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Record W208169458

When Private and Public Policing Merge: Thoughts on Commercial Policing

2011· article· en· W208169458 on OpenAlexaffabout
Massimiliano Mulone

Bibliographic record

VenueSocial Justice A Journal of Crime Conflict & World Order · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPatrollingPrivate securityPrivate sectorSociologyPolitical economyLawPublic administrationPolitical science
DOInot available

Abstract

fetched live from OpenAlex

THE PRIVATIZATION OF POLICING 1 HAS BEEN AN ONGOING DISCUSSION AMONG SCHOLARS for the last three decades. At the center of the debate is the growth of the market for security, encouraged by the development of new technologies (Brodeur, 2003), the rise of large private properties (Kempa et al., 2004), and the increasing feeling of insecurity (Baumann, 2007; O'Malley, 2010). The industry has flourished, to the extent that private police forces in several Western countries now have more employees than do the public police (Jones and Newburn, 2006). Although attempts to point to a shift in the production and delivery of security in our societies may have led to an overemphasis of the number of private security forces (Nalla and Newman, 1991), it is nonetheless a sign of a real change. Security has been gradually reduced to a commodity (Loader, 1999; Crawford, 2006; Goold et al., 2010), which can be purchased with increasing ease from a wide variety of sellers (Bayley and Shearing, 1996; 2001). In the Anglo-Saxon context, the privatization of policing has usually been studied as a corollary of the expansion (both quantitatively and qualitatively) of the private sector in general. There are many studies on the increasing use of private security forces for work that was traditionally done by public employees (for example, guarding police headquarters or transporting detainees) or in public spaces (i.e., patrolling streets and public spaces). These changes have often been seen as a central element in the privatization of policing (see, for example, Johnston, 1992; Jones and Newburn, 1998). However, very little research has been done on the other side of the mirror, that is, on the effect of privatization on the public security services, particularly the police. And even fewer studies have dealt with the active role of the public police in privatization (Brodeur, 2003; see, however, Reiss, 1988; Ayling et al., 2009). The privatization of the public police2 is a response, perhaps slightly delayed, to the neoliberal wind that has blown on public services since the end of the 1970s (at least in the Anglo-Saxon context; see Garland, 2001 ; O'Malley, 2010). Increasingly, police chiefs are being asked to think like business managers and performance management has become their guiding principle (Forst and Manning, 1999; Law Commission of Canada, 2002; Ayling et al., 2009). Police must prove that the money they receive from taxpayers is well spent and their service provision needs to be transparent, efficient, effective, and accountable. The pamphlet produced by the Association of Chief Police Officers, A Guide to Income Generation for the Police in England and Wales (2003), is a perfect example of these changes in approach. Several academics have begun to measure the impact of this transformation and their results suggest that it has clearly been significant in terms of the way police work is done and viewed (Ocqueteau and Pichon, 2008; Terpstra and Trommel, 2009). Alongside this general trend, there is a more tangible side to police privatization: the commercialization of police services. Increasingly, police organizations are selling the services they provide to private individuals and/or organizations, from renting off-duty police officers to offering training for the private security workforce (Mulone, 2008; Ayling et al., 2009). As Ayling and her colleagues (2009) have shown, police commercialization is not an isolated phenomenon, but has been accompanied by (new) management techniques. Public police are looking for new ways to deal with budget restrictions (to lengthen the arm of law to quote the authors). Selling services accompanies strategies, such as contracting out, creating charity organizations, relying on advertising, or using more coercive tactics (Grabosky, 2007; Grabosky and Ayling, 2007; Dupont, 2007). In this article, I will focus on the process of commercialization and on the effect of its techniques. …

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)0.008
metaresearch head score (Gemma)0.012
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0190.069
Scholarly communication0.0300.049
Open science0.0040.009
Research integrity0.0160.013
Insufficient payload (model declined to judge)0.0080.002

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 head0.144
GPT teacher head0.394
Teacher spread0.249 · 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
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

Citations13
Published2011
Admission routes2
Has abstractyes

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