Social Networks and Aggressive Behavior: Peer ...

Copyright 1988 by (he American Psychological Association, Inc. O012-1649/88/SO0.75

Developmental ftychology 1988, Vol. 24, No. 6, 815-823

Social Networks and Aggressive Behavior: Peer Support or Peer Rejection? Robert B. Cairns, Beverley D. Cairns, Holly J. Neckerman, Scott D. Gest, and Jean-Louis Gariepy

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

University of North Carolina at Chapel Hill Studied social networks and aggressive behavior in school in 2 cohorts of boys and girls in the 4th and 7th grades (N = 695). Measures of social networks yielded convergentfindings.Highly aggressive subjects (both boys and girls) did not differ from matched control subjects in terms of social cluster membership or in being isolated or rejected within the social network. Peer cluster analysis and reciprocal "best friend" selections indicated that aggressive subjects tended to affiliate with aggressive peers. Even though highly aggressive children and adolescents were less popular than control subjects in the social network at large, they were equally often identified as being nuclear members of social clusters. Aggressive subjects did not differ from matched control subjects in the number of times they were named by peers as "best friend," nor did the two groups differ in the probability of having friendship choices reciprocated by peers.

It has been broadly assumed that aggressive children are embedded in a familial matrix whereby negative actions support the consolidation of further hurtful, aggressive actions (Patterson, 1982; see Parke & Slaby, 1983, for a review). The finding of reciprocities in dyadic aggressive interchanges and coercive families has supported the idea that aggressive children are both the architects and the victims of their actions (Hall & Cairns, 1984; Patterson, 1982). Although the coercive social model has been most clearly elaborated for family interactions, it seems reasonable to expect that the same processes occur in social networks beyond the family (Bronfenbrenner, 1979). In particular, peer social clusters may also provide mutual support for aggressive behaviors as new social units emerge in adolescence (Cairns, 1979; Cairns, Neckerman, & Cairns, in press). To the extent that adolescents participate in the design of their social environments, they may be expected to affiliate with peers who are similar to themselves in salient life-style dimensions, including the propensity to act out toward others. Once in the close network of relationships, reciprocal processes should bring about even higher levels of similarity in aggressive behavior. The patterns of affiliation may be consolidated by social choice (selective acceptance by aggressive peers) or social default (selective exclusion by nonaggressive peers). Accordingly, "coercive clusters" in adolescence may (a) present multiple opportunities for aggressive reciprocation and escalation and (b) support a value structure that promotes aggressive actions toward other persons. Following these considerations, the dual aims of this study

This research was supported by grants from the Spencer Foundation and the National Institute of Child Health and Human Development (R01 23301). We thank Tamara R. Flinchum and Lynda Ferguson for their assistance in several aspects of this investigation. Correspondence concerning this article should be addressed to Robert B. Cairns, University of North Carolina at Chapel Hill, Department of Psychology, Davie Hall 013A, Chapel Hill, North Carolina 27514.

were to clarify the roles that highly aggressive children and adolescents play in peer social networks and to understand the functions that networks of peers play in the support of aggressive patterns. Attempts to study social relationships of aggressive children indicate that they instigate high levels of reciprocity in aggressive interactions. Within limits, aggression begets aggression in a reciprocal, escalating pattern (e.g., Hall & Cairns, l984;Raush, 1965; Toch, 1969). The mutual support of aggressive behaviors seems to be a factor in the dynamics of various coercive groups, including gangs of bullies (Olweus, 1979) and delinquents (e.g., Cohen, 1955; Giordano, Cernkovich, & Pugh, 1986). It should be noted that a different picture has been described in recent studies of children's social status. Subjects identified as "rejected" (as judged by peer ratings/nominations of likability and unlikability) have typically been found to be more aggressive than nonrejected subjects, and early identification as "rejected" is predictive of subsequent problems with aggressive behavior (Asher & Dodge, 1986; Coie & Dodge, 1983). Thus, it would appear that aggressive acts are correlated with social rejection and that rejection is correlated with the continuation of aggressive behavior. At a broader level, the association of rejection and aggression has been seen as consistent with the emphasis of sociologists Hirschi (1969) and Yablonsky (1962) on the essential social disaffiliation and disengagement of delinquent and aggressive youths. There is some evidence from studies of children, however, to indicate that dislike and popularity can coexist in the same individual and that assertive-aggressive behavior does not necessarily preclude popularity (Coie, Dodge, & Coppotelli, 1982). A subgroup of subjects labeled controversial—presumably because they obtained, simultaneously, higher-than-average scores on peer popularity and peer dislike—showed a blend of antisocial behavior and peer acceptance. This subgroup is of special interest because controversial subjects (who do not show up in large numbers) can sometimes be viewed as leaders in the peer group (Coie et al., 1982, p. 568). 815


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CAIRNS, CAIRNS, NECKERMAN, GEST, GARIEPY

Following assumptions discussed elsewhere (Cairns et al, in press; Kandel, 1978), the present research addressed three proposals on the relationship between aggressive behaviors and social affiliations. First, highly aggressive subjects were expected to be members of definable social clusters and not to differ from control subjects on this index of affiliation. Because of their abusive and coercive behaviors, aggressive subjects may be generally less popular than control subjects in the social network as a whole. On the other hand, aggressive adolescents may be accepted by other persons in the social cluster with whom they are identified. Hence, aggressive adolescents would be as likely as control subjects to have reciprocated "best friend" selections. A second proposal concerned the extent to which there is social support by peers for aggressive behaviors. Aggressive subjects may be expected to affiliate with aggressive peers. Across social clusters, there should be high levels of similarity between individuals of the same cluster with respect to aggressive expression (i.e., "homophily"). This expectation follows from the reciprocal and contagious nature of aggressive behaviors in social groups as well as the social choice and social default factors that serve to define entry into groups and help consolidate their structures. A third set of issues concerned gender differences and whether the patterns of group membership in highly aggressive girls were different from those in highly aggressive boys. Most relevant evidence indicates that the standards for the acceptability of assertive-aggressive behavior differ for boys and girls (e.g., Cairns, Cairns, Neckerman, Ferguson, & Gariepy, 1988; Savin-Williams, 1979). The different normative standards, in turn, may account for the difference in the sheer numbers of highly aggressive girls relative to highly aggressive boys. These social standards may also promote differences in the extent to which aggressive patterns are permitted to become a basis for differential peer group association. On the basis of the foregoing, it was expected that both boys and girls would show patterns of aggressive homophily, but that girls would be more vulnerable to rejection and social ostracism because of overt aggressive behavior. Studies of aggressive subjects and their social groups have suffered from a gender bias. For example, investigations of reciprocal relationships of violent subjects and studies of "gang" behavior have been traditionally limited to males (e.g., Cohen, 1955, Toch, 1969). There have been few instances where aggressive reciprocal relationships have been studied in girls (or in boys' relationships with girls) or in female "gangs" (Giordano et al., 1986). This bias is of some importance because the evidence that is available on reciprocal relationships involving girls indicates that the sex of the "other" does make a difference. Different patterns of reciprocal action have been obtained in male-female interactions relative to male-male ones (e.g., Barrett, 1979). The difference reflects the operation of a dual standard, in that girls are not supposed to be attacked by boys, although girls may attack both boys and girls. In one of the few systematic studies of adolescent delinquent gangs of girls, Giordano (1978) found within-group support for deviant norms not unlike that found in males. More recently, Magnusson (1987) has shown that affiliations with older peers play a powerful factor in accounting for the deviancy of early maturing Swedish teenage girls. Shortcomings in techniques available for social network anal-

ysis have made it difficult to describe the supportive role of peers at any age (e.g., Dunphy, 1963; Hartup, 1983; Moreno, 1934). Procedures that describe the social status of children often do not provide information about the nature of the social groups in which children participate (e.g., Coie & Dodge, 1983; Peery, 1979). Beyond categorization of children as "popular" "rejected," "isolated," "average," or "controversial," classical sociometry would seem to require information about (a) the identities of individuals within a given social cluster and (b) the number of social clusters within a microsocial network (Bronfenbrenner, 1944a, 1944b; Moreno, 1934). To this end, the present study introduced a procedure designed to capture information about the nature, status, and composition of social networks within schools. Method

Subjects A total of 695 subjects (364 girls and 331 boys) were recruited from seven public schools in two cohorts. Cohort 1 consisted of 220 fourthgrade subjects (116 girls and 104 boys; A/age = 10.2 years, SD = .57) from four elementary schools. Cohort 2 consisted of 475 seventh-grade subjects (248 girls and 227 boys; Mage = 13.4 years, SD = .58) from three middle schools. The mean family socioeconomic status on the Duncan scale (Featherman revision) was 30.2 (SD = 17.1) in Cohort 1 and 31.6 (SD = 17,8) in Cohort 2, and the full range of occupations was represented in the samples (range from 88 to 7; i.e., chair of medical center department, attorney, regional sales manager, small-business owner, truck driver, domestic worker, unemployed farm worker, etc.). Twenty-five percent of the subjects were minority status (predominantly Black). The seven schools were located in two counties: one, a suburban metropolitan area, and the other, a rural county (as classified by the 1980 U.S. census). There were no restrictions on inclusion other than consent: all children in the designated grade (fourth or seventh) in each school were included in the study if (a) the children wished to participate and (b) they and their parent or legal guardian signed a statement of informed consent. The participation rate ranged from 89% in the last junior high school assessed (132 of 149) to 50% in thefirstjunior high school (83 of 166), with an overall participation of 70% (695 of 994). The 70% of the children who consented to be subjects and the 30% who did not were compared in terms of ethnic status, sex, and probability of being nominated as highly aggressive. No systematic differences were obtained on any of these dimensions. Within the larger sample, 40 subjects, 20 girls and 20 boys, were judged by teachers, counselors, and principals to be highly aggressive (i.e., there were 20 highly aggressive subjects in each cohort). In order for an individual to be selected, he or she had to be nominated by two school personnel (teacher, counselor, or principal) who were closely acquainted with the subject. An additional group of 40 nonaggressive control subjects was identified and matched individually on the basis of sex, race, classroom attended, physical size, socioeconomic status, and chronological age.1 Priority was given to the matching variables in the ! The matching was successful on all variables (e.g., no significant differences were obtained on classroom, race, physical size, socioeconomic status, age), with one exception. The aggressive-control subjects in the fourth grade did not differ in age (10.1 vs. 10.3 years in aggressive and control girls and 10.6 vs. 10.5 years in aggressive and control boys, respectively). However, the aggressive-control subjects in the seventh grade differed (13.6 vs. 13.0 years in aggressive and control girls and 14.1 vs. 13.3 in the aggressive and control boys, respectively). To correct for any effects attributable to the age discrepancy in the older sample,

SOCIAL SUPPORT OR SOCIAL REJECTION? order of listing. In order for children to qualify for possible inclusion in the matched-control group, they could not have received a school nomination for being highly aggressive. As a check on the validity of the school nominations, pair-wise observations of each aggressive-control pair were conducted over a 4-day period, with extensive observations daily over two contexts. These observations (not reported in this article) indicated that the aggressive subjects and nonaggressive controls differed markedly in observed aggressive interchanges in the fourth and seventh grades.


Measures Multiple assessment procedures were used in order to obtain convergent evidence on the primary hypotheses {following the research strategy outlined in Cairns, 1986, and in Cairns & Cairns, 1988). The measures included in this report were as follows: peer reports of the individual's role in the school social networks; a social cognition interview on recent conflicts; Interpersonal Competence Scale-teacher (ICS-T) tests, which yielded factor scores on aggression, popularity, and academic competence factors; Interpersonal Competence Scale-self (ICS-S) tests, which yielded self-perception factor scores on the same factors; peer nominations for conflict instigation; and peer affiliations, as determined by "best friend" choices. These procedures and the measures that they generate have been described elsewhere (e.g., Cairns & Cairns, 1984; Cairns, Perrin, & Cairns, 1985). The measures included the following: Social network assessment. An individual, tape-recorded interview was conducted with each subject. A semistructured protocol was followed by the interviewer. The social networks in which subjects were involved were plotted on the basis of information obtained from subjects and peers in four sections of the interview. In one section, subjects and peers were asked, "Now tell me about your (school, class). Are there some people who hang around together a lot?" Follow-up probes elicited specific information about the perceived makeup of the clusters. As indicated in Cairns et al. (1985), high levels of intersubject agreement were obtained in the identification of cluster membership. In a second part, subjects were asked about any persons who were "not members of any groups." The persons named by the subject, including themselves, were counted as having been nominated for social isolation. In a third section, subjects were asked to identify their "best friends." For peer-friendship analyses, all choices of each child were listed. By comparing friendship choices across subjects, it was possible to determine which friendships were reciprocated and which were not. In a fourth part, subjects were asked to nominate persons (both male and female) who gave them "trouble" or "bothered" them. These nominations were followed by a request to provide a detailed and concrete account of a recent conflict with a peer (both male and female). Social cluster identification. In a preliminary study in this series, Cairns, Perrin, and Cairns (1985) used a decision rule procedure in order to identify the peer clusters in a social network and the relations among persons within each cluster. In the decision rule method, each respondent generated a "social map" for persons in their school grade. Because there was typically a high level of agreement across informants, it was possible to combine information across respondents and build a "composite social map" of the groups that existed in the classroom. It was a decision rule procedure because arbitrary standards were adopted (a) to order the cases into groups, (b) to judge whether borderline cases belonged to one or more social clusters, and (c) to determine which

persons were central to the cluster (nuclear members) and which were on the edge of membership (peripheral members). The present quantitative procedure evolved from the decision rule method. It was introduced in order to develop a broadly applicable technique for describing relations between persons and the structure of social networks, with minimal reliance on intuitive judgments. (A separate article, Cairns, Kindermann, & Gariepy, 1986, describes the method and alternative quantitative procedures.) In brief, four successive matrices were constructed for each classroom in order to arrive at the latent structure of the classroom networks. First, a raw recall matrix was constructed from the free recall of social groups by all subjects (male and female) in the classroom: each subject-respondent indicated which persons in the school belonged to which groups (see Table 1 in Cairns et al., 1985, for one recall matrix where each columnrefersto a different respondent and the children-to-be-clustered are listed down the rows). Second, each raw recall matrix was transformed to a cluster co-occurrence matrix (i.e., a symmetric matrix that summarized the frequency with which each person was named to the same group as each other person in the school and where the cells indicate the number of times two persons "co-occurred" in the same cluster). The rows of the cooccurrence matrix consisted of all children-to-be-clustered (including the subjects themselves), and the columns of the matrix were the same as the rows. The entries summarized the number of occasions that Person / has been identified by respondents to be in the same social group as Person j . The diagonal of the co-occurrence matrix contained the number of occasions that a given person was named to any group (i.e., subjects are considered to be members of all groups to which they have been named). Third, a correlation matrix was generated by intercorrelating the columns of the arrays of the co-occurrence matrix. Each correlation reflected the level of correspondence between the cluster membership scores of Subject A with those of Subject B. Transitivity typically was found in groups of individuals. That is, if Subject A obtained a significant positive correlation in patterns of co-occurrence with both Subject B and Subject C, then Subject B typically obtained a significant positive correlation with Subject C. This empirical transitivity facilitated the assignment of individuals to preliminary social clusters (i.e., persons who were judged by their peers to "hang around together"). Fourth, a Lambda-X (LX) LISREL matrix was constructed on the basis of the preliminary cluster descriptions, where each individual-tobe-clustered was treated as an "observed" variable, and the "latent" variables were clusters of persons. The aim of the LISREL was to clarify the social structure in those classes where the social clusters were not clearly defined, often because individuals may appear simultaneously in two or more clusters. In establishing the initial LX matrix, each person was declared free for a single latent variable (cluster) and fixed for all other latent variables (clusters). In thefinalstep, LISREL VI estimates of optimal factor loadings on the LX matrix were determined (Joreskog & Sorbom, 1984). When adjustments to the LX model were required, they usually involved relaxing the model so that a subject could simultaneously appear in two latent variables (i.e., to become members of two social clusters at the same time). Decisions about relaxing the model or relocating subjects were made on substantive, a priori grounds by inspection of the raw recall matrix. The goodness-of-fit measure from the LISREL solution was consulted as a guide to determine whether the fit was substantially improved by the adjustment.2 These "latent vari2

all analyses were conducted with and without age as a covariate. In no instance did covariance analyses (controlling for age) yield outcomes that were significantly different than the ANOVAS.

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The LISREL Goodness-of-Fit Index (GFI), root mean square residual (RMR), and other parameter estimates were used primarily for description in the present application. The properties of the correlational matrices derived from the co-occurrence matrices preclude standard LISREL inferential interpretations. Nonetheless, the LISREL VI program provides a guide for comparing the effects of relocating individuals from


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ables" defined the social network in each extended classroom ("extended" because the method permitted persons in the school other than those in the classroom to be cluster members). After the social clusters in each classroom were identified, the relative centrality of each cluster and of each member of the separate clusters was determined. The index to centrality was simply the number of times that a given person was named to a cluster. Using the average of the two persons in the cluster who received the highest number of nominations, the rank of the cluster was determined {i.e., high-, medium-, and lowsalient clusters). Similarly, nomination frequency was used to determine the status of individuals within their clusters: nuclear, secondary, or peripheral. Clusters (or persons) in the upper 30% rank of nominations were considered to be high salient (or nuclear rank), those in the lowest 30% were considered to be low salient (or peripheral rank), and those in the mid-range 40% were considered to be medium salient (or secondary rank). In sum, the method is a quantitative technique that yields information about (a) the social clusters within each classroom, (b) the identity of persons who are members of each cluster and their relations to each other, (c) the relative centrality of each cluster, (d) the relative rank of persons within the clusters, and (e) the extent of dual cluster memberships. For replication and reliability purposes, the entire network analysis was repeated for all designated classrooms using the decision rule analysis described in Cairns et al. (1985). The decision rule method of initial cluster estimation is relatively easy to compute: It preserves the identity of the other members of the social network and captures much of the salient information about classroom relationships. (It does not involve the construction of the co-occurrence, correlational, and LX matrices.) In the present data set, the two analyses—quantitative and decision rule—yielded virtually identical results and identical summary conclusions. The quantitative method, although more laborious and expensive in computer time, has an advantage in objectivity and freedom from subjective decisions about cluster membership. It also provides a quantitative guide for deciding whether the solution is improved by permitting joint cluster membership for particular persons. Accordingly, the results of the quantitative method are reported here.3 Peer nominations for conflict instigation. In the individual interview, subjects were asked the questions, "Has anybody bothered you recently or caused you any trouble? Or made you mad?" Depending on the sex of the individuals who were identified in the first question, the child was asked about the opposite sex and whether any boys or girls had bothered them or caused them trouble. In follow-up probes, the names of the other persons were established. This information was tape recorded, transcribed, tabulated, and coded with the aid of class and

one cluster to another as well as the effects of joint cluster membership. For purposes of description, the mean GFI across 63 classroom analyses (32 classrooms for boys and 31 classrooms for girls) was relatively high (.92), and the mean RMR was low (0.14), indicating that the LISREL vi models of networks provided a close fit to the observed correlational matrices. It is of interest to observe that no grade differences were obtained in these measures of network definition, but girls obtained a significantly higher mean GFI: for boys M = .90 and for girls M = .94, F( 1, 29) = 9.00, p < .01. Similarly, there was a significant sex difference in the average RMR, SO that expected/observed differences were smaller for girls than for boys: for boys M = . 16 and for girls M = . 12, F\ 1,29) = 6.50, p < .05. The network analyses for the 31 boys were individually matched (by classroom) to the network analyses for the 31 girls (i.e., the single all-male classroom was eliminated for the purposes of this comparison). This sex difference in the definition and clarity of social networks is consonant with the idea that girls have more easily identified social clusters and group membership than boys (Gilligan, 1982). It is also consistent with the more frequent use of social ostracism by girls.

school enrollment lists (there was more than 99% agreement by independent judges). The number of occasions that a given subject was named by peers as having caused a conflict was summarized over all male and female respondents in order to obtain a peer conflict nomination score. Because entire schools were sampled in the fourth and seventh grades, it was possible to compute the z score for the peer nominations of each subject (i.e., every subject was compared with others of the same sex in the schools in which they were enrolled). Conflict nomination scores were available from female peers, male peers, and summary female and male scores. Interpersonal Competence Scale-Teacher. The subject's teacher (or coteachers) completed the Interpersonal Competence Scale (Cairns & Cairns, 19 84). The ICS-T consists of 15 items that pertain to aggressiveness, popularity, affiliation, and academic competence. Each item requires the respondent to describe the subject on a 7-point scale. A factor analysis (varimax rotation) of the ICS-T items indicates that three distinct factors emerge with high levels of communality in all age-sex levels. The three item clusters were aggression, popularity, and academic competence. A LISREL measurement model indicated an excellentfitof the items to these three factors. For example, at the seventh-grade level, the hypothesized structural equation with three latent variables yielded a Goodness-of-Fit Index of .98, The chi-square with 17 degrees of freedom was 13.83 (p = 0.67), confirming the goodness-of-fit analysis. This LISREL solution was representative of those conducted at the other grade levels, indicating that three separate factors (aggressiveness, popularity, and academic competence) may be reliably identified in the ICS-T across this age range. Of special importance to this research was the ICS-T factor of "aggressiveness" (which consisted of three items; namely, "gets in trouble at school," "fights a lot," and "always argues"). The concurrent interrater reliabilities for the aggressive factor scores in assessments were r(35) « .82, and r(26) = .78 (Fisher's Z-averaged r = .81). These two-person interrater reliabilities compare favorably with those reported in other studies (e.g., Olweus, 1979) and prior reliabilities reported using the present scale (Cairns & Cairns, 1984). The construct validity of this aggressive factor score and its linkage to other external measures of aggressive behavior has been established in companion studies (Cairns & Cairns, 1984,1988). Comparable reliabilities were obtained for the popularity and academic factors. The items were reseated on the 7-point scale so that the lower the ICS-T factor score, the higher the social desirability. That is, for the aggressive factor, high factor scores reflected high aggressiveness; for the popularity factor, low factor scores reflected high popularity. Interpersonal Competence Scale-Self. Each year subjects completed a self-descriptive test form of the Interpersonal Competence Scale (ICSS). A booklet was prepared with the items printed on separate pages. Other than the inclusion of distractor items and booklet format, the subjects' tests (ICS-S) were identical with those completed by adults (ICS-T). The scales themselves had been developed through extensive pilot testing. The vocabulary and instructions were within the range of fourth-grade students. If necessary for comprehension, the interviewer read the item aloud. The same items were used across all years, and the year-to-year stabilities are reliable (Cairns et al., 1988).

Procedure Subjects were interviewed and tested in the school that they attended. Confidentiality was assured, and subjects were told that they could decline to answer any question or withdraw at any point. At the conclusion of the interview, they were given the choice of a school-related item obtained from one of the universities in the region (e.g., notebook, pen, 3 A detailed description of the method and rationale will be made available on request (Cairns, Kindermann, & Gariepy, 1986),

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SOCIAL SUPPORT OR SOCIAL REJECTION? pencil). Teachers were given minimal instructions on rating, except to use the full range of the scale if appropriate. Society for Research in Child Development ethical standards were followed in all aspects of the investigation.

Table 2 Popularity of Aggressive and Nonaggressive Groups as a Function of Grade and Sex Measures of popularity


Results

ICS-T (Teacher)

The research outcomes are summarized in three sections. In the first part, behavioral differences and similarities among the high-aggressive and the matched control groups are described. The second part focuses on aggressive children and their roles in the social network. The third part analyzes the role of peer social structures in the promotion and regulation of aggressive patterns. Gender similarities and differences are discussed in each section. Characteristics of Aggressive and Matched Control Subjects Subjects who had been placed in the high-aggressive group differed from those in the matched control group on several behavioral dimensions related to aggression and popularity. As shown in Table 1, subjects in the aggressive condition scored higher than those in the control condition on all measures of aggression used. The aggression-control differences were highly reliable in the ICS-T (teacher) assessments of aggression, 7*1(1, 36) = 34.68, p < .001, in peer nominations for aggressive conflicts, t\\t 36) = 29.62, p < .001, and in the ICS-S (self) ratings of aggression, F{\, 36) = 13.34, p < .001. Parallel effects were obtained in both grades and in both girls and boys. For the ICS aggressive factor measures, only the main effects of condition (aggression vs. nonaggression) were reliable; no other main effects or the interactions reached statistical significance. In the case of the summary peer nominations, there was also a reliable

Subjects/ group Boys Aggressive 4th grade 7th grade Control 4th grade 7th grade Girls Aggressive 4th grade 7th grade Control 4th grade 7th grade

ICS-S (Self)

M

SD

M

SD

4.12 4.23

1.73 1.46

2.42 3.45

1.00 1.08

2.73 3.73

1.59 1.23

2.38 3.33

0.80 1.31

4.32 4.53

1.38 1.41

2.80 2.80

1.65 0.86

3.03 3.13

1.09 0.69

2.30 2.35

0.87 0.74

Note. ICS = Interpersonal Competence Scale.

gender effect, in that boys were nominated for causing conflicts more often than girls, F(\f 36) = 4.87,p < .05.4 Aggressive subjects were also less popular than peers in the control group, as evaluated using the ICS-T popularity factor scores (Table 2). The main effect of condition (aggression vs. control) was highly reliable, F{\, 36) = 21.08, p < .001. No interactions were statistically reliable, nor were the main effects of grade or gender. Aggressive subjects were also more frequently disliked by peers, as inferred from nominations of peers who saw themselves as being bothered and bullied by them (see Table 1, "Conflict: peer" column). These outcomes are consistent with previousfindingsthat aggressive subjects are likely to be seen as generally unlikable and unpopular (e.g., Coie & Table 1 Characteristics ofthe Aggressive and Nonaggressive Groups as Dodge, 1983). Self-ratings on popularity, however, yielded parallel outcomes in the two groups. Aggressive subjects rated a Function ofGrade and Sex themselves to be as popular as control subjects in the ICS-S asMeasures of aggression sessment. Moreover, there were no differences between the aggressive subjects and matched-control subjects in the number ICS-T Conflict of occasions that peers named them as best friend (see below). (Teacher) (Peer) ICS-S (Self) Subjects/ group Boys Aggressive 4th grade 7th grade Control 4th grade 7th grade Girls Aggressive 4th grade 7th grade Control 4th grade 7th grade

M

SD

M

SD

M

SD

5.83 5.17

1.34 0.67

4.10 1.90

2.56 1.91

3.95 4.11

0.78 1.15

3.50 3.80

2.29 1.75

1.20 0.70

1.40 1.25

3.73 3.47

1.34 1.04

5,07 5.50

0.71 1.33

2.80 1.90

1.81 2.56

4.53 4.03

1.13 1.01

2.60 3.03

1.49 1.75

0.80 0.50

1.03 0.71

3.23 2.97

0.99 0.96

Aggression, Social Roles, and Rejection Two analyses of the social roles of highly aggressive and control subjects were permitted by the data: peer-defined social clusters and peer judgments of isolation/rejection from the social network. Social cluster analysis. The social clusters in the two 4

Note. ICS = Interpersonal Competence Scale.

Beyond the main effects attributable to the aggressive-control distinction, further analysis of the peer nominations indicated that (a) boys were reliably less likely to nominate girls than vice-versa and (b) there was a significant decrease in total nominations by girls as they grew older. In all nomination indices—whether generated by boys or girls— the differences between the aggressive- and matched-control groups were highly significant (p < .005).


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different grades were identified by peers. Confirming the results of preceding work, the social clusters identified in the cognitive social maps were predominantly (a) same-sex in composition and (b) reliably identified across individuals, even when persons were not themselves members of the clusters (Dunphy, 1963; Cairns et al., 1985). The cluster identification method was used to determine whether aggressive (or control) subjects were full members of the extent social clusters, peripheral members of social clusters, or were not named as members of any social cluster. The results of this classification are shown in Table 3. For summary purposes, subjects who were nuclear members of high salient clusters were classified as nuclear, subjects who were secondary members of high-salient clusters or nuclear/secondary members of medium-salient clusters were classified as secondary, and subjects who were in low-ranked clusters or peripheral members of any cluster, regardless of status, were classified as peripheral. Subjects not named at all were classified as isolated. No reliable differences were obtained between subjects in the aggressive and control conditions in type of cluster membership, using chi-square analyses. Across all age-sex groups, 95% (38 of 40) of the highly aggressive subjects were members of some social clusters, as identified by peers. Approximately onethird (12 of 40) were nuclear members of high-salient groups, and another 45% were secondary members in the social network (i.e., secondary members of high-salient groups or nuclear/secondary members of middle-salient groups). One-fifth of the total (20%) were peripheral members of the social network (i.e., members of low-status groups or peripheral "hangers on" to high-salient groups). Only 5% seemed to be removed from the social structure. These proportions were virtually identical with those of the matched control subjects, except that none of the control subjects were perceived to be removed entirely from the social structure (the difference is not reliable). No difference

Table 3 Cluster Membership of Aggressive and Nonaggressive Subjects as a Function of Grade and Sex Grade/group 4th Aggressive Girls Boys Control Girls Boys 7th Aggressive Girls Boys Control Girls Boys Sum {4th and 7th) Aggressive Control Total

Nuclear

Secondary

Peripheral

Isolate

.10(1/10) .40(4/10)

.60(6/10) .40(4/10)

.30(3/10) .20(2/10)

.00(0/10) .00(0/10)

.20(2/10) .20(2/10)

.70(7/10) .50(5/10)

.10(1/10) .30(3/10)

.00(0/10) .00(0/10)

.40(4/10) .30(3/10)

.40(4/10) .40(4/10)

.10(1/10) .20(2/10)

.10(1/10) .10(1/10)

.50(5/10) .50(5/10)

.30(3/10) .30(3/10)

.20(2/10) .20(2/10)

.00(0/10) .00(0/10)

.30(12/40) .45(18/40) .20(8/40) .05(2/40) .35(14/40) .45(18/40) .20(8/40) .00(0/40) .33(26/80) .45(36/80) .20(16/80) .03(2/80)

Note. Numbers in parentheses represent the number of subjects (out of total number) rated as being in the various clusters.

Table 4 Mean Nominations for Social Isolation by Peers by Sex, Grade, and Aggressive Group Status Aggressive condition Subjects Boys 4th grade 7th grade Summed over grade Girls 4th grade 7th grade Summed over grade

Nonaggressive condition

M

SD

M

SD

1.20 0.60 0.90

1.32 1.26 1.29

1.00 0.30 0.65

0.82 0.48 0.67

1.80 0.80 1.30

3.08 1.23 2.35

0.70 1.80 1.25

1.89 2.53 2.23

in category representation between the aggressive and control groups was statistically significant as determined using chisquare analyses (Table 3).5 Given that highly aggressive subjects were more likely to be nominated by peers for causing conflicts, it seems reasonable to expect that fewer peers would wish to be affiliated with them. This would lead to a reduction in the overall size of the clusters in which aggressive subjects were members. There is some modest support for this expectation. Among subjects who were members of social clusters, the mean numbers of persons in the clusters of the highly aggressive and matched control subjects were 5.11 and 5.72, respectively. However, this difference was not statistically reliable, F(\, 34) = 2.84, p> .05. Although aggressive girls tended to be in smaller clusters than control girls, none of the main effects (sex, grade, or risk condition) or their interactions were statistically significant. Peer judgments of isolation. In addition to describing the social structure, all subjects were asked to specify any persons who did not belong to any social group (i.e., those who were rejected or isolated). The number of times that each aggressive subject and his or her matched control was named as being outside the social network was determined. The means for the sexage-aggressive groups are shown in Table 4. The peer judgments of social isolation indicated no reliable effects, either as main factors or in interaction. Peer judgments of isolation may be used to identify particular isolated subjects. A conservative estimate of isolation may be obtained if a given subject was explicitly identified by at least 4 of his or her peers as having no social group. Overall, 10% (4 of 5 The clusters in Table 3 cumulated information from all respondents in the study, including the subjects themselves. An argument can be made that the individual's own self-assignments should be omitted because of possible self-enhancement distortions, particularly among subjects who are peripheral (Cairns, Neckerman, & Cairns, in press). When the clusters were recomputed without the subjects' self-assignments, no reliable changes were observed. As expected, more persons became categorized as isolated when the additional respondent (i.e., the self) was eliminated (5 of 40 in the combined aggressive group and 1 of 40 in the combined control group; 8% overall in combined groups). The differences were not statistically significant using chi-square analyses, either overall or in specific age-condition comparisons.

821

SOCIAL SUPPORT OR SOCIAL REJECTION? 40) of the highly aggressive subjects and 8% (3 of 40) of the nonaggressive control subjects qualified for this conservative judgment of isolation. The difference was not reliable.

Table 5 Relationships Between the Subject's ICS-T Aggressive Factor Score and Mean ICS- T Scores of' 'Best Friends'' Friendship reciprocity


Peer Social Organization and Aggression The question addressed in the next set of analyses concerned whether highly aggressive children and adolescents get together to form cliques. Do aggressive children tend to hang around together? This matter was investigated by intraclass correlational analyses of the social clusters identified through the quantitative network analysis. To determine if the clusters themselves differed in mean levels of aggressive expression, the aggressive factor scores (i.e., ICS-T) of the nuclear members of each group were determined.6 An intraclass correlational analysis of the similarity of ICS-T scores of the nuclear members of each social cluster permitted a determination of within-cluster similarity on aggressive scores. Intraclass coefficients were computed separately for the two grades and two sexes for the clusters in all classes. All levels of clusters (high, medium, and low) were included in the analysis. The intraclass coefficients using the 1CS-T aggressive factors indicated that nuclear members of the male clusters in the fourth grade were highly similar in terms of their ratings of aggression: the intraclass correlation was .75, F\22, 29) = 8.57, p < .001. For fourth-grade girls, however, the intraclass correlation for aggression was not significant, r' — .03, F{26, 39) ~ 1.07, p > . 10. The same analysis was completed for the seventh grade. In the early adolescent cohort, the intraclass correlation for aggression was significant both for males, r' ~ .43, F(48, 78) = 2.97, p < .001, and for females, f = .37, F(54,97) = 2.60, p