Selectively Incapacitating Frequent Offenders: Costs and Benefits of Various Penal Scenarios

Blokland, Arjan; Nieuwbeerta, Paul

doi:10.1007/s10940-007-9033-3

Cited by 20 publications

(17 citation statements)

References 43 publications

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“…This is similar to what Blokland and Nieuwbeerta (2007) did using GTM. In this case, rather than investigate whether a certain set of time-varying covariates could change the residual trajectory curve, these researchers use the residual trajectory curve to ''fill in'' missing holes in the offending trajectories.…”

Section: How Are Methods For Trajectories Applied?supporting

confidence: 86%

Measuring Long Term Individual Trajectories of Offending Using Multiple Methods

2009

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Criminal career researchers and developmental criminologists have identified describing individual trajectories of offending over time as a key research question. In response, recently various statistical methods have been developed and used to describe individual offending patterns over the life-course. Two approaches that are prominent in the current literature are standard growth curve modeling (GCM) and group-based trajectory models (GTM). The goal of this paper is to explore ways in which these different models with different sets of assumptions, do in fact lead to different outcomes on individual trajectories. Using a particularly rich dataset, the criminal career and life-course study, we estimate a unique trajectory for each individual in the sample using the GCM and GTM. We also estimate separate trajectories for each individual directly using the long time series. We then compare these three separate trajectories for each individual. We find that the average trajectories obtained from the different approaches match each other. However, for any given individual, these approaches tell very different stories. For example, each method identifies a rather different set of individuals as desistors. This comparison highlights the strengths and weaknesses of each approach, and more broadly, it reveals the uncertainty involved with measuring long term patterns of change in latent propensity to commit crimes.

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Section: How Are Methods For Trajectories Applied?supporting

confidence: 86%

Measuring Long Term Individual Trajectories of Offending Using Multiple Methods

2009

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“…24 While selectively incapacitating high-risk offenders is likely to be more successful in reducing crime, in practice this can be difficult to implement due to challenges in accurately predicting the likelihood of reoffending [146]. It also raises concerns over differential treatment of offenders [157], and the associated increase in prison costs may exceed any benefit of reduced crime [25].…”

Section: (A) Incapacitationmentioning

confidence: 99%

“…25 Notwithstanding this, EM is typically not utilized as a "treatment" to rehabilitate offenders ( [154], p. 232). Rather, it is used as a control-orientated sanction, and as such cannot be expected to influence offenders' long-term behavior and reduce recidivism post-monitoring ( [85], p. 73;…”

Section: (A) Incapacitationmentioning

confidence: 99%

“…33-34). 26 25 Schwitzgebel et al suggested that the information the BT-R transmitted could be "arranged into 'behavioral feedback' systems which [could] have considerable therapeutic potential" ( [166], p. 234). 26 Recall that Australia's early Ticket of Leave system owed some of its success to the publicity of the sanction and involvement of the community.…”

Section: (A) Incapacitationmentioning

confidence: 99%

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Punitiveness in Australia: electronic monitoring vs the prison

Kornhauser¹,

Laster

2014

Crime Law Soc Change

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Internationally, the 200 year honeymoon with the prison may be ending. Research showing that imprisonment is ineffective in reducing crime is finally being heeded by some conservative governments committed to cost cutting. But, as this case-study of Victoria, Australia, again highlights, punishment regimes are neither universal nor rational. Bucking the trend, prison numbers in Victoria have increased dramatically over the last decade and are set to rise higher. The lingering lure of the prison here, we argue, is a manifestation of Australia's colonial history in which punitiveness has always competed with pragmatic innovation. Although the research findings are inconclusive, we contend that Electronic Monitoring (EM), while differently fraught, better meets the key objectives of sentencing. Using a counterfactual social science thought experiment in the form of an imagined Cabinet submission, we show how political decision makers might be persuaded to effect a shift from prison to EM if it is framed within the competing visions of Australian national identity. We argue that understanding how social policy decisions are made sharpens the scholarly research agenda and also highlights how the convergence of a unique set of non-rational cultural assumptions can shape major shifts (or near misses) in the history of punishment in a particular society.

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“…found little substantive difference between different "strike-zones," concluding that costs associated with incarceration far exceeded benefits for different variants of California's Three-Strikes law Blokland and Nieuwbeerta (2007). concluded much the same in their study of selective incapacitation scenarios in the Netherlands.…”

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confidence: 96%

Using simulation modeling to evaluate sentencing reform in California: choosing the future

Auerhahn

2008

J Exp Criminol

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Criminal sentencing reforms that have as their ostensible goal the protection of the public through the mechanism of selective incapacitation have proliferated in recent years. The most prominent of these types of reforms are the "Three Strikes" laws. Because these changes to sentencing policy work by extending the term of incarceration for affected offenders, rather than by changing the rate of incarceration, many years must pass before the effects of these kinds of changes can be measured and evaluated by conventional statistical methods. Data-validated dynamic systems simulation modeling offers the analyst an opportunity to evaluate prospectively the effects of such changes on prison populations. In addition to providing descriptive and evaluative information about the likely consequences of these reforms to the compositional dynamics of prison populations, dynamic systems simulation modeling also affords the analyst the opportunity to experiment upon the system to examine prospectively the likely effects of policy changes. In this paper, simulation models of the California criminal justice system are created and validated with historical data in order to provide a plausible baseline upon which to base future projections. Different policy scenarios are simulated to the year 2030 to assess experimentally the likely consequences to prison populations and to evaluate how well these policies target the "dangerous offenders" proponents that these policies promise to remove from society via incarceration.We need to move away from the fragmentary studies of individual agencies and toward more comprehensive assessment of how... justice agencies influence one another and together influence crime. Decisions made in one justice agency have dramatic workload and cost implications for other justice agencies and for later decisions... To date, these systemic effects have not been well studied, and J Exp Criminol (

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Selectively Incapacitating Frequent Offenders: Costs and Benefits of Various Penal Scenarios

Cited by 20 publications

References 43 publications

Measuring Long Term Individual Trajectories of Offending Using Multiple Methods

Measuring Long Term Individual Trajectories of Offending Using Multiple Methods

Punitiveness in Australia: electronic monitoring vs the prison

Using simulation modeling to evaluate sentencing reform in California: choosing the future

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