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Record W2950521864 · doi:10.18192/jpp.v27i1.3318

Penal Depth, Weight, Tightness and Breadth

2018· article· en· W2950521864 on OpenAlexvenueno aff
Justin Piché, Kevin Walby

Bibliographic record

VenueJournal of Prisoners on Prisons · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical sciencePsychology

Abstract

fetched live from OpenAlex

A s a leading ethnographer in criminology who has conducted signifi cant in-depth observations and interviews inside prisons, Crewe (2015, p. 51) criticizes 'big picture' theorizing of punishment, noting that it often "stops at the gates of the prison, or breaches its surface somewhat barely or briefl y, judging levels of harshness or humanity largely by metrics such as imprisonment rates and prison conditions, or offi cial sources and fi rst appearances" (also see Crewe, 2009).Prisoners and their own accounts, whether mediated by scholars such as Crewe or through their own writing and ethnographies, often remain unacknowledged or become an afterthought in penal policy discussions and academic debates (Piché et al., 2014).This tendency is problematic, as the experiences of imprisonment cannot be gleaned from policy rhetoric or from standardized, quantitative assessments of the penal population (ibid, p. 52).Crewe (2015) suggests qualitative literature on penal depth, weight, tightness and breadth provides a better framework through which to understand prisoners' life experiences.Depth refers to the invasiveness of the prison regime.Weight refers to the sense of being held down or held back.Tightness refers to forms of control in carceral settings, some of which may not be as heavy or piercing as others.Breadth refers to the coverage, the scope, the all-encompassing nature of prisonization (Crewe, 2011).Overall, this literature on penal depth, weight, tightness and breadth tries to provide an alternative to broad, abstract theorizing of penality (Crewe et al., 2014) by putting emphasis on prisoners' lives rather than focusing on more abstract indicators.Such an orientation affi rms the need to hear from current and former prisoners about their experiences of these issues, as well as criminalization and imprisonment more broadly (Pollack and Eldridge, 2015), when studying the prison and its punitive counterparts operating across and beyond the penal system.Based on the longstanding work of the Journal of Prisoners on Prisons (JPP), which is now in its thirtieth year of circulation, and the much longer tradition of the penal press and prison writing (see Gaucher, 2002), we take the position that prisoners themselves are uniquely positioned to off er

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)0.026
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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.001

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 head0.024
GPT teacher head0.332
Teacher spread0.307 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

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