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Record W3200826486 · doi:10.3138/topia-43-008

Process and Becoming: Spatiality and Carceral Identities

2021· article· en· W3200826486 on OpenAlexvenueno aff
Marsha Rampersaud

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonIdentity (music)Power (physics)SociologyProcess (computing)CriminologySet (abstract data type)Work (physics)Transformation (genetics)Political scienceEngineeringAestheticsComputer science

Abstract

fetched live from OpenAlex

This paper theorizes that a process of identity transformation occurs when individuals enter prisons, whereby individuals become prisoners. I investigate how this identity transformation occurs through interaction with the prison’s architectural design. Prisons are posited as locations of purposeful spatial organization whose design evokes particular performances from those within and outside, and which actively contributes to the creation of the prisoner identity. This investigation reveals a carceral power at work which renders prisons sites of articulated and detailed control that exist within a broader set of institutional practices and relations of power aimed at the transformation of individuals. This discussion critically engages with the broader purpose of the prison: while prisons are meant to rehabilitate and reform prisoners, the structured architecture of the prison conflicts with this objective.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.035
Scholarly communication0.0090.010
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.063
GPT teacher head0.368
Teacher spread0.305 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueTOPIA Canadian Journal of Cultural StudiesSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207