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Record W2157401228 · doi:10.1089/env.2013.0028

“But You Never Know in These Kind of Things”: Contingent Factors for Environmental Justice at the Beare Wetland, Scarborough, Canada

2013· article· en· W2157401228 on OpenAlexaboutno aff
Lisa Sharma‐Wallace

Bibliographic record

VenueEnvironmental Justice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
FundersAustralian Government
KeywordsInjusticeConceptualizationEnvironmental justiceEconomic JusticeNegotiationSociologyEnvironmental ethicsPoliticsEnvironmental lawCriminologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Critics have reproached conventional environmental justice research for a limited conceptualization of justice that discounts structural factors as a primary cause of environmental injustice. This article reiterates and strengthens the structural critique by focusing on the corollary of structural environmental injustice, instead exploring the confluences, difficulties, and uncertainties of achieving environmental justice amidst an indifferent political and social environment. Drawing on examination of historical, planning, and promotional documents combined with analysis of two semi-structured interviews, the article explores the contingencies, negotiations, and unexpected events that led to the partial achievement of environmental justice at the Beare Wetland in Scarborough, Ontario, Canada while noting the structural challenges to environmental justice that remain. The article ends with a discussion of the wider implications for social and environmental justice.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0400.020
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0020.004
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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