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Record W2100824654 · doi:10.1093/bjc/azq014

Problematizing Carceral Tours

2010· article· en· W2100824654 on OpenAlexaffabout
Justin Piché, Kevin Walby

Bibliographic record

VenueThe British Journal of Criminology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of WinnipegCarleton University
Fundersnot available
KeywordsImprisonmentCriminologySociologyPrisonService (business)Public relationsPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Tours of operational prisons and jails have been advocated by some academics as one way of conducting observational research inside carceral institutions and have also been employed as a university-level pedagogical tool for teaching students about the realities of imprisonment. Though the merits of carceral tours as a knowledge-producing practice have been discussed in criminology and related social scientific disciplines, accounts of their limitations supported by empirical evidence remain sparse. Based on previously unpublished Correctional Service of Canada (CSC) penitentiary tour materials obtained through Access to Information requests, this article argues that carceral tours can be highly scripted and regulated in ways that obscure many of the central aspects of incarceration and, in particular, the experiences of prisoners. On the basis of our findings, we argue that, as presently organized, such tours afford little insight into the nature of imprisonment.

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)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.041
GPT teacher head0.315
Teacher spread0.274 · 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

Citations96
Published2010
Admission routes2
Has abstractyes

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