social networks and aggressive behavior

8/14/2019 Social Networks and Aggressive Behavior

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Developmental ftychology1988, Vol. 24 , No. 6 , 81 5-823 Copyright 1988 by (he American Psychological Association, Inc.O012-1649/88/SO0.75

Social Networks and Aggressive Behavior:Peer Support o r Peer Rejection?Robert B. Cairn s, Beverley D. C airns, Holly J. Neckerm an, Scott D. Gest, and Jean-Louis GariepyUniversity of No rth C arolina at Chapel Hill

Studied social networks and aggressive behavior in school in 2 cohorts of boys and girls in the 4thand 7th grades (N = 695). Measures of social netw orks yielded convergentfindings.Highly aggressivesubjects (both boys and girls) did not differ from matched control subjects in terms of social clustermembership or in being isolated or rejected within the social network. Peer cluster analysis andreciprocal "best friend" selections indicated that aggressive subjects tended to affiliate with aggressivepeers. Even though highly aggressive children and adolescents were less popular than control subjectsin the social network at large, they were equally often identified as being nuclear me mbers of socialclusters. Aggressive subjects did not differ from matched control subjects in the number of timesthey were named by peers as "best friend," nor did the twogroups differ in the probability of havingfriendship choices reciprocated by peers.

It has been broadly assum ed th at aggressive children are em-bedded in a familial matrix whereby negative actions supportthe consolidation of further hurtful, aggressive actions (Patter-son, 1982; see Parke & Slaby, 198 3, for a review). The findingof reciprocities in dyadic aggressive interchanges and coercivefamilies has supported the idea that aggressive children are boththe architects and the victims of their actions (Hall & Cairns,1984; Patterson, 1982). Although the coercive social model hasbeen most clearly elaborated for family interactions, it seemsreasonable to expect that the same processes occur in socialnetworks beyond the family (Bronfenbrenner, 1979).In particular, peer social clusters may also provide mutualsupport for aggressive behaviors as new social units emerge inadolescence (Cairns, 1979; Cairns, Neckerman, & Cairns, inpress). To the extent that adolescents participate in the designof their social environments, they may be expected to affiliatewith peers who are similar to themselves in salient life-style di-mensions, including the propensity to act out toward others.Once in the close network of relationships, reciprocal processesshould bring abou t even higher levels of similarity in aggressivebehavior. The patterns of affiliation may be consolidated by so-cial choice (selective acceptance by aggressive peers) or socialdefault (selective exclusion by nonaggressive peers). Accord-ingly, "coercive clu sters" in adolescence may (a) present multi-ple opportunities for aggressive reciprocation and escalationand (b) support a value structure that promotes aggressive ac-tions toward other persons.

Following these considerations, the dual aims of this study

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

were to clarify the roles that highly aggressive children and ado-lescents play in peer social networks and to understand the func-tions that networks of peers play in the support of aggressivepatterns. Attempts to study social relationships of aggressivechildren indicate tha t they instigate high levels of reciprocity inaggressive interactions. Within limits, aggression begets aggres-sion in a reciprocal, escalating pattern (e.g., Hall & Cairns,l984;Raush, 1965; Toch, 1969). The m utual sup port of aggres-sive behaviors seems to be a factor in the dy namics of variouscoercive groups, including gangs of bullies (Olweus, 1979) anddelinquents (e.g., C ohen, 1955; Giordano, Cernkovich, & Pugh,1986).It should be noted th at a different picture ha s been describedin recent studies of children's social status. Subjects identifiedas "rejected" (as judged by peer ratings/nom inations of likabil-ity and unlikability) have typically been found to be more ag-gressive than nonrejected subjects, and early identification as"rejected" is predictive of subsequent problems with aggressivebehavior (Asher & Dodge, 1986; Coie & Dodge, 1983). Thu s,it would appear that aggressive acts are correlated w ith socialrejection and tha t rejection is correlated with the c ontinuationof aggressive behavior. At a broa der level, the association of re-jection and aggression h as been seen as consistent with the e m-phasis of sociologists Hirschi (1969) and Yablonsky (1962) onthe essential social disaffiliation and disengagement of delin-quen t and aggressive youth s.There is some evidence from studies of children , however, toindicate that dislike and popu larity can coexist in the same indi-vidual and that assertive-aggressive behavior does not necessar-ily preclude popularity (Coie, Dodge, & Coppotelli, 1982). Asubgroup of subjects labeled controversialpresumably be-cause they obtained, simultaneously, higher-than-average scoreson peer p opularity and peer dislikeshowed a blend of antiso-cial behavior and peer acceptance. This subgroup is of specialinterest because controversial subjects (who do not show u p inlarge numbers) can sometimes be viewed as leaders in the peergroup (Coie et al., 1982, p. 568).

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816 CAIRNS, CAIRNS, NECKERMAN, GEST, GARIEPYFollowing assum ptions discussed elsewhere (Cairns et a l, inpress; Kandel, 1978), the present research addressed three pro -posals on the relationship between aggressive behaviors and so-cial affiliations. First, highly aggressive subjects were expectedto be m emb ers of definable social clusters and no t to differ fromcontrol subjects on this index of affiliation. Because of their

abusive and coercive behaviors, aggressive subjects may be gen-erally less popular than control subjects in the social networkas a whole. On the other hand, aggressive adolescents may beaccepted by other p ersons in the social cluster with whom theyare identified. Hence, aggressive adolescents would be as likelyas control subjects to have reciproca ted "best friend" selections.A second proposal concerned the extent to which there is so-cial support by peers for aggressive behaviors. Aggressive sub-jects may be expected to affiliate with aggressive peers. Acrosssocial clusters, there should be high levels of similarity betweenindividuals of the same cluster with respect to aggressive expres -sion (i.e., "hom ophily"). This expectation follows from the re-ciprocal a nd contagious na ture of aggressive behaviors in social

groups as well as the social choice and social default factors thatserve to define entry into groups and help consolidate theirstructures.A third set ofissues concerned gender differences and whetherthe p atterns of group mem bership in highly aggressive girls weredifferent from those in highly aggressive boys. Most relevantevidence indicates tha t the s tandards for the acceptability of as-sertive-aggressive behavior differ for boys and girls (e.g., C airns ,Cairns, Neckerman, Ferguson, & Gariepy, 1988; Savin-Wil-liams, 1979). The different normative standards, in turn, mayaccoun t for the difference in the sheer numb ers of highly aggres-sive girls relative to highly aggressive boys. These social stan-dards may also promo te differences in the ex tent to which ag-

gressive patterns a re perm itted to become a basis for differentialpeer group association. On the basis of the foregoing, it wasexpected that both boys and girls would show patterns of aggres-sive homophily, but th at girls would be more vulnerable to rejec-tion and social ostracism because of overt aggressive behavior.Studies of aggressive subjects and their social groups havesuffered from a gender bias. For example, investigations of re-ciprocal relationships of violent subjects and studies of "gan g"behavior have been traditionally limited to males (e.g., Cohen,1955, Toch, 1969). There have been few instances where aggres-sive reciprocal relationships have been studied in girls (or inboys' relationships with girls) or in female "gangs" (Giordanoet al., 1986). This bias is of some importance because the evi-

dence that is available on reciprocal relationships involvinggirls indicates that the sex of the "other" does make a difference.Different patterns of reciprocal action have been obtained inmale-fema le interactions relative to m ale-m ale ones (e.g., Bar-rett, 1979). The difference reflects the operation of a dual stan-dard, in that girls are not supposed to be attacked by boys, al-though girls may attack both boys and girls. In one of the fewsystematic studies of adolescent d elinquent gangs of girls, Gior-dano (1978 ) found within-group su pport for deviant norms no tunlike that found in males. More recently, Magnusson (1987)has shown that affiliations with older peers play a powerful fac-tor in accounting for the deviancy of early maturing Swedishteenage girls.Shortcomings in tech niques available for social network anal-

ysis have made it difficult to describe the supportive role of peersat any age (e.g., Dunphy, 1963; Ha rtup, 1983; Mo reno, 1934).Procedures that describe the social status of children often donot provide information about the nature of the social groupsin which children participate (e.g., Coie & Dodge, 1983; Peery,1979). Beyond categorization of children as "popular""rejected," "isolated," "average," or "controversial," classicalsociometry would seem to require information about (a) theidentities of individuals within a given social cluster and (b) thenum ber of social clusters within a m icrosocial network (Bron-fenbrenner, 1944a, 1944b; Moreno, 1934). To this end, the pres-ent study introduce d a procedu re designed to capture informa-tion about the nature, status, and composition of social net-works within schools.

MethodSubjects

A total of 695 subjects (364 girls and 331 boys) were recruited fromseven public schools in two cohorts. Cohort 1 consisted of 220 fourth-grade subjects (116 girls and 104 boys; A/a ge = 10.2 years, SD = .57)from four elementary schools. Cohort 2 consisted of 475 seventh-gradesubjects (248 girls and 227 boys; Mage = 13.4 years, SD = .58) fromthree middle schools. The mean family socioeconomic status on theDuncan scale (Featherman revision) was 30.2 (S D = 17.1) in Coho rt 1and 31.6 (S D = 17,8) in Cohort 2, and the full range of occupations wasrepresented in the samples (range from 88 to 7; i.e., chair of medicalcenter department, attorney, regional sales manager, small-businessowner, truck driver, domestic worker, unemployed farm worker, etc.).Twenty-five p ercen t of the subjects were minority status (predominantlyBlack). The seven schools were located in two counties: one, a suburbanmetropolitan area, and the other, a rural county (as classified by the1980 U.S. census). There were no restrictions on inclusion other thanconsent: all children in the designated grade (fourth or seventh) in eachschool were included in the study if (a) the children wished to partici-pate and (b) they and their parent or legal guardian signed a statementof informed consent. The participa tion ra te ranged from 89% in the lastjunio r high school assessed (132 of 149) to 50% in thefirst unior highschool (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% whodid not were compared in terms of ethnic status, sex, and probabilityof being nominate d as highly aggressive. No systematic differences wereobtained on any of these dimensions.

Within the larger sample, 40 subjects, 20 girls and 20 boys, werejudged by teachers, counselors, and principals to be highly aggressive(i.e., there were 20 highly aggressive subjects in each co hort). In orderfor an individual to be selected, he or she had to be nominated by twoschool personnel (teacher, counselor, or principa l) w ho were closely ac-quainted with the subject. An additional group of 40 nonaggressive con-trol subjects was identified and matched individually on the basis ofsex, race, classroom attended, physical size, socioeconomic status, andchronological age.1 Priority was given to the matching variables in the! The matching was successful on all variables (e.g., no significantdifferences were obtained on classroom, race, physical size, socioeco-nomic status, age), with one exc eption. Th e aggressive-control subjectsin the fourth grade did not differ in age (10.1 vs. 10.3 years in aggressiveand control girls and 10.6 vs. 10.5 years in aggressive and control boys,respectively). However, the aggressive-control subjects in the seventhgrade differed (13.6 vs. 13.0 years in aggressive and control girls and14.1 vs. 13.3 in the aggressive and control boys, respectively). To correct

for any effects attributable to the age discrepancy in the older sample,


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SOCIAL SUPPORT OR SOCIAL REJECTION? 817order of listing. In order for children to qualify for possible inclusionin the matched-control group, they could not have received a schoolnomination for being highly aggressive. As a check on the validity of theschool nomin ations, pair-wise observations of each aggressive-controlpair were conducted over a 4-day period, with extensive observationsdaily over two contexts. These observations (not reported in this article)indicated that the aggressive subjects and nonaggressive controlsdiffered markedly in observed aggressive interchanges in the fourth andseventh grades.

MeasuresMultiple assessment procedures were used in order to obtain conver-gent evidence on the prima ry hypotheses {following the research stra t-egy outlined in Cairns, 1986, and in Cairns & Cairns, 1988). The mea-sures included in this report were as follows: peer reports of the individ-ual's role in the school social networks; a social cognition interview onrecent conflicts; Interpersonal C ompetence S cale-teacher (ICS-T) tests,which yielded factor scores on aggression, popularity, and academiccompetence factors; Interpersonal Competence Scale-self (ICS-S) tests,

which yielded self-perception factor scores on the same factors; peernom inations for conflict instigation; and peer affiliations, as determinedby "best friend" choices. These procedures and the measures that theygenerate 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 interviewwas conducted with each subject. A semistructured protocol was fol-lowed by the interviewer. The social networks in which subjects wereinvolved were plotted on the basis of information obtained from sub-jects and peers in four sections of the interview.In one section, subjects and peers were asked, "Now tell me aboutyour (school, class). A re there some people who hang around together alot?" Follow-up probes elicited specific information about the perceivedmakeup of the clusters. As indicated in C airns et al. (1985), high levels

of intersubject agreement were obtained in the identification of clustermembership. In a second part, subjects were asked about any personswho were "not members of any groups." The persons named by thesubject, including themselves, were counted as having been nom inatedfor social isolation. In a third section, subjects were asked to identifytheir "best friends." For peer-friendship analyses, all choices of eachchild were listed. By comparing friendship choices across subjects, itwas possible to determine which friendships were reciprocated andwhich were not. In a fourth part, subjects were asked to nominate per-sons (both male and female) who gave them "trouble" or "bothe red"them. These nominations were followed by a request to provide a de-tailed and concrete account of a recent conflict with a peer (both maleand 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 relationsamong persons within each cluster. In the decision rule method, eachrespondent 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. Itwas a decision rule procedure because arbitrary standards were adopted(a) to order the cases into groups, (b) to judge whether borderline casesbelonged to one or more social clusters, and (c) to determine which

all analyses were conducted with and without age as a covariate. In noinstance did covariance analyses (controlling for age) yield outcomesthat were significantly different than the ANOVAS.

persons were central to the cluster (nuclear members) and which wereon the edge of mem bership (peripheral m embers).The present quantitative procedure evolved from the decision rulemethod. It was introduced in order to develop a broadly applicable tech-nique for describing relations between persons and the str ucture of so-cial networks, with minimal reliance on intuitive judgments. (A sepa-rate article, Cairns, Kind erma nn, & Gariepy, 1986, describes themethod and alternative quantitative procedures.) In brief, four succes-sive matrices were constructed for each classroom in order to arrive atthe latent struc ture of the classroom netw orks. First, a raw recall matrixwas constructed from the free recall of social groups by all subjects(male and female) in the classroom: each subject-respondent indica tedwhich persons in the school belonged to which groups (see Table 1 inCairns et al., 1985, for one recall matrix where each column refers o adifferent respondent and the children-to-be-clustered are listed downthe rows).

Second, each raw recall matrix was transformed to a cluster co-occur-rence matrix (i.e., a symmetric matrix that summarized the frequencywith which each person was named to the same group as each otherperson in the school and where the cells indicate the number of timestwo persons "co-occurred" in the same cluster). The rows of the co-occurrence matrix consisted of all children-to-be-clustered (includingthe subjects themselves), and the columns of the matrix were the sameas the rows. The entries summarized the num ber of occasions that Per-son / has been identified by respondents to be in the same social groupas Person j . The diagonal of the co-occurrence matrix contained thenumber of occasions that a given person was named t o any group (i.e.,subjects are considered to be members of all groups to which they havebeen named).Third, a correlation matrix was generated by intercorrelating the col-umns of the arrays of the co-occurrence m atrix. Each correlation re-flected the level of correspondence between the cluster membershipscores of Subject A with those of Subject B. Transitivity typically wasfound in groups of individuals. That is, if Subject A obtained a signifi-cant positive correlation in pattern s of co-occurrence w ith both SubjectB and Subject C, then Subject B typically obtained a significant positivecorrelation with Subject C. This empirical transitivity facilitated theassignment of individuals to preliminary social clusters (i.e., personswho were judged by their peers to "hang around together").Fourth, a Lambda-X (LX) LISREL matrix was constructed on the ba-sis of the preliminary cluster descriptions, where each individual-to-be-clustered was treated as an "observed" variable, and the "latent"variables were clusters of persons. The aim of the LISREL was to clarifythe social structure in those classes where the social clusters were notclearly defined, often because individuals may appear simultaneouslyin two or more clusters. In establishing the initial LX matr ix, each per-son was declared free for a single latent variable (cluster) and fixed forall other latent variables (clusters). In thefinalstep, LISREL VI estimatesof 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 simulta-neously appear in two latent variables (i.e., to become members of twosocial clusters at the same time). Decisions about relaxing the modelor relocating subjects were made on substantive, a priori grounds byinspection of the raw recall matrix. The goodness-of-fit measure fromthe LISREL solution was consulted as a guide to determ ine w hether thefit was substantially improved by the adjustment.2 These "latent vari-

2 The LISREL Goodness-of-Fit Index (GFI), root mean square resid-ual (RMR), and other parameter estimates were used primarily for de-scription in the present application. The properties of the correlationalmatrices derived from the co-occurrence matrices preclude standardLISREL inferential interpretations. Nonetheless, the LISREL VI programprovides a guide for compa ring the effects of relocating individuals from


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818 CAIRNS, CAIRNS, NECKERMAN, GEST, GARIEPYables" defined the social network in each extended classroom ("ex-tended" because the method permitted persons in the school other thanthose in the classroom to be cluster members).After th e social clusters in each classroom were identified, the relativecentrality of each cluster and of each member of th e separate clustersw as determined. The index t o centrality w as simply th e number of timesthat a given person was nam ed t o a cluster. Using the average of the twopersons in the cluster w h o received the highest number of nominations,the rank of th e cluster was determined {i.e., high-, medium-, and low-salient clusters). Similarly, nomination frequency was used to deter-mine the status of individuals within their clusters: nuclear, secondary,or peripheral. Clusters (or persons) in the upper 3 0% rank of nomina-tions were considered to be high salient (or nuclear rank), those in thelowest 30 % were considered to be low salient (or peripheral rank), andthose in the mid-range 40% were considered to be medium salient (orsecondary rank). In sum, the method is a quantitative technique thatyields information about (a) the social clusters within each classroom,(b) the identity of persons who are members of each cluster and theirrelations to each other, (c) the relative centrality of each cluster, (d) therelative rank of persons within the clusters, and (e) the extent of dualcluster memberships.

For replication and reliability purposes, the entire network analysisw as repeated for all designated classrooms using th e decision ru le analy-s is described in Cairns et a l. (1985). The decision rule method of initialcluster estimation is relatively easy to com pute: It preserves the identityof the other members of th e social network and captures much of thesalient information about classroom relationships. (It does not involvethe construction of the co-occurrence, correlational, and L X matrices.)In the present data set, the two analysesquantitative and decisionruleyielded virtually identical results and identical summary conclu-sions. The quantitative m ethod, although m ore laborious and expensivein compu ter time, ha s an advantage in objectivity and freedom fromsubjective decisions about cluster membership. It also provides a quanti-tative guide for deciding whether the solution is improved b y permittingjoin t cluster memb ership for particular persons. A ccordingly, the resultsof the quantitative m ethod are reported here.3Peer nominations fo r conflict instigation. In the individual inter-view, subjects were asked the questions, "Has anybody bothered yourecently or caused you any trouble? Or made you mad ?" Depending onthe sex of the individuals who were identified in the first question, thechild was asked about the opposite sex and whether any boys or girlshad bothered them or caused them trouble. In follow-up probes, thenames of the other persons were established. This inform ation w as taperecorded, transcribed, tabulated, and coded with the aid of class and

one cluster to another a s well as the effects of oint cluster membership.For purposes of description, the mean GFI across 6 3 classroom analyses(32 classrooms for boys and 3 1 classrooms for girls) was relatively high(.92), and the mean R M R was low (0.14), indicating that the L I S R E L vimodels of networks provided a close fit to the observed correlationalmatrices. It is of interest to observe that no grade differences were ob-tained in these measures of network definition, but girls obtained a sig-nificantly higher mean GFI: for boys M = .90 and for girls M = .94,F ( 1, 29) = 9 . 0 0 , p < . 0 1 . Similarly, ther e w a s a significant se x differencein the average R M R , S O that expected/observed differences w ere smallerfor girls than for boys: for boys M = . 16 and for girls M = . 1 2 , F \ 1,29) =6.50, p < . 0 5 . The network analyses for the 31 boys were individuallymatched (by classroom) to the network analyses for the 31 girls (i.e.,the single all-male classroom was eliminated for the purposes of thiscomparison). This sex difference in the definition and clarity of socialnetworks is consonant with the idea that girls have more easily identifiedsocial clusters and group membership than boys (Gilligan, 1982). It isalso consistent with the m ore frequent use of social ostracism b y girls.

school enrollment lists (there was more than 99% agreement by inde-pendent judges). The number of occasions that a given subject wasnamed by peers as having caused a conflict was summarized over allmale and female respondents in order to obtain a peer conflict nom ina-tion score. Because entire schools were sampled in the fourth and sev-enth grades, it w a s possible to compute the z score for the peer nomina-tions of each subject (i.e., every subject w a s compared with others of thesame sex in the schools in which they w ere enrolled). Conflict nom ina-tion scores were available from female peers, male peers, and sum maryfemale and male scores.Interpersonal Competence Scale-Teacher. The subject's teacher (orcoteachers) completed the Interpersonal Competence Scale (Cairns &Cairns, 19 8 4 ) . The ICS-T consists of 15 items tha t per tain to aggressive-ness, popularity, affiliation, and academ ic competenc e. Each item re -quires th e respondent t o describe the subject on a 7-point scale. A factoranalysis (varimax rotation) of th e ICS-T items indicates that three dis-tinct factors emerge w ith high levels of communa lity in all age-sex lev-e l s . The three item clusters were aggression, popularity, and academiccompetence. A L I S R E L measurement model indicated an excellentfitofthe items to these three factors. For example, at t he seventh-grade level,the hypothesized structural equation with three latent variables yieldeda Goodness-of-Fit Index of . 9 8 , The chi-square with 17 degrees of free-dom was 13.83 (p = 0.67), confirming the goodness-of-fit analysis. ThisL I S R E L solution w as representative of those conducted at the other gradelevels, indicating that three separate factors (aggressiveness, popularity,and academic competence) may be reliably identified in the ICS-Tacross this ag e range.

Of special importance to this research was the ICS-T factor of "ag-gressiveness" (which consisted of hree items; namely, "gets in trouble a tschool," "fights a lot," and "always argues"). The concurrent interraterreliabilities for the aggressive factor scores in assessments were r(35) . 8 2 , and r(26) = .78 (Fisher's Z-averaged r = .81). These two-personinterrater reliabilities compare favorably with those reported in otherstudies (e.g., Olweus, 1979) and prior reliabilities reported using thepresent scale (Cairns & Cairns, 1984). The construct validity of thisaggressive factor score and its linkage to other external measures of a g -gressive behavior has been established in compan ion studies (C airns &Cairns, 1984,1988). Comparable reliabilities were obtained for t h e p o p -ularity and academic factors. The items were reseated on the 7-pointscale so that the lower th e ICS-T factor score, the higher the social desir-ability. Th at is , for the aggressive factor, high factor scores reflected highaggressiveness; for the popularity factor, low factor scores reflected highpopularity.

Interpersonal Competence Scale-Self. Each year subjects com pleteda self-descriptive tes t form of the Interpersonal Competence Scale ( I C S -S ). A booklet was prepared with the items printed on separate pages.Other than the inclusion of distractor items and booklet format, thesubjects' tests (ICS-S) were identical with those completed by adults(ICS-T). The scales themselves had been developed through extensivepilot testing. The vocabulary and instructions were within the range offourth-grade students. If necessary for comprehension, the interviewerread the item aloud. The same items were used across all years, and theyear-to-year stabilities are reliable (C airns et a l . , 1988).Procedure

Subjects were interviewed and tested in the school that they attended.Confidentiality was assured, and subjects were told that they could de-cline to answer a n y question o r withdraw at any point. A t t h e conclusionof the interview, they were given the choice of a school-related itemobtained 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? 819pencil). Teachers were given minimal instructions on rating, except touse the full range of the scale if appropriate. Society for Research inChild Development ethical standards were followed in all aspects of theinvestigation.

ResultsThe research outcomes are summarized in three sections. Inthe first part, behavioral differences and similarities among thehigh-aggressive and the m atched c ontrol groups are described.The second part focuses on aggressive children and their rolesin the social network. The third part analyzes the role of peersocial structures in the promotion and regulation of aggressivepatterns. Gender similarities and differences are discussed ineach section.

Characteristics of Aggressive and MatchedControl SubjectsSubjects who had been placed in the high-aggressive groupdiffered from those in the m atched control g roup on several be-havioral dimensions related to aggression and popularity. Asshown in Table 1, subjects in the aggressive condition scoredhigher than those in the control condition on all measures ofaggression used. The aggression-con trol differences were highlyreliable in the ICS-T (teacher) assessments of aggression, 7*1(1,36) = 34.68, p < .001, in peer nominations for aggressive con-flicts, t\\ t 36) = 29.62, p < .001, and in the ICS-S (self) ratingsof aggression, F{\, 36) = 13.34, p < .001. Parallel effects wereobtained in both grades and in b oth girls and boys. For the ICSaggressive factor measures, only the main effects of condition(aggression vs. nonaggression) were reliable; no other main

effects or the interactions reached statistical significance. In thecase of the summ ary peer nom inations, there was also a reliable

Table 1Characteristics of he Aggressive an d Nonaggressive Groups asa Function of Grade and Sex

Table 2Popularity of Aggressive an d Nonaggressive Groups as aFunction of Grade and Sex

Subjects/groupBoysAggressive4th grade7th gradeControl4th grade7th gradeGirlsAggressive4th grade7th gradeControl4th grade7th grade

ICS-T(Teacher)M

5.835.173.503.80

5,075.502.603.03

SD

1.340.672.291.75

0.711.331.491.75

Measures of aggressionConflict(Peer)

M

4.101.901.200.70

2.801.900.800.50

SD

2.561.911.401.25

1.812.561.030.71

ICS-S (Self)M

3.954.113.733.47

4.534.033.232.97

SD

0.781.151.341.04

1.131.010.990.96

Subjects/groupBoysAggressive4th grade7th gradeControl4th grade7th gradeGirlsAggressive4th grade7th gradeControl

4th grade7th grade

Measures of popularityICS-T (Teacher)M

4.124.232.733.734.324.533.033.13

SD

1.731.461.591.231.381.411.090.69

ICS-S (Self)M

2.423.452.383.332.802.802.302.35

SD

1.001.080.801.311.650.860.870.74

Note. ICS = Interpersonal Com petence Scale.

gender effect, in that boys were nominated for causing conflictsmore often than girls, F(\ f 36) = 4.87,p < .05.4Aggressive subjects were also less popular than peers in thecontrol group, as evaluated using the ICS-T popularity factorscores (Table 2). The main effect of condition (aggression vs.control) was highly reliable, F{\, 36) = 21.08, p < .001. Nointeractions were statistically reliable, nor were the main effectsof grade or gender. Aggressive subjects were also more fre-quently disliked by peers, as inferred from nom inations of peerswho saw themselves as being bothered an d bullied by them (seeTable 1, "Conflict: peer" column ). These outcomes are consis-tent with previousfindings hat aggressive subjects a re likely tobe seen as generally unlikable and unpopular (e.g., Coie &Dodge, 1983). Self-ratings on popu larity, however, yielded par -allel outcomes in the two groups. Aggressive subjects ratedthemselves to be as popular as control subjects in the ICS-S as-sessment. Moreover, there were no differences between the ag-gressive subjects and matched-control subjects in the numberof occasions that peers nam ed them as best friend (see below).

Aggression, Social Roles, and RejectionTwo analyses of the social roles of highly aggressive and con-trol subjects were permitted by the data: peer-defined socialclusters and peer judgmen ts of isolation/rejection from the so-cial network.Social cluster analysis. The social clusters in the two

Note. ICS = Interpersonal Competence Scale.

4 Beyond the main effects attributable to the aggressive-control dis-tinction, further analysis of the peer nominations indicated that (a)boyswere reliably less likely to nom inate girls than vice-versa and (b) therewas a significant decrease in total nominations by girls as they grewolder. In all nom ination indicesw hether generated by boys or girlsthe differences between the aggressive- and matched-control groupswere highly significant (p < .005).


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820 CAIRNS, CAIRNS, NECKERMAN, GEST, GARIEPYdifferent grades were identified by peers. Confirming the resultsof preceding work, the social clusters identified in the cognitivesocial maps were predominantly (a) same-sex in compositionand (b) reliably identified across individuals, even when personswere not themselves members of the clusters (Dunphy, 1963;Cairns et al., 1985). The cluster identification method was usedto determine whether aggressive (or control) subjects were fullmembers of the extent social clusters, peripheral members ofsocial clusters, or were not named as members of any socialcluster. The results of this classification are shown in Table 3.For summary purposes, subjects who were nuclear members ofhigh salient clusters were classified as nuclear, subjects who weresecondary members of high-salient clusters or nuclear/second-ary members of medium-salient clusters were classified as sec-ondary, and subjects who were in low-ranked clusters or periph-eral members of any cluster, regardless of status, were classifiedas peripheral. Subjects not named at all were classified as iso-lated.

No reliable differences were obtained between subjects in theaggressive and control conditions in type of cluster member-ship, using chi-square analyses. Across all age-sex groups, 95%(38 of 40) of the highly aggressive subjects were members ofsome social clusters, as identified by peers. Approximately one-third (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/sec-ondary members of middle-salient groups). One-fifth of the to-tal (20%) were peripheral members of the social network (i.e.,members of low-status groups or peripheral "hangers on" tohigh-salient groups). Only 5% seemed to be removed from thesocial structure. These proportions were virtually identical withthose of the matched control subjects, except that none of thecontrol subjects were perceived to be removed entirely from thesocial structure (the difference is not reliable). No difference

Table 3Cluster Membership ofAggressive and Nonaggressive Subjectsas a Function of Grade and Sex

Grade/gro up Nuclear Secondary Peripheral Isolate

Tab le 4Mean Nominations for Social Isolation by Peers by Sex,Grade, and Aggressive Group Status

4thAggressiveGirlsBoysControlGirlsBoys7thAggressiveGirlsBoysControlGirlsBoysSum {4th and 7th)AggressiveControlTotal

.10(1/10) .60(6/10) .30(3/10) .00(0/10).40(4/10) .40(4/10) .20(2/10) .00(0/10)

.20(2/10) .70(7/10) .10(1/10) .00(0/10).20(2/10) .50(5/10) .30(3/10) .00(0/10)

.40(4/10) .40(4/10) .10(1/10) .10(1/10).30(3/10) .40(4/10) .20(2/10) .10(1/10)

.50(5/10) .30(3/10) .20(2/10) .00(0/10).50(5/10) .30(3/10) .20(2/10) .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)

SubjectsBoys4th grade7th gradeSummed over gradeGirls4th grade7th gradeSummed over grade

AggressiveconditionM

1.200.600.901.800.801.30

SD

1.321.261.293.081.232.35

NonaggressiveconditionM

1.000.300.650.701.801.25

SD

0.820.480.671.892.532.23

in category representation between the aggressive and controlgroups was statistically significant as determined using chi-square analyses (Table 3).5

Given that highly aggressive subjects were more likely to benom inate d by peers for causing conflicts, it seems reasonable toexpect that fewer peers would wish to be affiliated with them.This would lead to a reduct ion in the overall size of the clustersin which aggressive subjects were me mbe rs. Ther e is some mo d-est support for this expectation. Among subjects who weremembers of social clusters, the mean numbers of persons in theclusters of the highly aggressive and matched control subjectswere 5.11 and 5.72, respectively. However, this difference wasnot statistically reliable, F(\, 34) = 2.84, p> .05. Although ag-gressive girls tended to be in smaller clusters than co ntrol girls,none of the main effects (sex, grade, or risk condition) or theirinteractions were statistically significant.Peer judgments of isolation. In addit ion to describing thesocial structure, all subjects were asked to specify any personsw ho did not belong to any social group (i.e., those who wererejected or isolated). The n u m b e r of times that each aggressivesubject and his or her matched control was named as being out-side the social network was determined. The means for the sex-age-aggressive groups are shown in Table 4. The peer judg-men ts of social isolation indica ted no reliable effects, either asmain factors or in in teract ion.Peer judg me nts of isolation may be used to identify part icula risolated subjects. A conservative estimate of isolation may beobtained if a given subject was explicitly identified by at least 4of his or her peers as having no social grou p. Overall, 10% (4 of

Note. Numbe rs in parentheses represent the num ber of subjects (out oftotal num ber) rated as being in the various clusters.

5 The clusters in Table 3 cumulated information from all respondentsin the study, including the subjects themselves. An argument can bemade that the individual's own self-assignments should be omitted be-cause of possible self-enhancement distortions, pa rticularly among sub-jects who are peripheral (Cairns, Neckerman, & Cairns, in press). Whenthe clusters were recomputed without the subjects' self-assignments, noreliable changes were observed. As expected, more persons became cat-egorized as isolated when the additional respondent (i.e., the self) waseliminated (5 of 40 in the combined aggressive group and 1 of 40 in thecombined control group; 8% overall in combined groups). The differ-ences were not statistically significant using chi-square analyses, eitheroverall or in specific age-condition com parisons.


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SOCIAL SUPPORT OR SOCIAL REJECTION? 82140) of the highly aggressive subjects and 8% (3 of 40) of thenonaggressive control subjects qualified for this conservativejudgm ent of isolation. The difference was not reliable.Peer Social Organization and Ag gression

The question addressed in the next set of analyses concernedwhether highly aggressive children and adolescents get togetherto form cliques. Do aggressive children tend to hang aroundtogether? This matter was investigated by intraclass correla-tional analyses of the social clusters identified through the quan -titative network analysis. To determine if the clusters them-selves differed in mea n levels of aggressive expression, the ag-gressive factor scores (i.e., ICS-T) of the nuclear members ofeach group were determined.6 An intraclass correlational anal-ysis of the similarity of ICS-T scores of the nuclear m embers ofeach social cluster permitted a determ ination of within-clustersimilarity on aggressive scores. Intraclass coefficients were com-puted separately for the two grades and two sexes for the clustersin all classes. All levels of clusters (high, medium , and low) wereincluded in the analysis.

The intrac lass coefficients using the 1CS-T aggressive factorsindicated that nuclear members of the male clusters in thefourth grade were highly sim ilar in term s of their ratings of ag-gression: the intraclass correlation was .75, F\22, 29) = 8.57,p < .001. For fourth-grade girls, however, the intraclass co rrela-tion for aggression was not significant, r' .03, F{26, 39) ~1.07, p > . 10. The same analysis was completed for the seventhgrade. In the early adolescent coh ort, the intraclass correlationfor 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 < . 0 0 1 .''Best Friend" Analysis

An alternative technique for analyzing social networks in -volved the use of the "best friend " info rmatio n. From eac h sub-ject's protocol, persons who were named as best friends weredetermined. By cross-reference, it was possible to determinewho reciprocated th e selection (i.e., whether the best friendhimself or herself nam ed th e subject as best friend). This analy-sis was completed separately for the best friend selections ofboys an d girls in the two cohorts. The mean scores on the ICS-T aggressive factor were determined for reciprocated and non-recipro cated friendships. The individ ual's own aggressive factorscores were correlated separately with th e mean aggressivescores of both reciprocated an d nonreciprocated friends.

The results of this analysis for the fourth-grade cohort indi-cate a high relationship in the aggressive factor scores of males,but only if the best friend choices were reciprocated (Table 5).That is, the correlation between th e ICS-T aggressive factorscores for boys whose friendship choices were mutual was .61(p < .01), whereas the aggressive scores of nonrec iprocate d bestfriend choices were not reliably correlated, r - .12, p > .10. Ifone did not have information about friendship reciprocationand al l best friends named by the subject were considered (aswould be the case if the friendship choices of the best friendshad not been determined), similarity on the aggressive factorscores would remain statistically significant for fourth-grade

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

SubjectsBoys4th grade7th gradeGirls4th grade7th grade

Reciprocal

.61*.63*

.07.51*

Nonreciprocal

.12.40*

.19.12

Sum.41*.49*.08.34*

Note. ICS-T = Interpersonal Com petence Scale-Teacher.*/? < .01 (product-mom ent correlation).

males, r = .41, p < .01. The seventh-grade cohort boys repli-cated th e findings from th e younger boys: r = .63, p < .01, forthe reciprocated pairs. In the older male group, however, eventhe nonreciprocated best friends had a reliable similarity withthe subject in terms of ICS-T aggression factor scores, r = .40,p < .01. For girls in the fourth-grade cohort, there were lowlevels of similarity between th e mean scores of best friends onthe ICS-T aggressive factor, regardless of whether the friendshipselections were reciprocated (Table 5). In the seventh-grade co -hort, however, th e best friends of girls were similar in aggressivefactor scores. Again, th e relationship was strongest if the femalebest friend choices were reciprocated. The data ar e consistentwith th e cluster analyses, in that girls in early adolescence tendto affiliate with other girls who ar e similar on aggressive exp res-sion.Finally, subjects in the highly aggressive group did not differfrom th e subjects in the matched-control group in terms ofnumber of reciprocated choices as best friend. The same per-centage (43%) of highly aggressive subjects as matched controlsubjects received reciprocated best friend choices. The groupsdid not differ in the number of times that they were selectedby peers as a best friend nor in the number of times that theirfriendship choices were reciprocated.

DiscussionHighly aggressive girls and boys were usually solid membersof peer clusters in the fourth and seventh grades an d they typi-

cally had a network of friends. The finding that aggressive ado -lescents have lower levels of general popu larity an d likabilityfindings that were replicated in this reportmay serve to ob-scure the "concealed competencies"7 that perm it these personsto survive in particular social contexts. Being popular with th e6 The ICS-T measure was used because of its demonstrated stabilityand relationship to subsequent problem behaviors. Other "external"measures, including peer nom inations, yield parallel results.7 The term concealed competence has been used by Norman Gar-mezy to refer to unrecognized and perhaps unrealized skills possessedby persons, especially individuals who have been deemed delinquent,deviant, retarded, or socially incompetent (private communication,

May 15,1988).


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822 CAIRNS, CAIRNS, NECKERMAN, GEST, GARIEPYgroup as a whole may not be the only goal for adolescents, andfailure to achieve broad-based popularity should not be takenas evidence of wholesale social rejection. Fu rthermo re, aggres-sion and correlated life-styles appear to provide a significantbasis for pee r affiliations.These findings are consistent with the observations of Gior-dano (e.g., Giordano et al., 1986) on the cohesion of deviantgroups. The results are also in accord with earlierfindings hatindicated that some "controversial" aggressive children areboth rejected and accepted by peers (Coie et al,, 1982; Coie &Dodge, 1983). In the present study, aggressive children in bothcohorts and in both sexes may be disliked by some classmatesfor legitimate reasons (bullying, ridiculing, or v ictimizing). Butdislike by certain peers is not equivalent to social rejection orisolation from the entire social structure . Highly aggressive ado-lescents may alienate many peers, but the relationships thatthey establish with some peers seem no less meaningful thando those of nonaggressive adolescents. In any case, the highlyaggressive subjects in this study were typically m embers of so-cial clusters, and they w ere as likely as m atched control subjectsto have a coterie of reciprocal "bes t friends."

A dark side to coercive cliques in adolescence requires com -men t because of its relevance to societal rejection. In the co urseof development, coalitions of aggressive adolescents might beexpected to com e into conflict with ad ults as well as peers andto threate n the existing order. In the compe tition for hegemonyin the school context, aggressive coalitions of students can dev-astate the au thority of adults. Failures by the persons in chargeof the school to abo rt the formation of such groups or to regu-late them could be an abd ication of responsibility. Hence, coali-tions among aggressive adolescents demand the attention ofteachers and principals. Implicit and explicit rejection of ag-gressive adolescents by school personnel should, in the long run,catalyze the attitudes of peers who have been victimized. Overtime, mem bers of coercive peer groups should be m ore likely todrop out of school, or to be forced out through suspension andexpulsion.

Turning to sex similarities and differences, it is noteworthythat aggressive patternsand correlated behaviorsprovideda basis for social cohesion and comm onalities in friendships forboth boys and girls. At the outset of the study, it seemed reason-able to expect th at a nticipatory sex differences would arise be-cause of the sanctions against direct physical aggression in girls.Romantic and sexual interests become of greater importancefor girls than boys (e.g., Cairns et al., 1988), and the normativecriteria for feminine attractiveness ordinarily do not includeaggressiveness (Gilligan, 1982). Accordingly, fourth-grade girlsshowed no propensity to sort out their friends on dimensionscorrelated with aggressive behavior. On the other hand, thepresent data clearly show that, by adolescence, aggressive ho-mophily is almost as strong for girls as it is for boys. These find-ings do not stand alone. Both M agnusson (1987) and Giorda noet al. (1986) found that deviant teenage girls tend to affiliatewith other girls who match their acting-out behaviors. By ad-olescence, the external constraints with respect to aggressiveaffiliation may be relaxed for females, possibly because suchgroups of girls are perceived to be less threatening than gangsof adolescent males. Alternatively, affiliations among aggressiveadolescent girls may be caused by their exclusion (i.e., ostra-

cism) from other, more acceptable groups. All this is to empha-size tha t social clusters are no t merely the creation of childrenand adolescents: The broader social commu nity of teachers, ad-ministrators, and parents probably contributes to the forma-tion and dissolution of social clusters at all ages.A comment on methodology is in order. Although the qu anti-tative method adopted here for analyzing social networks re-quires multiple steps, most of the information on cluster mem -bership can be abdu cted by a brief inspection of the raw recallmatrix. There is considerable agreement among children andadolescents in their perceptions of whom was associated withwhich cluster. The key to network analysesw hether qua ntita-tive, geometric (Moreno, 1934), rule-guided (Cairns, et al.,1985), or abductive (Dunphy, 1963)is to cap ture the in terre-lations among persons as they exist in groups and subgroups.These solutions should be convergent, as the present data sug-gest. Methods that focus on the po pularity of individuals as op-posed to the dynamics of networks may capture differentsources of variance (Cairns, 1983). Specifically, recent methodsfor identifying "social st atus " on the basis of pooled ratings ofhow peers like, dislike, or ignore the subject typically reveal littleabout the person's placement in a network of relationships (e.g.,Asher & Dodge, 1986). One contribution of the present studyhas been to describe a quantitative procedure that can bebroadly applied t o networks in classrooms and o ther social set-tings.

This work was completed on a representative sample of non-urban youths in diverse living circumstan ces in the 1980s; it isdoubtless limited in generality by cultural and temporal con-straints. The problems addressed, however, are universal. Bycertain standards (e.g., socioeconomic status, sex distribution,racial representation), this sample is not unlike that repre-sented in the national p opulation. Moreover, generality is sug-gested by key similarities between ou r results and those of previ-ous researchers once the difference in methodology and con-structs is acknowledged (e.g., Asher & Dodge, 1986; Coie &Dodge, 1983). The present outcomes are also consistent withrecent developmental (Parks & Slaby, 1983) and sociological(Giordan o et al., 1986) perspectives on reciprocities in aggres-sive behavior. Aggressive adolescents may be unpopular in thelarger social community of peers and adults, yet they can beaccepted by and closely linked to the particular subgroups ofpeers. Further analysis of this phenom enon should be useful inclosing the gap between the sociological focus on delinquent"gangs" and the psychological emphasis on n ormal peer groups(Hartup, 1983).

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