to push back on the deepening of capitalist relations that would otherwise be ushered in by an uncritical embrace of “green energy” enthusiasm.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.038
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.080
Scholarly communication0.0130.010
Open science0.0020.008
Research integrity0.0040.006
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 head0.038
GPT teacher head0.312
Teacher spread0.274 · 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

Citations113
Published2018
Admission routes3
Has abstractyes

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