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Record W2563465075 · doi:10.1111/hojo3_12187

The Voluntary Sector and Criminal JusticeA. Hucklesby and M. Corcoran (Eds.). Basingstoke: Palgrave Macmillan (2016) 252pp. £68.00hb ISBN 978‐1‐137‐37067‐9

2016· article· en· W2563465075 on OpenAlexaboutno aff
Nicola Padfield

Bibliographic record

VenueThe Howard Journal of Crime and Justice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsVoluntary sectorCriminologySociologyPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

This book examines the history of European communist parties in a number of countries following the fall of the Soviet Union.Taking as its starting point the events of 1989 to 1991, it examines the immediate responses of European communist parties to the crisis, their search for an identity separate from Moscow and the formation of distinct electoral platforms and reformist programmes.It tracks their recent electoral success (or for some, distinct lack of electoral success) and contrasts the paths taken by communist parties across the continent.The first few chapters set the scene for what comes later.Chapter 1 focuses on 'Survival and Renewal' in the early 1990s and Chapter 2 looks at the 'regroupment' and the establishment of a 'European Movement' (a network of left-wing parties cooperating both within and outside the European Parliament).Chapter 3 discusses the creation of the Party of the European Left in the European Parliament.The chapters that follow then focus on the communist parties of particular countries; Die Linke (Germany), Partito della Rifondazione Comunista (Italy), Parti Communiste Francais (France), The Communist Party of Bohemia and Moravia, and the Scandinavian left.What is striking is the diversity of paths taken, and fortunes enjoyed, by the parties.For instance, as just one example of divergence, whereas Die Linke achieved national appeal and gained 11.9% of the vote in the federal elections of 2009 and 19.2% in the Saarland state election, the Partito della Rifondazione Comunista was nearly finished following a difficult period in coalition with the mainstream right, taking only 3.1% of the vote in the general election of 2009 (as part of the 'Rainbow Coalition') and subsequently gained no seats in parliament.Just as the book plots the differences in the parties' post-1989/91 experiences, it also brings out a set of consistent and shared dilemmas.How should the hard left respond to the Maastricht Treaty?Seen as a neoliberal free trade project, the parties struggled to frame opposition to the Treaty without surrendering their internationalist (in this case, pan-European) heritage.Further, some parties gained sufficient strength to become viable coalition partners, often to right-of-centre parties.Should this opportunity for power be taken, or is support for right-wing parties and their agenda seen as too high a price to pay?The book may not appear to be of immediate interest to criminologists, particularly those with a United Kingdom focus.First, there is no discussion of crime or criminal justice policy.The book is a work of political science and a reader looking for a discussion of crime policy within European left parties will look in vain.Second, the book carries no analysis of how post-1989 communism and socialism fared in Britain; this is very much a book about 'continental' left movements.British readers will no doubt find themselves asking which parallels from the European story apply to Britain, and whether the recent apparent strengthening of the hard left within the British Labour Party forms part of this story, or whether Britain is somehow distinct.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.003
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0420.015

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2016
Admission routes1
Has abstractyes

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