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Record W2164730069 · doi:10.7202/006533ar

Spatiality and Environmental Justice in Parkdale (Toronto)

2003· article· en· W2164730069 on OpenAlexvenueaboutno aff
Cheryl Teelucksingh

Bibliographic record

VenueEthnologies · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental justicePoliticsSpace (punctuation)SociologyEnvironmental ethicsEconomic JusticeEnvironmental studiesField (mathematics)Perspective (graphical)Social justiceWork (physics)Social sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

As part of the project to name environmental injustices in Canada, this article explores the significance of a critical analysis of social space to understand environmental justice problems in an urban Canadian community. Environmental injustices that impact on particular geographical locations have a readily apparent, fixed spatial aspect. However, I argue that a broader view to the politics of how space is produced and reproduced is necessary to explain the way in which the spatial manifestations of political economic transformations can create new and dynamic environmental injustices (Massey 1993). I at first outline some of the key components of the environmental justice perspective. Then, by drawing on critical work in the area of human geography, in particular Edward Soja’s (1996) and Henri Lefebvre’s (1991) work, I review the limitations of the dominant approach to spatiality in the American environmental justice literature. I then present my arguments in favour of a critical view to social space through a consideration of my field research findings in the Toronto community of Parkdale.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.044
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0230.010
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.032
GPT teacher head0.324
Teacher spread0.292 · 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

Citations31
Published2003
Admission routes2
Has abstractyes

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