Many school-based interventions have been aimed at alcohol use prevention among youth, but with limited effectiveness.1,2 One potential avenue for making school-based drinking interventions more effective is through the use of social multipliers. A social-multiplier effect is produced when policies take advantage of the tendency of individual behaviors to vary with the behavior of the reference group.3 For example, recent research in the area of obesity suggests that young people’s social networks may be used as social multipliers, so that the benefits of obesity prevention activities can be extended beyond the direct target of the intervention.4,5 This approach of targeting social networks is likely to be cost-effective because scarce resources could be spent on reaching influential persons and changing their behaviors, rather than spreading efforts more thinly across all students. For example, a given funding level may be sufficient if it fully involves only 10% of students, whereas it might be insufficient if spread over 100% of students. In the former case, there might be a smaller number of influential -dents (eg, peer leaders) that could diffuse prevention messages and norms.6,7 However, identifying influential students is key to this strategy. In this paper, we start with the assumption that identifying overlapping friendship networks is too complex and time-consuming to be used as part of a broadly implemented intervention. Instead, we focus on the distribution of drinking behavior within grade levels at schools. Our primary goal is to address the questions: Which points in the drinking distribution, within school and grade, are important in the “contagion” of drinking over time? Are students who are extreme in drinking behavior more influential who are average or normal with regard to drinking more influential? Alcohol use, the focus of our investigation, is an important problem to address at younger ages because early-onset drinking is associated with problem drinking behaviors later in life. It is a well-replicated finding that the younger a person starts drinking, the greater the risk for alcohol-related problems.8,9 These problems include impaired brain development and intellect, alcohol-related cirrhosis, and alcohol dependence.5,9,10 Alcohol use also has immediate consequences for adolescents, including increased risk for traffic crashes, crime, unintentional injury, disease, risky sexual behavior, academic problems, depression, homicide, and suicide.11,12 Drinking is also a social behavior. Although some reasons to drink are intrapersonal, such as personality type and social skills,11 many influences to drink are social, including prevalence of drinking in the home, in the community, and among peers.12 Major social influences among adolescents are family members, peers, school colleagues and personnel, and media models.13–15 Adolescents are thought to observe, bond to, and in turn model the social behaviors of those who are influential. Peers are thought to be the most significant social-risk factor in adolescent experimentation with alcohol and drugs—more important than the influence from parents.13,16 For example, Keefe17 documented that as youths age, parental influence on sub -stance use decreases, but peer influence remains strong and consistent. Peer influence on substance use is thought to occur through several avenues. In terms of socialization, adolescents may adjust their behaviors based on attitudes and behaviors of others in the surrounding environment.18 There is also evidence for a false consensus effect among adolescents in which adolescents overestimate peer acceptance for drugs or alcohol as a social norm,19,20 with some studies showing that perceived use among peers is more influential for behavior than actual use.21 Finally, in terms of self-selection, adolescents may choose to associate with peers who are similar to them and who readily have drugs or alcohol available.22 Fortunately, focusing on the distribution of drinking behavior among grades within schools not only sidesteps the effort needed to identify peer networks, but also allows us to avoid selection problems because grade-level peers are assigned rather than selected. Our research questions were as follow. First, who has more influence on the alcohol consumption of classmates: students who are extreme for drinking, or students who are average or normal with regard to drinking? Second, do these effects differ by gender, or according to whether peers’ cognitions (intentions) versus actual behaviors are used as the marker of drinking? Last, is there evidence that either extreme or average drinking behaviors or intentions actually change the distribution of drinking behaviors in this age-group over time, highlighting their role as social multipliers for drinking? One hypothesis is that students in a grade or in a school gauge their behavior against that of higher-risk students, with the idea that anything up to that level is “okay.” On the other hand, students may gauge their behavior on the grade average. If the former hypothesis is true, scarce resources could be concentrated on the extreme students, which would lead to a social-multiplier effect because everyone else will be influenced.