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Tackling Prison Overcrowding: Build More Prisons? Sentence Fewer Offenders? by M. Hough, R. Allen and E. Solomon

2010· article· en· W2035643869 on OpenAlexaboutno aff
Justice Tankebe

Bibliographic record

VenueThe Howard Journal of Criminal Justice · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonImprisonmentCriminal justiceOvercrowdingPoliticsCriminologyPopulationEconomic JusticeDemocracyPolitical sciencePunishment (psychology)LawSociology

Abstract

fetched live from OpenAlex

Bristol : Policy Press ( 2008 ) 138pp. £ 14.99pb ISBN 978-1-84742-110-4 There are two commonplace facts about crime and justice in England and Wales. First, is that criminal victimisation has continued to decline since the mid-1990s. Second, is the coincidence of this decline with a phenomenal growth in the prison population by over 60%. This short monograph presents a collection of papers from the proceedings of a symposium that examined government policy on the latter issue as contained in Lord Carter's (2007) report. After an introductory chapter setting out the scope of the symposium, Nicola Lacey begins her analysis with the increased politicisation of law and order in England and Wales. Lacey argues that liberal democratic economies are in a situation akin to the ‘prisoners' dilemma’; that is to say, ‘electoral arrangements and other institutional features of economic and political organisation [in these countries] have created a situation in which the strategic capacity for political and economic coordination necessary to reduce punishment is lacking’ (p.9). Her analysis shows the difficulties of justifying imprisonment on cost-benefit analysis, not only because it fails to reckon with the full complexity of the issues; but also even on such a utility analysis, the evidence would seem to show that ‘increased prison spending is a form of fiscal mismanagement’ (p.16). For Lacey, the solution lies with distancing criminal justice policy from party politics by creating a bipartisan as the equivalent of the Monetary Policy Committee, contending that it is in the interest of politicians to do so. In Chapter 3, Carol Hedderman offers a critical analysis of the grounds for the Labour Government's decision to build more prisons to try to overcome prison overcrowding rather than, say, sentence fewer offenders. Hedderman offers a compelling analysis that casts doubt on the soundness of the evidence on which the government has based this policy decision, describing it ‘inadequate’ and often ‘highly misleading’. Jacobson et al.'s chapter examines the issues from the standpoint of sentencing; they explore, inter alia, whether, and how, sentencing guidelines should be sensitive to prison capacity. Liebling discusses the proposal for ‘Titan’ prisons, arguing convincingly, I think, against the primacy given to ‘economic efficiency’ and making a case for issues of legitimacy to be taken more seriously. Chapter 5 explores issues of the terms and conditions of employment in private prisons, while Chapter 6 presents a review of various ‘decarceration strategies’, based on the experiences of countries such as Finland and Canada. In the penultimate chapter, Rod Morgan offers a summary of some of the key themes emerging from the symposium, and Rob Allen's contribution completes the volume by examining how some of the proposals might shape the future development of penal policy. This is a well-organised book, with logically-strong progression from chapter to chapter. The analyses are bold, compelling and thoughtful, with often radical proposals for tackling prison overcrowding. But perhaps it is the very radical nature of some of the proposal that may make them less attractive to some politicians. Nonetheless, it would be interesting to see how penal policy develops in the next couple of years under the current Coalition Government of the Conservative and Liberal Democrat parties.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.304
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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.

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
Published2010
Admission routes1
Has abstractyes

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