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Record W4306408372 · doi:10.1386/public_00123_1

Relational Praxis Art: Confronting Epistemic Injustice In Lumpen Community

2022· article· en· W4306408372 on OpenAlexaffabout
Kim G. Jackson

Bibliographic record

VenuePublic · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPraxisGentrificationInjusticeSociologyAgency (philosophy)CapitalismPoliticsNeighbourhood (mathematics)Environmental ethicsCriminologyPolitical scienceSocial scienceEconomic growthLaw

Abstract

fetched live from OpenAlex

In a gentrifying Toronto neighbourhood, unwaged/unhoused community members work to maintain their access to a small park that is the heart of their cultural, economic and spiritual practices. Besieged by institutional violence and medicalization, the violences of colonial-capitalism, ageism, ableism, stigmatization and ongoing trauma, their inhabitation of the park is seen to make it “sketchy.” The Friends of Watkinson Park (FoWP) was formed to resist exclusion by gentrification. In working with FoWP I have generated a method called relational praxis art (rpa). With rpa, I engage local materially-based exchange relations and social reproduction practices that build low-income community as a basis for resisting symbolic violence and epistemic injustice: blaming and shaming low-income peoples for the conditions of their lives and the denial of their truths and knowledge contributions. Rpa prioritizes political agency, knowledge production, culture and creativity to generate interventions that assert low-income inhabitation of urban space towards a liberatory future.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0140.032
Scholarly communication0.0080.006
Open science0.0020.016
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.127
GPT teacher head0.273
Teacher spread0.147 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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