Second Generation Risk Assessment Models – Static Actuarial Risk Models

Second-generation risk assessments (Bonta 1996) emerged largely as an artefact of empirically-based research which focused on the prediction of the success or failure of offenders released from custody on parole (Burgess 1928 [1968]). Due to the perceived subjectivity, lack of consistency, and lack of validity of first generation risk assessments, these methods of assessment were abandoned in favour of what appeared to be empirically sound actuarial practices, namely second-generation risk assessments (Hannah-Moffat, 2005, Bonta 1996).

Empirically driven, evidence-based offender risk assessments originated from two fundamental studies in the United States by Hart (1923) and Burgess (1928 [1968]). Burgess’s study (1928 [1968]), perhaps the most academically acclaimed, sought to obtain an understanding of the association between offenders, their offending behaviour, and recidivism in a step to improve the decision-making process of the Parole Board

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and the treatment of their prisoners. This was achieved through the development of what was considered a sound systematic foundation which would identify key factors associated with the likelihood of recidivism for paroled men. Burgess identified 21 equally weighted risk factors that differentiated parole success from failure; each factor was assigned a risk score of one, thus the higher the collective score the greater the likelihood of recidivism (Bonta 1996). Actuarial-based risk assessment tools were developed through empirical-based research and the identification of risk factors and risk scoring. Some scholars recognise that the actuarial approach developed by Burgess (1928 [1968]) remains the ‘gold standard’ for risk assessment development to date, or at least that Burgess’s study represented a pioneering attempt to objectify and empirically rationalise offending behaviour (Schewalbe et al 2007).

By the 1980’s, actuarial tools were widely used in penal practice to predict recidivism and levels of risk; furthermore, most objective risk instruments adopted a scoring method or a variation on the weighting7 methodology (Bonta 1996, Maurutto and Hannah-Moffat 2005). Some of the more prominent tools that were used in the United Kingdom included the Risk of Reconviction (ROR) Scale and the Offenders Group Reconviction Scale (OGRS) (Copas et al 1996). These risk assessment tools were based upon empirical research and were primarily designed to differentiate between risk categories and levels of risk, for example to determine a level of low, medium, high, or very high risk for each individual offender in relation to their likelihood of re-offending (Hannah-Moffat 2005, Bonta 1996, Maurutto and Hannah-Moffat 2005). This is achieved through the measurement and classification or grouping of offenders which is determined by risk factors that are static in nature.

Static risk factors focus less on individual characteristics and more on objective variables that are not subject to change, namely historic aspects of offending behaviour and demographic criteria, such as age of first offence, criminal history and type of

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The OASys user manual describes the calculation of risk reconviction and its relevance to weighting data as follows ‘the risk of reconviction is calculated from all the information about the various dynamic risk factors and the data recorded about the current offence and criminal history. Research has shown that not all offending-related factors are equally correlated with the likelihood of reconviction, this is why the raw scores are weighted….weighting the scores also enables a direct comparison to be made…’ (OASys User Manual, 2002, p121).

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offending behaviour. Thus, static risk assessment models provide fixed levels of understanding risk and risk-taking behaviour, which are in turn, utilised to predict offending behaviour and facilitate supervisory decisions (Schwalbe et al 2007, Maurutto and Hannah-Moffat 2005). It is here that any given criteria can easily and quickly be assigned a risk-score through the production of numerical calculations and subsequently reduce the need for extensive labour intensive assessments. Risk assessment strategies in this sense fail to incorporate professionally-based judgements which may enable practitioners to pay particular attention to the likelihood that an offender could re- offend, instead drawing upon actuarial-based judgements that focus on an individual possessing characteristics associated with re-offending (Hudson 2003). This type of catch-all approach to assessing offenders places an emphasis on visible, practical and accountable risk, and draws attention to individuals who possess all the characteristics or predictive signs associated with offending. The danger here is that predictions of the likelihood of re-offending can result in false negatives – when someone who is not predicted to re-offend does, or false positives – when someone who is predicted to re- offend does not (Hudson 2003, p48). Webster et al (2006) argues that the static actuarial risk factors which are usually associated with offending, such as truanting, single parenthood, educational low-achievement, and disruptive childhoods can also be equated with poverty and that ‘the narrowing down of risk factors to the family, parenting, truancy, and peer groups, reflects more a process of political expediency... than any genuine attempt to understand the causes of criminality’ (Webster et al 2006, p12). Risk assessments then, may appear to present a development towards accuracy and effectiveness, but to what extent do risk assessments serve as a (politically-fuelled) mechanism for organisations in attempts to respond to crime, regulate staff, govern offending behaviour, and limit accountability.

An acknowledged limitation of actuarial-based risk assessment models can be found in their inability as objective instruments to determine the rehabilitative needs or treatment interventions of offenders (Bonta 1996, Maurutto and Hannah-Moffat 2005). That is to say, there has arguably been an over-reliance on actuarial-based assessments that are based upon static factors relating to offending, which has in turn, inhibited practitioner- based judgements and the identification of the rehabilitative needs of individuals in favour for the management of offenders. Still, it becomes apparent when exploring

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documented advances in offender risk assessment, that actuarial approaches to assessing risk, have until recently, been favoured over assessments based on professional judgements as a result of their ability to improve consistency in information processing and their predictive validity (Schwalbe et al 2007, Hoge 2002, Wiebush et al 1995, Champion 1994). The main strength of actuarial methods lies in their reliance on clearly articulated risk factors or indicators which are grounded in empirical data, but the utility of actuarial-based assessments is limited in that they are based on and intended for the classification and categorisation of groups or populations. This means that they are not sufficiently expert or accurate predictive tools of risk in respect of the individual; similarly, they are equally unable to provide professionals with assistance in terms of identifying appropriate interventions which might reduce risk-taking behaviour. As a result, the practitioner remains invaluable in providing a professional judgment or a discretionary decision which may prove a more appropriate outcome when determining suitable rehabilitative interventions. Nonetheless, the underlying rationale of assessment methods is to ensure that practitioner processes and procedures are informed and guided by an objective knowledge process or way of thinking, which in turn has brought with it a shift in power interests. Where once practitioner knowledge acted as a mechanism for addressing re-offending and assigning appropriate interventions to offender-related needs, this has been replaced by a risk assessment method that is geared towards increasing efficiency and effectiveness amongst practitioner productivity and service provisions. Consequently, it could be suggested that actuarial based assessments retain a position of hierarchy over the practitioner and their decision-making processes.