Conference Agenda

Research on social norms shows that targeting perceptions of inclusive and diverse norms can be a fruitful method for promoting positive intergroup relations. However, despite this promising earlier research, it is important to better understand how social norms that promote positive intergroup relations can be spread effectively throughout the wider community. Individuals within social networks whose behaviors strongly affect perceptions of social norms, referred to here as social referents, may be important to engage in interventions to effectively spread information and innovations within social networks. Building on this notion, we evaluated our school intervention from the INCLUSIVITY project (www.inclusivitynorms.com). We implemented two waitlist-controlled intervention trials in five high schools (n = 3,911, aged 10-19); two of these schools were at high risk for conflicts between ethnic and religious groups. RSiena was used to examine intervention effects in school networks and to control for confounding processes (e.g., friendship influence). In intervention schools, social referents increased their friends’ respect and tolerance toward discriminated groups and also enhanced perceived inclusive and diverse social norms, even after controlling for friendship influence. No evidence of outsized influence from social referents was found in control schools. Furthermore, evidence for school-level changes was limited and inconsistent. Thus, targeting social referents may be a promising strategy to promote tolerance and positive intergroup relations among friends, yet it has limited potential to change intergroup tolerance at the school level.

Powering Up is a novel school-based intervention that utilizes three sources of power to combat peer victimization in middle school: (1) Why Power is a 12-lesson curriculum designed to alter the maladaptive attributions of at-risk victims; (2) Friend Power uses experimental techniques to build friendships between victims and influential peers in their grade; and (3) Peer Power harnesses the power of these influential youth to change peer norms about the acceptability of bullying. The current research utilizes longitudinal social network analysis (SNA) approaches such as Siena and Latent Space Modeling to examine diffusion and peer influence effects among Powering Up participants in three U.S. middle schools (N=1004). One notable finding from Peer Power was that closeness to peer leaders in the network significantly increased participants’ endorsement of defending behaviors. Various other applications of these dynamic tools will be explored using pre- and post-intervention data from Powering Up, and the role of SNA in conducting peer-led interventions will be discussed.

Selection and influence processes play a key role in shaping how students group based on achievement. Previous research has documented both mechanisms at play in academic achievement, but most studies rely on self-reported grades rather than valid measures of cognitive ability. We argue that cognitive ability itself is not directly contagious among students. Instead, we hypothesize that the observed achievement clustering is driven by learning-related behaviors, such as classroom participation. To test this, we analyze a nationally representative sample of more than 2,000 Czech 6th graders and track their academic and behavioral changes over the course of a year. We use item response theory (IRT)-based cognitive scores in mathematics and Czech language at two time points, along with measures of classroom participation. We apply stochastic actor-oriented models (SAOMs) to examine both selection and influence processes in student networks. Preliminary results from multi-group SAOMs indicate that students exhibit selection and influence based on IRT-based achievement. However, when classroom participation is included in the model, it emerges as the primary factor driving selection and influence, while direct achievement-based effects diminish. These findings suggest that behavioral engagement in learning rather than cognitive ability determines academic clustering among peers. At the conference, we will extend our analysis using a random-effects SienaBayes model to further disentangle these dynamics and provide deeper insights into the social processes underlying academic success.