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Record W4210470628 · doi:10.1080/10282580.2021.2018655

‘A prison is no place for a party’: Neoliberalism, charitable fundraising, carceral enjoyments and abolitionist killjoys

2022· article· en· W4210470628 on OpenAlexafffundabout
Linda Mussell, Justin Piché, Kevin Walby, Lisa Guenther

Bibliographic record

VenueContemporary Justice Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsQueen's UniversityWomen's and Gender Studies et Recherches FéministesUniversity of WinnipegUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrisonImprisonmentSociologyTicketPoliticsCriminologyTourismNegotiationGovernment (linguistics)General partnershipCriminalizationPublic relationsPublic administrationPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

This paper explores a case study of the struggle over the cultural meanings of charity and imprisonment related to United Way’s 2019 Rockin’ The Big House fundraising concert in partnership with Correctional Service of Canada (CSC) and the City of Kingston at Kingston Penitentiary. Contributing to literature at the intersection of penality, prison tourism, and the charitable sector, we examine how staging authenticity and fostering penal spectatorship were central to driving ticket sales for and encouraging enjoyment at the concert held on the grounds of Canada’s first penitentiary. Based on an analysis of internal government records and CSC communications with United Way, we demonstrate how event planning and advertising relied on denigrating stereotypes regarding criminalized persons. Highlighting the value of collective organizing, action research, and newsmaking interventions aimed at opposing carceral enjoyments, we illustrate how cultural meanings of penality can be confronted as a means to advance abolitionist politics.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.016
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.353
Teacher spread0.293 · 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

Citations3
Published2022
Admission routes3
Has abstractyes

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