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Recognizing the potentially deleterious consequences of criminalizing school discipline, schools are increasingly turning to alternative methods for holding students accountable for misbehavior. Restorative justice (RJ) practices--which seek to hold students who cause harm accountable without removing them from their learning environment--ostensibly represent an antidote to traditional discipline. However, RJ practices have been the subject of limited high quality scientific inquiry. This study aims to fill this gap through the implementation and evaluation of a restorative program in a school district (District 18) that struggles with the highest suspension rates in New York City.

Related literature presents inconclusive results regarding the effectiveness of restorative justice (RJ) in schools (Anyon et al. 2016; Augustine et al. 2018; Gonz?lez 2015; Gonz?lez et al. 2019). There is little uniformity in restorative justice implementation, although some key components of successful implementation (e.g., staff buy-in, resources) have been identified. Because no two schools are likely to implement restorative practices identically, evaluating them with scientific rigor--typically requiring large samples--has been inherently challenging. As such, randomized controlled trials of restorative justice in schools were virtually non-existent in 2015 (at the time the current study was proposed), and most existing research relied on qualitative, quasi-experimental or pre-post designs. The push for quantitative rigor resulted in the present study, a mixed method randomized controlled trial, along with other recently published or ongoing rigorous evaluations.

The restorative justice program in question aimed to improve school climate, strengthen relationships schoolwide, prevent and intervene in conflict, reduce incidents and suspensions, and enhance any existing restorative practices already in place. Restorative justice has the potential to reduce dependency on punitive measures (e.g., suspension) when an incident occurs at school. Additionally, given the priority placed on building community and providing mental health support, restorative justice may also reduce such incidents altogether, while creating a positive school climate. As such, the primary quantitative outcomes in this study were incident rates, suspension rates, and school climate. This study was a randomized control trial that included a treatment group (enrolled in RJ program), comparison group (no RJ program enrollment), and control groups (general restorative justice practices). The research team hypothesized the following:

• • Hypothesis 1: Students in the treatment group would have fewer incidents and suspensions than the control group.
  • Hypothesis 2: Students in the treatment group would have fewer incidents and suspensions than the comparison group.
  • Hypothesis 3: Students in all of District 18 would have fewer incidents and suspensions than the comparison group.
  • Hypothesis 4: The treatment group would have a more positive school climate than the control group.

The Center for Court Innovation, in partnership with independent consultants from the public defender's office of certain tribes, conducted a comprehensive survey of tribal justice system stakeholders, focused on the existing use of risk-needs assessments and similar tools, and existing data collection/technology used by tribal jurisdictions around the country. The survey results create a comprehensive portrait of tribal court system risk and need assessment, data collection, management, and challenges reported by those directly involved in managing and working with people in the system.

This study uses quantitative and qualitative research to fill a gap in the scholarly literature on "what works" in school discipline, climate, and safety and has important implications for educators and justice policymakers nationwide. The quantitative analysis utilized data from 2010-2015 of middle and high school students (N=87,471 students nested within 804 schools and 74 neighborhoods) in New York City. Researchers applied hierarchical modeling methods to analyze effects of neighborhood, school, and student characteristics on: 1) future school disciplinary outcomes; 2) future arrest; and 3) grade advancement. Demographic variables for individual participants include race, gender, and if they are an English language learner.

Demographic variables for neighborhoods include race, median income, crime rates, and education levels.