Elsevier

Social Networks

Volume 38, July 2014, Pages 41-49
Social Networks

A behavior genetic analysis of the tendency for youth to associate according to GPA

https://doi.org/10.1016/j.socnet.2014.01.001Get rights and content

Highlights

  • Research suggests peers resemble one another on a host of traits.

  • Cognitive ability often shows moderate-to-strong correlation between peers.

  • Our findings reveal a correlation among peers in respect to their GPA.

  • ACE model results show genetic factors explain 72% of the variance in peer GPA.

Abstract

Behavior genetic research has revealed that many “environmental” variables are partially influenced by genetic factors. Known as gene–environment correlation (rGE), this line of scholarship provides insight on how and why individuals select into certain environments. Juxtaposing this body of evidence with research on peer group homophily—the tendency for peers to resemble one another on certain traits such as academic ability—raised two research hypotheses: (1) youth will associate with peers who receive grades similar to themselves (i.e., homophily for GPA); and (2) a portion of the variance in peer group GPA (i.e., the peer network average GPA) will be explained by individuals’ genetic self-selection into the peer group (rGE). The results supported both hypotheses by showing a strong predictive relationship between the target individual's GPA and that of his/her peers and by revealing that 72% of the variance in peer group GPA was explained by genetic influences.

Section snippets

Homophily in peer groups

A large body of evidence has revealed that members of a peer group tend to resemble one another on a host of traits. Evidence from psychology reveals, for example, that individuals tend to resemble their peers on measures of physical characteristics, attitudes, and aspirations (Caspi and Roberts, 2001, Harris, 1998, McPherson et al., 2001). Similarly, sociological and criminological evidence indicates that peers tend to resemble one another on measures of delinquent and criminal involvement (

Cognitive ability as a sorting factor

Findings from one stream of research speak to the intellectual similarity of individuals within a peer group (Bonney, 1942). Two classic studies are particularly relevant when considering the level of similarity between peers on measures of cognitive ability. In the first study, Almack (1922) performed one of the first analyses examining intelligence as a peer-sorting factor. Participants were drawn from grammar and middle schools in San Jose, California and were administered IQ tests. Next,

Genetic influences on peer group selection

Building on principles of evolutionary biology, Rushton et al. (1984) proposed a genetic similarity theory which states that organisms detect other genetically similar organisms via the manifestation of genotype through phenotype (e.g., behavior) and exhibit favoritism and protective behaviors toward those similar others. In other words, the genetic influences are expressed as phenotypic outcomes, or signals, that are then noticed by similar others. The more phenotypically (genetically) similar

The current study

Much attention has been given to the role that peers play in personality development (Harris, 1998) and research findings have consistently shown that all aspects of human development are driven, at least partially, by genetic factors (Turkheimer, 2000). Among these genetically influenced traits is one's cognitive ability (Plomin, 1999, Plomin and Spinath, 2004). Juxtaposing the knowledge that between-individual differences in cognitive ability are partially the result of genetic influences

Data

Data drawn from the National Longitudinal Study of Adolescent Health (Add Health; Harris, 2009) were analyzed in the current study. The Add Health is a prospective, nationally representative study of American adolescents who were enrolled in middle or high school during the 1994–1995 academic year. Sampling began at the school level and, from a list of nearly 30,000 schools, 132 schools were selected for inclusion in the study. On a designated day, all students attending each of the schools

Analysis plan

The analysis unfolded in three interrelated steps. First, the correlation between the target respondents’ grades/GPA and the average GPA for the peer network to which they belonged was examined in a series of multiple regression models (Hypothesis 1). These models employed ordinary least squares regression because the dependent variable, peer network average GPA, approximated a normal distribution. All target respondents in the wave 1 in-home data file who had valid network data were analyzed

Findings

Presented in Table 2 are the results from five regression models where the peer network average GPA served as the dependent variable and all in-home participants with non-missing data at wave 1 were analyzed. This table reveals one main finding: the target respondent's grade in all four subjects and the target respondent's overall GPA is positively and significantly related to the peer network average GPA. Standardized regression coefficients are presented in brackets to allow for the

Discussion

There is little doubt that peers resemble one another on myriad traits. Indeed, much research has reported a correlation between peers on a range of personality characteristics, health outcomes, behaviors, and even physical attractiveness (McPherson et al., 2001). What has yet to be determined is why peers resemble one another so closely. Undoubtedly, much of the extant research can be explained in a causal framework. The work by Christakis and Fowler, 2007, Christakis and Fowler, 2008 displays

Acknowledgements

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for

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