MétaCan
Menu
Back to cohort
Record W4284887130 · doi:10.22329/wyaj.v38.7388

Mapping Racial Geographies of Violence on the Colonial Landscape

2022· article· en· W4284887130 on OpenAlexaffvenueabout
Ingrid Waldron

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIndigenousMateriality (auditing)ColonialismSpace (punctuation)SociologyVulnerability (computing)CriminologyEnvironmental justiceRace (biology)InequalityGeographyGender studiesEthnologyPolitical scienceEcologyAestheticsArchaeologyLaw

Abstract

fetched live from OpenAlex

This paper unpacks the concept of “spatial violence” to examine the social justice dimensions of race, place, space, and the Indigenous and Black communities in Canada. The paper highlights the larger socio-spatial processes that create disproportionate exposure and vulnerability to the harmful social, economic, and health impacts of inequality in Indigenous and Black communities. It also argues that the lived experience of spatial violence and toxic exposure live together and that it is not possible to understand their impacts in Indigenous and Black communities in isolation. The paper also disrupts traditional notions of “the environment” that are centered on harmonizing cities and nature by highlighting the symbolic and materiality of space, especially with respect to how it harms Indigenous, Black and other racialized communities.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0000.000
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 head0.026
GPT teacher head0.315
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 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

Citations2
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueWindsor Yearbook of Access to JusticeSame topicIndigenous Health, Education, and RightsFrench-language works237,207