MétaCan
Menu
Back to cohort
Record W2907197623

Privatisation in criminal Justice: key issues and debates

2018· book· en· W2907197623 on OpenAlexaboutno aff
Christopher Hamerton, S. Douglas Hobbs

Bibliographic record

VenueePrints Soton (University of Southampton) · 2018
Typebook
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCriminal justicePrisonPolitical sciencePrivate sectorGovernment (linguistics)PoliticsPublic sectorTheory of criminal justicePublic administrationContext (archaeology)Quarter (Canadian coin)Coalition governmentCriminologyLawSociology
DOInot available

Abstract

fetched live from OpenAlex

In recent years, the criminal justice sector has made various strategic partnerships with the private sector, exemplified by initiatives within the police, the prison system, offender services and legal defence. This has seen unprecedented growth in the past quarter of a century, and a veritable explosion under the tenure of the Conservative Liberal Coalition government in the United Kingdom. This book explores the social, cultural, and political context of privatization in the criminal justice sector. Key areas of domestic and global concern are highlighted and illustrated with detailed case studies of important developments. It connects the study of criminology and criminal justice to the wider study of public policy, government institutions, and political decision making and provides a theoretical and practical framework for evaluating collaborative public and private sector response to social problems at the beginning of the twenty-first century.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0070.038
Scholarly communication0.0160.018
Open science0.0020.007
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0090.001

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 head0.026
GPT teacher head0.278
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueePrints Soton (University of Southampton)Same topicCriminal Justice and Corrections AnalysisFrench-language works237,207