One of the key components of problem-solving courts is to deliver sanctions in a way that aligns with deterrence theory. In particular, sanctions should be swift, certain, progressive (or graduated in response to continual noncompliance), and proportional to the severity of the offense (Taxman, Soule, & Gelb, 1999). Failure to adhere to these principles may lead to higher dropout rates in problem-solving courts and higher recidivism rates in the long term (Goldkamp, White, & Robinson, 2001; Kushner, Peters, & Cooper, 2014; Shaffer, 2011).
Given the potential iatrogenic effects emerging from sanctioning processes, there has been a considerable amount of attention given to the delivery of sanctions and their effects on clients’ behavior within problem-solving courts. Shaffer’s (2011) meta-analysis of 76 drug courts showed that programs that did not have a formal sanctioning system and did not swiftly respond to major infractions had higher recidivism rates than programs that had a standardized sanctioning system and swiftly imposed sanctions. These ideas of effective sanctioning have been further tested in the literature on swift, certain, and fair (SCF) sanctioning programs for probationers and parolees. Programs that emphasize swift and certain sanctioning have been shown to reduce substance use, probation revocation, recidivism, and reincarceration (DeVall, Lanier, & Hartmann, 2013; Hamilton, Campbell, van Wormer, Kigerl, & Posey, 2016; Snell, 2007).
While the literature has devoted a significant amount of attention to the effects of sanction swiftness and certainty, fewer studies have examined the element of proportionality and its relationship to clients’ noncompliance. Proportionality is central to effective sanctioning because clients may escalate their offending behavior if they perceive that: (1) the sanctioning process is unfair or unequitable across participants, or (2) if minor violations are punished the same as severe violations. In light of these considerations, the current study investigates: (1) how practitioners rank order common infractions within a problem-solving court, (2) if the imposed sanctions are proportional to the severity of the infraction, and (3) whether disproportionality in the sanctioning process leads to an escalation of client noncompliance (in terms of severity and quicker violation of program rules).
The use of graduated sanctioning grids has been used extensively in probation and parole settings and can build upon researchers’ understanding of sanctioning within problem-solving courts. SCF sanctioning models were popularized by Project HOPE and have been implemented in at least 28 states. Mirroring problem-solving courts’ activities, Project HOPE and similar programs focus on: (1) explaining all rules and consequences to participants, (2) frequently monitoring compliance with rules through regular probation/parole meetings and random drug testing (e.g., at least 1-2 times per week), and (3) “swiftly” administering the sanction in response to noncompliance. The conceptualization of swiftly administering sanctions varies across programs, with some SCF programs immediately imposing a sanction upon detection of noncompliance (Carns & Martin, 2011; Grommon, Cox, Davidson, & Bynum, 2013; Hawken & Kleiman, 2011; Hawken et al., 2016; Kunkel & White, 2013), others imposing sanctions within one to 96 hours of detection (Devall et al., 2013; Neal & Shannon, 2013), and still others administering sanctions nine to 15 days postviolation (Harrell, Mitchell, Merrill, & Marlowe, 2004; Lattimore et al., 2016; O’Connell, Brent, & Visher, 2016).
Overall, the research suggests that programs that immediately impose sanctions may be more effective (Hawken & Kleiman, 2011) than programs in which there is a lag between noncompliance and receipt of a formal sanction (Lattimore et al., 2016; O’Connell et al., 2016). The strongest evidence for this notion emerges from Grommon et al.’s (2013) study of moderate-risk parolees who were randomly assigned to one of three conditions: (1) an experimental group who had frequent, random drug testing (with instant results) and were immediately jailed for any positive drug screens or failing to report; (2) a control group who had frequent, random testing, but did not have instant drug test results or immediate sanctions; and (3) a control group who had neither frequent drug testing nor immediate sanctions. The results showed that the experimental group had fewer positive drug tests and lower recidivism rates at 6 months and 18 months than either control group. These positive findings stand in stark contrast to the null results from Delaware’s Decide Your Time (O’Connell et al., 2016), Maryland’s Break the Cycle (Harrell et al., 2003, and the HOPE Demonstration projects (Lattimore et al., 2016), where sanctions were formally imposed 9-15 days after the violation was detected.
Other structured sanctioning programs have focused on enhancing the proportionality of sanctioning, rather than increasing the swiftness of punishment. Washington’s Swift and Certain (SAC) program put forth a series of graduated sanction for probation violations based upon the severity of the sanction and the number of prior sanctions. A quasi-experimental study of high-risk probationers found that SAC participants were less likely to be jailed (24% vs. 28%) or have a prison confinement (3.1% vs. 19.2%) after a violation, and had 20%–30% lower odds of a felony, violent, and/or property conviction at the 12-month follow-up, relative to a historical comparison group that was not subject to SAC procedures. A cost-benefit analysis of SAC showed a $16 return on investment for every dollar invested in SAC (Hamilton et al., 2016). While Washington’s SAC program produced reductions in crime for probationers, other proportionality grids have failed to reduce recidivism for parolees in Ohio (Martin & Van Dine, 2008; Steiner, Travis, & Makarios, 2008) and California (Turner, Braithwaite, Kearney, Murphy, & Haerle, 2012).
The evidence above suggests that sanctions may effectively prevent criminal behavior for some populations when sanctions are certain, swift, progressive/graduated, and proportional to the severity of the offense. The problem-solving court literature has consistently examined the effects of sanction certainty and progressiveness on clients’ behavior and found them to be important elements to providing effective sanctions. Fewer studies have investigated whether disproportionality in sanctioning impacts clients’ behavior. Disproportionality in sanctioning may exacerbate clients’ noncompliance because: (1) individuals become defiant when they perceive sanctions as illegitimate or unfair (Sherman, 1993), or (2) individuals are not deterred from committing more serious violations if the consequences are the same for both minor and serious offenses.
In light of these considerations, the current study investigates the following questions:
1. How do staff rate the seriousness of violations within a problem-solving court?
2. Based upon staff members’ ratings on the seriousness of violations, do they administer sanctions that are proportionate to the seriousness of these violations?
3. Does disproportionality in the sanctioning lead to clients’ subsequently committing more serious infractions and in a shorter time frame?
The intellectual roots of today’s sanctioning practices are grounded in Jeremy Bentham and Cesare Beccaria’s work. While the field has staunchly adhered to the principles of swiftness, certainty, and severity, the principle of proportionality has been overshadowed in much of the discussion on how to punish and effectively control behavior. This study sought to contribute to this aspect of literature by examining the following questions: (1) how do staff members rate the severity of common violations within a problem-solving court? (2) to what degree are sanctions proportional to the severity of clients’ infractions? (3) what may lead to disproportionate sanctioning for low- and mid-level violations? and (4) how does disproportionate sanctioning impact clients’ behavior?
One finding should be noted before discussing the limitations and policy implications of the study. The data suggest that there may be a lack of equity in sanctioning practices when comparing outcomes for non-White clients to White clients. Approximately 38% of the VTC clients are non-White, yet 58% of clients in the sanction data are non-White. Also, non-White clients were more likely to receive an upward departure (OR = 3.45) compared to White clients, controlling for the number of priors for the same violation, number of priors overall (to date), incurring multiple violations at the same time, phase of the program, age, whether they were a drug offender, and whether they were a felony offender. Thus, despite controlling for general patterns of noncompliance, non-White offenders received disproportionate punishments relative to White offenders. This conclusion differs from that of previous studies, which found that race was not associated with receiving a sanction (Callahan, Steadman, Tillman, & Vesselinov, 2013; Guastaferro & Daigle, 2012) or that White participants fared worse in some sanctioning outcomes than non-Whites (Shannon, Jones, Nash, Newell, & Payne, 2018). Yet, it should be noted that previous research has examined only whether one did or did not receive a sanction, and it has not investigated whether the characteristics of the sanctioning process—swift, certain, progressive, and proportional—vary across racial and ethnic groups. The current study’s findings and those from Gallagher (2013) suggest that future research should continue to explore disparities in sanction processes across racial and ethnic groups.