This article reports on the results of a quasi-experimental study of practitioners' skills in probation work. Videotaped interviews were produced by a group of probation officers and analysed by researchers using a checklist designed to identify the range of skills used in oneto-one supervision. Reconviction rates were found to be significantly lower among those whose supervisors were assessed as using a wider range of skills. The article also reviews the recent history of research on practitioners' skills in probation, and considers the implications of positive findings from this and other studies.

This article examines the rise in prominence of ‘enforcement’ as a key aspect of the work of the probation service in England and Wales, and assesses the extent to which probation's ‘enforcement turn’ can be said to have enhanced the legitimacy of the Service. With reference to research on the effects of the toughening up of enforcement policies on both offenders and staff, this article argues that the equation of ‘toughness’ and ‘legitimacy’ in the probation context is deeply problematic. The article concludes that we may have reached a ‘tipping point’ with regard to enforcement and its reputational significance for the probation service, and that a more responsive and flexible approach towards the enforcement of community sanctions may be emerging.

This article critically analyses the nexus of race and risk prediction technologies applied in justice systems across western jurisdictions. There is mounting evidence that the technologies are overpredicting the risk of recidivism posed by racialized groups, particularly black people. Yet the technologies are ostensibly race neutral in the sense that they do not refer explicitly to race. They are also compliant with race equality laws. To investigate how apparently race neutral technologies can nevertheless yield racially disparate outcomes, the article draws on insights distilled from the sociology of race and the sociological scholarship on standardization. It uses themes from these two scholarships to unravel the intersecting structural and creational dynamics capable of fomenting the digital racialization of risk.

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To develop an empirical account of the impact of contemporary penal developments on frontline probation practice in England and Wales, this article will draw on a study that examined how the interrelated discourses of ‘risk management’ and public protection’ pervading probation policy in England and Wales are translated in enforcement practice. The study found a degree to resistance to the prevailing risk-focused policy agenda. Frontline probation practitioners reported that they tended to rely mainly on a compliance-oriented enforcement model underpinned by welfarist ideals reminiscent of penal modernism1.

Objectives: This article presents two studies assessing the impact of mindfulness in prison (prisoners and staff) and non-custodial settings. Method: Study 1—prisoners ( n = 17) and staff ( n = 15) in a UK prison completed a mindfulness program; 16 individuals acted as a single time point comparison. Data were collected using self-report, computer based and physiological measurement. Study 2—men under community probation supervision were allocated to mindfulness (completed, n = 28) or TAU ( n = 27). Data were collected using self-report mindfulness measures. Results: Study 1—statistically significant (increases in mindfulness skills (η2 p = .234 to η2 p = .388), cognitive control (η2 p = .28), and heart rate variability (SDNN; η2 p = .41) along with significant decreases in stress (η2 p = .398) were found. In study 2, the mindfulness group showed non-significant improvements in mindfulness skills. Conclusion: The findings suggest brief mindfulness interventions could make an important contribution to offender rehabilitation and custodial staff wellbeing.

Organisations, governments, institutions and others across several jurisdictions are using AI systems for a constellation of high-stakes decisions that pose implications for human rights and civil liberties. But a fast-growing multidisciplinary scholarship on AI bias is currently documenting problems such as the discriminatory labelling and surveillance of historically marginalised subgroups. One of the ways in which AI systems generate such downstream outcomes is through their inputs. This paper focuses on a specific input dynamic which is the theoretical foundation that informs the design, operation, and outputs of such systems. The paper uses the set of technologies known as predictive policing algorithms as a case example to illustrate how theoretical assumptions can pose adverse social consequences and should therefore be systematically evaluated during audits if the objective is to detect unknown risks, avoid AI harms, and build ethical systems. In its analysis of these issues, the paper adds a new dimension to the literature on AI ethics and audits by investigating algorithmic impact in the context of underpinning theory. In doing so, the paper provides insights that can usefully inform auditing policy and practice instituted by relevant stakeholders including the developers, vendors, and procurers of AI systems as well as independent auditors.

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