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Record W7133100234

Making Good: Racial Neoliberalism and Activist Subjects in Toronto's Parkdale Neighbourhood

2016· dissertation· W7133100234 on OpenAlexaboutno aff
Griffin Epstein

Bibliographic record

VenueTSpace · 2016
Typedissertation
Language
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsNeoliberalism (international relations)GentrificationBourgeoisieRhetorical questionPoliticsEthnographyPower (physics)RacializationRacismPerformativity
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines the complex roles the Parkdale Activity-Recreation Centre (PARC), a progressive social service agency, has played in Toronto’s gentrifying Parkdale neighbourhood. Emerging from the author’s experiences as a PARC worker, this research juxtaposes the agency’s rhetorical and material investments in opposing gentrification and neoliberalism with its ongoing momentum towards privatization, and spatial and social enclosure. It suggests that the key to understanding these contradictions lies in the construction of the enlightened bourgeois activist, a subject whose genuine desire for personal and political “goodness” both reinforces and obscures racial and gendered violence. Relying on an existing textual archive, ethnographic observation, and extensive interview data, this dissertation tracks the racial and gendered strategies of gentrification and neoliberalism through descending scales: the Parkdale neighbourhood; the institutional and spatial environments of PARC; and the interpersonal and intrapsychical relationships between and among PARC staff. At every level, the enlightened bourgeois activist emerges as both an architect and an effect of existing power structures. Ultimately, this dissertation argues that so long as we leave race and gender uninterrogated in our external and internal lives, the social work that we imagine to be emancipatory will reinforce those systems of domination we hope to oppose.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.408
Teacher spread0.370 · 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 teacher head, not a consensus.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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