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Effects of Communication, Information Overlap,and Behavioral Consistency on Consensus InSocial Perception.Thomas E. MalloyRhode Island College, tmalloy@ric.edu

Fredric AgatsteinRhode Island College

Aaron YarlasUniversity of California - Los Angeles

Linda AlbrightWestfield State College

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Recommended CitationMalloy, Thomas E.; Agatstein, Fredric; Yarlas, Aaron; and Albright, Linda, "Effects of Communication, Information Overlap, andBehavioral Consistency on Consensus In Social Perception." (1997). Faculty Publications. Paper 130.http://digitalcommons.ric.edu/facultypublications/130

INTERPERSONAL RELATIONS AND GROUP PROCESSES

Effects of Communication, Information Overlap, and BehavioralConsistency on Consensus in Social Perception

Thomas E. Malloy and Fredric AgatsteinRhode Island College

Aaron YarlasUniversity of California, Los Angeles

Linda AlbrightWestfleld State College

Three experiments (N = 69, 162, and 201, respectively) were conducted to test the mathematicallyderived predictions of the Weighted Average Model (D. A. Kenny, 1991) of consensus in interpersonalperception. Study 1 estimated the effect of perceiver communication, Study 2 estimated the effectsof communication and stimulus overlap, and Study 3 estimated the effects of communication, overlap,and target consistency on consensus. The strongest consensus was found when perceivers communi-cated about highly overlapping information about targets who were cross-situationally consistent.Conversely, the lowest level of consensus was observed when perceivers did not communicate and hadnonoverlapping information about targets who were cross-situationally inconsistent. Both stimulusvariables (overlap and consistency) and an interpersonal variable (communication) affected consen-sus as predicted by the Weighted Average Model.

The Weighted Average Model (W\M) developed by Kenny(1991) is a formal mathematical specification of the effect ofsix variables on the level of consensus (i.e., interpersonal agree-ment) when multiple judges rate a common target. The variablesof W\M include: perceiver-target acquaintance, stimulus over-lap and shared meaning systems between two perceivers, consis-tency of the target's acts, extraneous information, and communi-cation between perceivers. Below, we consider conceptually andformally the parameters of W\M.

Parameters of W \ M

Acquaintance is the amount of information perceivers haveabout the stimulus target, and intuitively, as information in-creases, consensus should also increase. The effect of acquain-

Thomas E. Malloy and Fredric Agatstein, Department of Psychology,Rhode Island College; Aaron Yarlas, Department of Psychology, Univer-sity of California, Los Angeles; Linda Albright, Department of Psychol-ogy, Westfield State College.

This research was supported in part by Rhode Island College facultyresearch funds and a National Science Foundation Graduate fellowshipto Aaron Yarlas. We thank David A. Kenny for assistance with conceptu-alizing and programming simulations of the Weighted Average Modeland for his comments. We also thank our research assistants: SuzyBarcelos, Sheryl Kopel, Linda Pelopida, and Lynn Winquist.

Correspondence concerning this article should be addressed toThomas E. Malloy, Department of Psychology, Rhode Island College,Providence, Rhode Island 02908. Electronic mail may be sent via theInternet to tmalloy@grog.ric.edu.

tance has been emphasized in social perception research (e.g.,Albright-Malloy, 1987; Hinder & Colvin, 1988; Kenny, Al-bright, Malloy, & Kashy, 1994; Newcomb, 1961). Stimulusoverlap is the degree to which multiple judges observe the samebehaviors of the target in the same setting, and is a parameterthat, according to Kenny (1991), has been ''largely ignored"(p. 156) in research on social perception. If two perceivers viewa single act by a target and interpret that act similarly, the twohave a shared meaning system. For example, if perceivers judgea smile as indicative of sociability, then they will use the same"social grammar" to interpret the meaning of acts. Meaningsystems are likely a product of culturally specific tutelage (Vy-gotsky, 1962, 1978), although cross-cultural research in emo-tion (Ekman, 1992a, 1992b) and personality perception (Al-bright et al., 1997) has suggested some meaning systems maybe universal. The target consistency parameter is concerned withthe degree of behavioral stability across situations; this has beenstudied extensively (e.g., Kenrick & Stringfield, 1980; Mis-chel & Shoda, 1995). Extraneous information' is a basis ofjudgment that is not linked to the target's overt behavior. Forexample, if a perceiver judges a target by using informationabout category membership that is irrelevant to overt behavior,then extraneous information is a source of the perception. Fi-nally, communication is the exchange of independently derivedinformation about a target by perceivers.2

1 Extraneous information has also been called unique impression (seeKenny, 1991, p. 159).

2 Although WAM has been developed to include additional variables(Kenny et al., 1994), the focus here is on the 1991 model.

Journal of Personality and Social Psychology. 1997, Vol. 73. No. 2. 270-280Copyright 1997 by the American Psychological Association, Inc. 0022-3514/97/J3.00

270

EFFECTS OF COMMUNICATION, OVERLAP, AND CONSISTENCY 271

WAM: An Integrative Heuristic

The variables of WAM reflect the assumption that consensusis a product of three simultaneous processes: stimulus effects,intraindividual social cognitive processes, and interpersonal pro-cesses. W&M is related conceptually to other probabilistic func-tional approaches (e.g., Brunswik, 1956; Funder, 1995) to per-ception that emphasize distal effects (i.e., stimulus features),proximal effects (sensory and neural mediation as well as infer-ence processes), and the effects of the broader ecology withinwhich perception occurs. In W\M, stimulus effects on consen-sus are the amount, the consistency, and the overlap of informa-tion. The processes through which stimuli affect social percep-tion has been emphasized in ecological models (e.g., Baron &Misovich, 1993; McArthur & Baron, 1983).

Intrapersonal social cognitive processes are represented bythe shared meaning and extraneous information parameters.Given some stimulus information, to what extent do differentindividuals have a similar phenomenological experience of it,and to what extent do unique, unshared cognitive processesinfluence judgments? An extensive literature has focused onthese processes (e.g., Nisbett & Ross, 1980) and, for example,social stereotypes are shared meaning systems that produceconsensus.

Finally, the communication parameter gives W\M an interper-sonal character, reflecting an assumption that, to some extent,consensus is a social construction (Vygotsky, 1978). Thesemetatheoretical features of W5\M produce a highly integrativeheuristic that bridges multiple approaches to social perception.

Kenny's Formalization of the WAM Parameters

With exposure to a target's acts (i.e., behavior and appear-ance), WAM states that consensus among perceivers (r) is afunction of the simultaneous effect of the following fivevariables:

qnp2 (1 - pi) + n2pjp2

k2 + n (1 - p^ + «Vi(1)

where q is the proportion of overlapping acts observed by thejudges, n is the number of target acts seen by both judges, p{

is the degree of consistency of target acts across time or situa-tion, p2 is the similarity of judges' meaning systems, and k isthe extraneous information judges use when rating a target.

Equation 1 assumes that judges have not communicated theirindependent impressions. When there is some communication,the consensus correlation r of Equation 1 may be adjusted bythe communication parameter (a), which yields r ' :

r + a2r + 2a

1 + a2 + 2ar(2)

Communication may lead judges to agree that the target's behav-ior represents the same personality characteristic, or communi-cation may polarize judgments. Of most interest in this researchis the case in which communication produces agreement. Sincethe presentation of WAM, three classes of studies have testedits predictions. They are reviewed below.

Mathematical Simulation of Consensus Using

Mathematical simulations using WAM have confirmed intu-itively derived assumptions regarding model variables and con-sensus, but they have also produced some counterintuitive con-clusions. For example, WAM predicts that when judges are pre-sented with identical information (q — 1) about a target showingsome degree of behavioral consistency (i.e., p\ > 0), increasingthe number of acts will not increase consensus (assuming thatjudges do not use only extraneous information and that theyshare common meaning systems). As the proportion of overlap-ping information declines (q < 1), consensus will be influencedby acquaintance, because judgments are based on larger samplesof acts and, as a result, are more reliable. In another simulation,Kenny demonstrated that under a set of conditions in whichunique impressions are high (k = 1), target consistency is low(p! = .05), meaning systems are shared by judges (/?2 = .5),and overlap is complete (q = 1), consensus does not increasewith increased acquaintance.

However, manipulation of the parameters of Equations 1 and2 in mathematical simulations may or may not reflect the rela-tionships between the terms of WAM and consensus in empiricaldata. Consequently, other research has tested WAM empirically.

Research Design Constraints on Parameters

One approach has been to control WAM parameters throughconstraints on the design and empirical operations of a study.For example, Albright, Kenny, and Malloy (1988) studied con-sensus at zero acquaintance (n = 0) with complete overlap (q-I) and attempted to isolate the impact of shared meaningsystems (p2). Consensus was found to result from similar mean-ing attached to appearance cues.

In related work, Malloy, Albright, Kenny, Agatstein, and Win-quist (1997) designed a study in which a single target individualwas judged on the Big Five personality dimensions by membersof three different social groups: friends, family, and coworkers.A constraint imposed was that the members of different socialgroups be unacquainted (n = 0), that they never simultaneouslyobserved the target engage in behavior {q = 0 ) , and that theynever communicated with one another (a - 0) about the target.In this study, WAM variables—overlap, communication, andacquaintance—were held constant at zero between, but notwithin, social groups, and the study showed that agreementwithin groups was substantially greater than agreement betweengroups.

Direct Evaluation of 'WAM Parameters

As an alternative to mathematical simulations and passivecontrol, some investigators have either directly measured orexperimentally manipulated the parameters of WAM. For exam-ple, Chaplin and Panter (1993) measured the effect of sharedmeaning (p2) following exposure to behavioral descriptions(e.g., "being pleasant when a stranger asks for directions") asindexed by ratings of the typicality, difficulty, and evaluation ofthe behavioral acts. Judges also rated 25 individuals who hadreceived substantial media attention on two dimensions: friendli-ness and organization. Ten judges were randomly selected fromthe total sample, and the relationship between the shared mean-

272 MALLOY, AGATSTEIN, Y\RLAS, AND ALBRIGHT

ing measure on three dimensions (typicality, difficulty, and eval-uation) was correlated with a measure of interjudge agreement.Chaplin and Panter (1993) concluded that this study provided' 'substantial support for the hypothesis that shared meaning oneach of the three dimensions is related to rating agreement"(p. 562).

Tn a second study, Chaplin and Panter (1993) measured theshared meaning parameter (p2), experimentally manipulated thedegree of consistency {p\) of two targets on personality dimen-sions (playfulness and openness), and experimentally manipu-lated communication (a) regarding target characteristics. Theresults of this second study confirmed the results of their firststudy and showed that "shared meaning strongly predicted inter-judge agreement" (Chaplin & Panter, 1993, p. 575). However,this study failed to support the prediction that target consistencyand communication would affect interjudge agreement.

In a study conducted by Park, DeKay, and Kraus (1994),perceivers judged rive different targets on the basis of self-gener-ated descriptions in five different social situations (25 judgmentsin total) under one of three conditions. In the two conditionsof most interest here, judges were either unaware that the 25descriptions were generated by five people in five different situa-tions, or were clearly aware of this. By using variance compo-nents, three terms of WAM were estimated: target consistency(/?]), shared meaning systems (p2), and a parameter estimatingthe degree to which two judges perceived the target similarlyin two different situations (p3; e.g., A rates B in the worksituation, and C rates B in the context of friends). Resultsshowed that the magnitude of parameters px and p$ varied acrossthe known and not-known conditions, but the shared meaningparameter (p2) was consistent across the known and not-knownconditions. Overall, when judges knew they were rating fivepeople in five different situations, target information was inte-grated in such a way that consistency across situations wasimposed by the judge (px). Regardless of whether judges knewor did not know they were rating the same target in five differentsituations, they showed a clear tendency to "agree on theirinterpretation of the meaning of the same act" (Park et al.,1994, p. 444), and p2 was "substantial" in both experimentalconditions. Further, Park el al.'s (1994) results confirmed a keyassumption of V\&.M that p3 = p\P2 and are consistenl withdata reported by Malloy et al. (1997) in showing rather weakagreement among different judges (family, friends, coworkers)who rated a single target in different situations.

Comparing the results of Chaplin and Panter (1993) withthose of Park et al. (1994), there is consistent support for theimpact of shared meaning on interjudge agreement. These twostudies differ in regard to estimates of the effect of target consis-tency, but there is also another important difference betweenthem. Chaplin and Panter manipulated the consistency of targetinformation across situations and observed a weak effect,whereas Park et al. estimated the level of target consistency onthe basis of judges' perceptions and found a stronger effect.Clearly, the consistency parameter of WAM deserves furtherscrutiny. In addition, Chaplin and Panter's failure to confirmthe predicted communication effect on consensus suggests theneed for additional attention to this variable. It is possible thatthe communication intervals used in their manipulations (1- or3-min discussion periods) were not sufficient to affect consen-sus. Therefore, in the present studies we used much longer com-

munication intervals. Further, Chaplin and Panter (1993) in-structed judges to "try to tbrm an impression about the personand get a good sense about what that person is like" (p. 571).This instruction may have made judges more confident in theirown assessment and more resistant to the influence ofcommunication.3

The Present Research

This research is similar to that of Chaplin and Panter (1993)and Park et al. (1994). In three studies, we undertook a sequenceof experimental manipulations of "WAM parameters. First, westudied the effect of perceiver communication on consensus.This foundation study was important because W\M predictsthat communication increases consensus, but Chaplin and Pant-er' s study failed to confirm this. However, by increasing thecommunication interval and using more general instructions toperceivers regarding the judgment task, we expected to find acommunication effect on consensus. We also manipulated thenature of communication itself. In the first study, communicationabout target characteristics was general, whereas in the secondstudy communication about targets was focused on specifictraits. This second study also included manipulation of the stim-ulus overlap parameter of W\M. Finally, a third study includedmanipulations of the communication, stimulus overlap, and tar-get consistency parameters.

In addition to the W\M variables manipulated in these stud-ies, the empirical operations and statistical analysis served tocontrol the remaining variables. Acquaintance was held constantwithin all the studies and was generally at a low level. Weassumed that perceivers, who were all undergraduates at a state-supported college of about 10,000 students and most of whomwere from the same geographic locale, had similar meaningsystems that were based on a common culture. Further, thestatistical analysis of social perception data (a social relationsanalysis) controlled individual differences in meaning systemsand judges' unique responses to a specific target. So, overall,the parameters of W\M selected for experimental study (com-munication, overlap, and stimulus consistency) were isolatedwhile the remaining parameters were held constant or controlledanalytically.

Study 1

Method

Participants

Sixty-nine Rhode Island College students recruited from undergradu-ate psychology classes participated in the study, which we claimed wasto focus on "personality traits."

Procedure and Design

Participants watched a 15-min videotape of four individuals (two menand two women, aged 17-22 years) discussing the appropriate age tolegally drink alcohol. The individuals were volunteers from the RhodeIsland community and were unacquainted. On arrival at a taping session,

5 We thank an anonymous reviewer who clarified this point for us.

EFFECTS OF COMMUNICATION, OVERLAP, AND CONSISTENCY 273

they were instructed to discuss with one another the appropriate age tolegally consume alcohol.

The 69 participants were assigned randomly to groups of 2 or 3,and groups were then randomly assigned to one of two experimentalconditions. In the communication condition, after viewing the targetsdiscussing the age to legally consume alcohol, perceivers were instructedto "discuss the personality characteristics of each individual on thetape" and were given 10 min for this discussion. Groups of perceiversin the control condition observed the videotaped discussion but did notdiscuss the targets' characteristics. Perceivers in the communication andno-communication (control) conditions then independently rated, fromtheir separate cubicles, the four targets on the videotape on 20 traits byusing 7-point bipolar dimensions. The 20 trait names and their opposites,selected to represent each of the Big Five personality factors were asfollows: sociable, friendly, humorous, and talkative (Factor I) ; warm,honest, flexible, and agreeable (Factor II); responsible, careful, self-disciplined, and organized (Factor III); secure, confident, independent,and calm (Factor IV); intelligent, knowledgeable, wise, and creative(Factor V). The traits appeared in a random order. A two-group designwas used, but nested within each of the levels of the communicationfactor were nine Perceiver x Target matrices.

Analyses

First, we decomposed the social perception scores from the PerceiverX Target matrices into component sources of perceiver, target, and rela-tionship plus error. We then estimated the absolute variance of the targetcomponents within each of the 18 matrices. These analyses were accom-plished by using the BLOCKO computer program (Kenny, 1995). Thisapproach is called a social relations analysis (Kenny, 1994).

The variance of the target components in a social relations analysisis an estimate of consensus in interpersonal perception (see Kenny etal., 1994, for a detailed discussion). The absolute target variance forthe four indicators of each of the five factors was used to form a con-struct. We conducted an analysis to test the hypothesis that the absolutevariance of the five factors and an overall-average factor was equal tozero. These analyses focused on the question "Ts there reliable consensusin the perceivers' ratings of targets' personality characteristics?" Wealso considered variability in consensus across the Big Five factors.

The next step was to estimate the effect of the communication manipu-lation on consensus. For this analysis, the absolute construct variances4

(based on four traits for each factor) from the social relations analysiswere compared by using Student's t to test for mean differences in thelevel of consensus on factor variances in the communication and no-communication conditions. Because the prediction tested was that therewould be greater consensus in the communication condition, we con-ducted one-tailed significance tests. We also estimated the effect of themanipulation (Cohen's d) on construct variance for each factor.

Results and Discussion

Levels of Consensus

Table 1 shows that there was statistically reliable consensuson all five factors across the 18 groups of perceivers. For FactorsI through V, absolute variances and proportion of total variancedue to the target component were: (I) 1.03 and .24, (II) 0.14and .03, (III) 0.47 and .16, (IV) 0.27 and .08, (V) 0.40 and.15, respectively. Across the five factors, the absolute target vari-ance was 0.46, was reliably different from zero, and accountedfor about 13% of the total variance in trait ratings.

Although WAM makes no predictions about variability inconsensus across traits, we also considered this factor. A re-peated measures analysis of variance (ANOVA.) demonstrateda main effect due to the Big Five factors, F(4, 13) — 3.33, p

Table 1Study 1: Consensus in Trait Ratings as Measured by Absolute

and Relative Target Variances

Factor

ITIM

IHb,civa,b

vc ,dAverage

Absolute variance

1.03*0.14*0.47*0.27*0.40*0.46

Relative variance

.24

.03

.16

.08

.15

.13

Note. Each factor variance is based on four traits. The social relationsanalysis uses replications across groups (G), so each variance has 17 df(G - 1). Average variance was aggregated across factors. Seven-point(1-7) scales were used. Factors that share letter subscripts have meanvariances that did not differ significantly at p > .05.*P < .05.

= .04. As shown in Table 1, mean variances on the factors weresignificantly different for all pairs of means (all ps < .02),except for Factors II and IV, r(17) = .89, p = .39; Factors Hiand IV, r(17) = 1.66, p = .12; Factors II and V r(17) = 2.02,p = .06; and Factors III and V, z(17) = .65, p = .53. Factor Tconsensus was greater than consensus on all other factors (aver-age/? = .02), confirming past research (Kenny et al., 1994).

Effect of Communication on Consensus

Table 2 shows that relative to the no-communication condi-tion, there was greater target variance in the communicationcondition on all five factors and on the overall factor. Consensusin the communication condition was significantly higher than inthe no-communication condition on four of five factors: I (1.48and .58), III (0.73 and .21), IV (0.65 and .00),5 and V (.68and .13, p = .06), and on an average across the five factors(.75 and .20). Perceiver communication did not significantlyaffect consensus on Factor II (.21 and .07). Estimates of theeffect of the manipulation in a standard deviation metric (Co-hen's d) for Factors I through V were 0.88, 0.48, 0.95, 1.52,and 0.82, respectively. Across the five factors, mean consensusin the communication condition was 1.27 SDs higher than inthe no-communication condition, supporting the hypothesis thatcommunication increases consensus, as predicted by Wi\M.

This study had two noteworthy methodological features. First,the communication manipulation was not focused on specifictraits. Perceivers were instructed to "discuss the personalitycharacteristics of each individual on the tape" and to rate eachtarget on specific traits after a 10-min period of general discus-sion. Second, although WAM assumes that communication

4 Absolute rather than relative variances from the social relations anal-ysis were analyzed because less restrictive assumptions underlie theanalysis of these unstandardized estimates. Using relative variances withgroup as the unit of analysis would have, in effect, produced a measureof consensus within each group that is in a different metric.

5 In the analysis of variance components that use least squares proce-dures, estimates may be negative (see Searle, 1971). We have assumedthat when the true component variance is zero, the estimated samplevariance will be negative half of the time (Malloy & Kenny, 1986).Negative variances should be treated as zero.

274 MALLOY, AGATSTEIN, YARLAS, AND ALBRIGHT

Table 2Study 1: Effect of Communication on Consensus in Judgments on Big Five Factors

Factor

ITIUIIVVAverage

Experimental condition

Communication

Abs. variance

1.480.210.730.650.680.75

Rel. variance

.30

.03

.15

.14

.18

.16

No communication

Abs. variance

.58

.07

.21

.00*

.13

.20

Rel. variance

.15

.01

.05

.00

.05

.05

'(16)

1.75*0.961.89*3.03*1.632.54*

Effectsize d

0.880.480.951.520.821.27

Note. Results are mean target construct variances and are based on four traits per construct (absolutevariances from the social relations analysis) for the 18 groups. Abs. = absolute; rel. = relative."This variance was actually negative (—.11) but was set to zero (see Malloy and Kenny, 1986, for adiscussion of negative variance in social relations analysis).*p < -05.

among perceivers increases consensus, the degree to which per-ceivers have access to overlapping information about a target isalso a ''critical parameter in determining the level of consensus"(Kenny, 1991, p. 161). In general, WAM predicts that as bothcommunication and overlap increase (assuming exposure to anequal number of target acts and equivalent meaning systems),consensus will likewise increase. Therefore, a second study wasdesigned to (a) replicate the communication effect, (b) extendthe communication manipulation by making it more focusedand trait specific, and (c) estimate the extent to which the com-munication effect interacts with stimulus overlap.

Study 2

Method

Participants

One hundred and sixty-two Rhode Island College students recruitedfrom undergraduate psychology classes participated in the study, whichwe claimed was to focus on "personality rating."

Procedure and Design

Participants watched a 15-min videotape of four individuals (die sameas in Study 1) discussing the appropriate age to legally consume alcoholin the state of Rhode Island. Study 2 included two independent variables:perceiver communication and stimulus overlap. Although the no-commu-nication control conditions were identical in Studies 1 and 2, the commu-nication manipulation in Study 2 was highly focused on specific traits,as demonstrated in the following instructions:

Now you are to discuss the people Scott, Denise, Bill, and Christhat you just watched while they discussed the appropriate age forlegal drinking on die videotape. %u are to discuss for three minuteseach, eight different personality traits of the four people on thetape. We would like everyone to speak during all 8 of these threeminute discussions.

An experimenter ensured that all perceivers discussed each target oneach of eight traits. The order of traits was random for each of the 64groups.

The stimulus overlap manipulation was accomplished by the followingoperations. First, perceivers in groups were presented with the same

(i.e., overlapping) randomly selected segments of the videotape of thefour individuals discussing the issue of legal alcohol consumption. How-ever, the amount of overlapping information was manipulated. Perceiversin half the groups had 10% overlapping segments of the tape, whereasthose in the remaining groups had 80% overlapping tape segments. Afterviewing the overlapping tape segments, perceivers were presented withnonoverlapping tape segments. The operations ensured that all perceiverswere exposed to an equal amount of stimulus information while varyingthe degree to which the information was overlapping.

The 162 participants were assigned randomly to groups of 2 or 3,and groups were assigned randomly to one of four experimental condi-tions. After watching either 10% or 80% overlapping information, parti-cipants either did or did not communicate about the targets. All perceiversthen independently rated the four targets on the videotape on eight bipo-lar, 7-point ( 1 - 7 ) scales. Given the more focused and time-consumingnature of the communication manipulation, it was necessary to reducethe number of trait dimensions on which perceivers rated targets. Eightdimensions were selected on the basis of two criteria: at least a moderatelevel of consensus in Study 1 and at least one trait for each of the BigFive factors. In addition, the trait leadership (a Factor I indicator) wasincluded in Study 2, although it was not included in Study 1. Theremaining seven traits (with their opposites) represented the factors:talkative (I) , sociable (I), agreeable (II), flexible (II), mature (III),secure (IV), and intelligent (V). Overall, a 2 X 2 design was used, butnested within each of the four conditions were 16 Perceiver x Targetmatrices.

Analyses

We decomposed the social perception scores from the Perceiver xTarget matrices into the component sources of perceiver, target, andrelationship plus error. We then estimated the variance of die targetcomponents within each of the 64 matrices. This social relations analysiswas accomplished by using BLOCKO (Kenny, 1995). The absolute andproportion of total variance for the factors were estimated and thenaveraged. This analysis was focused on the following question: "Isthere reliable consensus in the perceivers' ratings of targets personalitycharacteristics?"

We then estimated the effect of the communication and overlap manip-ulations on consensus and analyzed the 64 absolute target variances (onefrom each group of perceivers) for the five factors from the socialrelations analysis by using an ANOVA. Estimates (Cohen's d) of themain and interaction effects on consensus were also computed.

EFFECTS OF COMMUNICATION, OVERLAP, AND CONSISTENCY 275

Results and Discussion

Level of Consensus

The social relations analysis showed that there was reliableand rather substantial consensus on target ratings for all fivefactors in Study 2. The highest level of consensus was observedon Factor I (3.46), with about 70% of the total variance inratings on this factor being due to the target. Substantial consen-sus was also observed on Factor IV (2.84), Factor ID (1.77),and on Factor V (1,18). The average level of consensus onFactor II was 1.26. As in Study 1, we also considered the traiteffect on consensus, and a repeated measures ANOV\ showedsignificant differences in consensus across factors, F( 2, 66) —26.87, p = .04. As shown in Table 3, mean target variances onthe factors were significantly different (all ps < .04) for allpairs of means, except for Factors IT and V, r(63) — 0.29, p =.11. As in Study 1, consensus on Factor I was greater (all ps< .01) than on all other factors.

A t test comparing the two independent average variancesacross the five factors for Studies 1 and 2, with group as theunit of analysis (.46, n = 18, and 2.10, n = 64, respectively),showed significantly more consensus in Study 2, r(80) = 6.90,p < .001.

Effect of Communication

The effect of communication on consensus was statisticallyreliable for all Big Five factors, as may be seen in Table 4.Effect estimates (Cohen's d) measuring the differences betweenthe communication and no-communication conditions in a stan-dardized metric for each of the five factors were as follows:Factor T, 1.37; Factor II, 1.53; Factor III, 1.56; Factor IV, 1.44;and Factor V, 1.33. Across the five factors, the more focusedcommunication manipulation of Study 2 produced an overalleffect estimate of 1.45, showing a greater communication effectrelative to the overall communication effect of Study 1 (1.27).

Effect of Stimulus Overlap

The manipulation in which perceivers viewed either 10% or80% overlapping information did not significantly affect consen-sus on any factor. As can be seen in Table 4, the effect (Cohen's

Table 3Study 2: Consensus in Trait Ratings as Measured by Absoluteand Relative Target Variances

Factor Absolute variance Relative variance

InflIIIIVvaAverage

3.46*1.26*1.77*2.84*1.18*2.10

.70

.36

.53

.62

.44

.53

Note. Variances are based on social relations analysis of data from 64groups. Relative variance is the proportion of total variance. Factors arebased on the Big Five. Metric is 1 to 7. Factors that share subscriptshave mean variances that did not differ significantly at p > .05.*p < .05.

d) of overlap on consensus for the five factors ranged from .06to .40, with an average of .15, which shows that the overlapmanipulation had a weak effect. The level of consensus acrossall factors (i.e., absolute target variance) was 2.28 in the 10%and 2.38 in the 80% overlap conditions, respectively. In addition,in no case was the Overlap X Communication interaction termin the ANOVA statistically significant. The estimate of the interac-tion effect on the overall measure showed that only about 1% ofthe variance in consensus was accounted for by the Communica-tion X Overlap interaction. The failure to confirm the Communi-cation X Overlap interaction predicted by W\M could have beendue to the very high level of behavioral consistency exhibited bythe four stimulus targets in the videotape used in Studies 1 and2. The manner of presentation of the stimulus targets was designedto show natural social interaction among four individuals withvery little constraint on behavior by the experimenter. That is,the situation was designed to be what Snyder and Ickes (1985)called "weak," which should have facilitated the expression oftrait dispositions. In this tape, the four unacquainted individualscame to the laboratory, met for the first time, and spent 15 mindiscussing the appropriate age to legally consume alcohol. Theonly constraint on their behavior was the content of the conversa-tion, and we found that the four individuals maintained consistentpositions on the issue and behaved consistently throughout thediscussion. In terms of W\M, the consistency parameter was veryhigh and, as a result, the overlap manipulation in which perceiversviewed common segments of the videotape (either 10% or 80%in common) may not have had the intended effect. Even thoughfor some perceivers only 10% of the acts viewed were identical,the actual overlap may have been much higher because the acts(e.g., verbal statements offering a position on the issue) werehighly consistent across the 15-min discussion period.

As a result, we designed a third study that included threevariables of theoretical interest in WAM: communication, stimu-lus overlap, and target consistency. However, the inclusion ofthe consistency variable in the design required that we abandonthe natural and uncontrolled social interaction of the stimulustape used in Studies 1 and 2 to gain more control over consis-tency. As a result, we created hypothetical stimulus targets sothat consistency of "acts" could be actively manipulated.

Study 3

Method

Participants

Two hundred one students recruited from undergraduate psychologyclasses at Rhode Island College participated in the study, which weclaimed was to focus on "personality rating."

Procedure and Design

The study included three manipulated variables: the consistency oftarget behavior, the degree of overlapping stimulus information, and com-munication among perceivers. The overall structure of the design was 2X 2 x 2. Participants (perceivers) were presented with information abouttwo people (called targets) in two different situations. This informationwas in the form of sentences describing behavior. Five sentences describedbehavior in Situation 1, and five sentences described behavior in Situation2 for each target. Within each situation, one target was always describedby using four sentences containing Factor I (extraversion) traits indicating

276 MALLOY, AGATSTEIN, YARLAS, AND ALBRIGHT

Table 4Study 2: Effects of Communication and Stimulus Overlap on Consensusin Judgments on Big Five Factors

I

Communication No communication

Factor 10% overlap 80% overlap 10% overlap 80% overlap FCom dam FOvEr dOver

Abs.Rel.

IIAbs.Rel.

IllAbs.Rel.

IVAbs.Rel.

VAbs.Rel.

OverallAbs.Rel.

4.42.42

2.54.32

2.99.57

4.45.58

2.42.24

3.42.41

4.77.43

2.13.28

2.78.56

4.69.60

1.55.16

3.55.42

2.25.02

0.13.02

0.54.20

1.08.25

0.39.04

1.13.18

2.37.28

0.13.02

0.77.26

1.14.27

0.28.03

1.20.19

29.24* 1.37 0.30 .14

36.13* 1.53 0.31 .14

37.64* 1.56 0.00 0.01

31.98* 1.44 0.06 .06

27.35* 1.33 2.46 .40

— 1.45 — .15

Note. Variances are based on data from 64 groups and 162 judges. Each condition mean is the averageabsolute (Abs.) target variance and is based on 16 groups from the social relations analysis. Overallrepresents the results for a single general factor. Rel. = relative variances; d = Cohen's effect estimate;Com = communication; Over — overlap,*p < .05.

high standing on the factor and one sentence with a trait selected randomlyfrom one of the four remaining Big Five factors. The other target wasdescribed by using one Factor I trait and four traits selected randomlyfrom the remaining factors. Targets had to vary on Factor I because themeasure of consensus we used was a variance and, at the limit, if targetsare identical then variance is expected to be zero.

As an example, the following two descriptions were given for twotargets that stood high and low, respectively, on Factor I in Situation 1.Target 1 was described as follows: "Target made the friend feel wel-comed and comfortable in the new situation", "Target complied whenasked to help members in a group perform a task", "Target interactedin a friendly manner with all the other members of the group'', ' 'Targetcaptivated the group with a dynamic description of the situation", and"Target often verbalized ideas during the group's discussion". Target 2was described as follows: "Target carefully planned and executed everystep of the task"; "After getting into the car, the target put on theseatbelt"; "Although tempted by the rich dessert, target adhered to thediet"; "Target had an exhibition of original artwork"; and "Targetoffered to care for a friend's child, while the friend was hospitalized".Participants were given 1 min to read the sentences containing the traitinformation in each situation.

Consistency manipulation. When targets were consistent across situ-ations, trait descriptions in Situations 1 and 2 were consistently high(80% of the traits indicated extraversion) or low (20% of the traitsindicated extraversion) on Factor I. When targets were inconsistent, theywere described by traits in which 80% of the information indicatedextraversion in Situation 1, followed by 20% extraverted trait informa-tion in Situation 2, or the reverse pattern was presented (20% extravertedtraits in Situation 1 followed by 80% extraverted traits in Situation 2).

Overlap manipulation. Judges (in groups of 2 or 3) received either100% overlapping (i.e., identical sentences) or 0% overlapping (com-pletely different sentences) trait information regarding extraversion foreach of the two targets. The amount of information was held constant,with five traits presented in Situations I and 2 (10 sentences total).

Communication manipulation. After presentation of target informa-tion, judges immediately made ratings of the target or communicatedfor 30 s about the target's standing on each of seven traits and thenmade ratings of the hypothetical targets.

Ratings of extraversion. Each of the two targets were rated by using7-point scales (1 -7 ) bounded by the following Factor I (extraversion)traits (and their opposites): friendly, outgoing, a people person, extra-verted, talkative, expressive, and social.

Statistical Analyses

We decomposed social perception scores from the Perceiver x Targetmatrices into the component sources of perceiver, target, and relationshipplus error. We then estimated the variance of the target componentswithin each of the 80 matrices. These social relations analyses wereaccomplished by using BLOCKO (Kenny, 1995). We then averaged theabsolute variances for the seven indicators of extraversion to produce asingle average variance.

We then estimated the effect of the communication, overlap, and con-sistency manipulations on consensus. .For this analysis, the 80 averageabsolute target variances (one from each group of perceivers) wereanalyzed by using an ANOVA. Manipulation effect estimates were alsocomputed.

Theoretical Predictions:Target-Consistency and Communication

Stimulus-Based and Interpersonal Main Effects

We predicted a main effect for target consistency such thatthere would be greater consensus for consistent than for incon-sistent targets. A main effect for communication was also pre-

EFFECTS OF COMMUNICATION, OVERLAP, AND CONSISTENCY 277

dieted such that there would be greater consensus with, thanwithout, communication.

Interaction of Stimulus Effects: Overlap X ConsistencyInteraction

W\M predicts that the stimulus has an important effect onconsensus. When target behavior is inconsistent across situa-tions and is totally nonoverlapping across perceivers, the ambi-guity of the stimulus information is maximized. Stimulus ambi-guity is reduced when perceivers are exposed to consistent targetbehavior, even when that behavior is nonoverlapping. Therefore,we predicted that under the condition of nonoverlapping infor-mation consensus would be greater for consistent than for incon-sistent targets.

Interaction of Interpersonal and Stimulus Effects

Communication X Overlap interaction. Assuming thatidentical stimulus information affects judgments similarly, whenperceivers also communicate about their impressions, this shouldproduce an interactive effect on consensus. We predicted aninteraction of communication and overlap such that the commu-nication effect on consensus would be larger with 100% thanwith 0% overlap.

Communication X Overlap X Consistency interaction. Inaddition, we anticipated an even more complex interaction ofstimulus and interpersonal effects. Our prediction was that theinteraction effect of stimulus overlap and communication woulditself be moderated by the consistency of the stimulus informa-tion. That is, a triple interaction of communication, consistency,and overlap was predicted such that the tendency for communi-cation to increase consensus with 100% overlap was greater forconsistent than for inconsistent stimulus targets. We expectedthat the greatest consensus would be observed when perceivershad communicated about the same information that was consis-tent across situation.

Results and Discussion

The level of consensus in perceptions of extraversion was.41, ?(79) = 5.00, p < .05, on the extraversion factor acrossthe 80 groups; this finding replicates the results of Studies 1and 2. Mean absolute variances by experimental condition arereported in Table 5, and an ANOVA summary is presented inTable 6. Results showed significantly greater consensus in thecommunication condition than in the no-communication condi-tion, with mean variances of .63 and .37, respectively. Therewas also significantly greater consensus for consistent targets(.60) than for inconsistent targets (.27). These main effectsconfirmed the predictions derived from W\M.

The predicted interaction of consistency and stimulus overlapwas confirmed. Consensus was significantly higher for consis-tent targets (.68) than for inconsistent targets (.11) with non-overlapping information. Further, the interaction of communica-tion and overlap was confirmed, and the communication effecton consensus (.83) was larger with 100% than with 0% over-lap (.44).

A three-way communication X consistency X overlap interac-tion predicted by W\M was confirmed. To further decompose

Table 5Study 3: Effects of Communication, Stimulus Overlap,and Target Consistency on Consensusin Judgments of Extraversion

Communication No communication

Factor 0% overlap 100% overlap 0% overlap 100% overlap

Consistent stimulus target

Abs.Rel.Sim.

IAbs.Rel.Sim.

.67

.50

.50

.21

.22

.27

1.050.590.50

.68

.48

.26

Inconsistent stimulus target

0.610.460.50

.00b

.00

.00

.00s

.00

.27

.26

.26

.26

Note. Entries are means with 10 groups per cell. Metric is 1-7. Abs.= absolute variance; Rel. = relative variance; Sim. = predicted valuesof r' in Equation 2 based on a Weighted Average Model simulation."Variance was estimated as - .16. bVariance was estimated as - .08.See Malloy and Kenny (1986) for a discussion of negative variance insocial relations analysis.

this interaction, we estimated the joint effects of communicationand overlap separately within the inconsistent and consistentstimulus target conditions. The first 2 x 2 analysis produced anonsignificant communication X overlap interaction, F(l, 36)= 0.03, p = .87, d = .06, among inconsistent targets. The sameanalysis was then conducted within consistent stimulus targets,and the communication X overlap interaction was statisticallysignificant, F{\, 36) = 6.61, p = .01, d = .86. These resultsshow that communication about the same, temporally stableinformation was associated with the highest level of consensusand that the communication effect was descriptively nonexistentwith nonoverlapping, inconsistent stimulus information.

WAM Simulation of Study 3 's Results

Of the three studies, Study 3 contained explicit informationabout the values of the greatest number of W\M parameters.Parameter pi was experimentally manipulated so values were 1and 0 for consistent and inconsistent stimulus targets, respec-tively. Parameter q was equal to 0 in the 0% overlap and to 1in the 100% overlap conditions. Acquaintance («) was constantat 10 acts (i.e., sentences). Unique impression (k) was assumedto be zero because the perceiver and relationship componentswere partitioned from the target component. By using theseassumed values of WVM parameters, estimates for p2 (meaningsystems) and a were produced by using Equations 1 and 2.Communication was estimated rather than fixed to some a priorivalue, because although this variable was experimentally manip-ulated, we did not assume that communication would produceperfect agreement among judges (i.e., a = 1.00). By usingEquations 1 and 2, we estimated parameter a at .137 and p2

at .263.Then, by using these assumed and estimated values for WAM

parameters, we used an iterative, least squares estimation crite-

278 MALLOY, AGATSTEIN, YAKLAS, AND ALBRIGHT

Table 6Effects of Communication, Overlap, and Target Consistency on Consensus

Source of variance main effects

CommunicationOverlapConsistencyCommunication X OverlapCommunication X ConsistencyOverlap x ConsistencyCommunication X Overlap X Consistency

Residual errorTotal

df

1111111

7179

MS

4.210.101.912.030.411.781.690.410.53

F

10.170.254.614.900.994.294.09

P

.002

.62

.04

.03

.32

.04

.05

d

.72

.11

.48

.50

.22

.47

.46

Note. Fs were converted to rs to compute d. MS = mean square.

rion to produce the best fitting values of r' of Equation 2 for eachof the eight conditions of Study 3. These results are presented inTable 5 and show that the empirical estimates of consensus (ina standard relative variance metric) are generally reproducedclosely by Equations 1 and 2 under the assumed and estimatedvalues of WAM parameters. The greatest discrepancy occurredfor consistent stimulus targets with no communication at bothlevels of stimulus overlap. In the 0% condition, A\AM underesti-mated consensus (.48 observed and .26 predicted), whereas inthe 100% overlap condition WAM predicted .27, and the empiri-cal estimate was .00.

Integration of Results From Studies 1, 2, and 3

A summary of the effect .sizes of WAM parameters on consen-sus in each of the studies is presented in Table 7. The effectsizes' magnitudes are quantified by Cohen's d. To compute theds, we calculated the square roots of the Fs (given 1 df), whichyielded t, which we then doubled. This product was then dividedby the square root of df tor the residual source of variance. Asone may see in Table 7, in terms of main effects, the greatesteffect on consensus was due to interpersonal communication,with an average effect estimate of d - 1.15 across the threestudies. Considering the stimulus effects on consensus, the sin-gle estimate of the consistency effect (d = 0.48) from Study 3was about 3.69 times greater than the average stimulus overlap

Table 7Magnitude of Stimulus and Interpersonal Effects onConsensus in Studies 1, 2, and 3

Experimental effect

CommunicationOverlapConsistencyCommunication X OverlapCommunication X ConsistencyOverlap X ConsistencyCommunication X Overlap X Consistency

1

1.27*——————

Study

2

1.45*0.15

—0.04

———

3

0.72*0.110.48*0.50*0.220.47*0.46*

Note. Entries are Cohen's da. Dashes indicate effect was not estimatedin the study.*p < .05.

effect from Studies 2 and 3 (d - 0.13). Considering just maineffects of WAM parameters on consensus, it is clear that commu-nication had the greatest effect, followed by consistency andoverlap, respectively.

However, as predicted by WAM, there is clear evidence ofa complex interaction of interpersonal communication and thestimulus effects of overlap and consistency. When targets wereconsistent across situations, there was a communication X over-lap interaction that was statistically significant (effect estimated = 0.86). However, when stimulus targets were inconsistent,the communication x overlap interaction was not significant,and the effect estimate was much smaller (d = 0.06).

Overall, this pattern of results shows that interpersonal com-munication had a strong effect on consensus and that the consis-tency effect was moderate. The two estimates of the overlapmain effect, however, are relatively much weaker. Yet the overlapmanipulation, when coupled with communication or target con-sistency, did result in moderate effects on consensus (d = 0.50and 0.47, respectively). Further, when communication was cou-pled with consistent and overlapping judgment-relevant stimulusinformation, the highest level of consensus (absolute variance= 1.05) was observed.

General Discussion

Three experiments were designed to estimate the effects ofperceiver communication, overlapping stimulus information, andthe consistency of targets' acts across situations on consensusin social perception. The specific predictions of the studies werederived from the W^M (Kenny, 1991), and consensus was esti-mated by using the variance measure from a social relationsanalysis (Kenny et al., 1994).

Interpersonal Communication Effect on Consensus

All three studies confirmed the prediction that communicationamong perceivers increases consensus. Moreover, the resultsshowed that perceiver communication increases consensus whenthe stimulus targets are either real people engaged in videotapeddiscussion (Studies 1 and 2) or hypothetical targets describedonly by trait adjectives embedded in sentences (Study 3). Fur-ther, the communication effect held when perceivers were givena general, unfocused instruction to discuss the personality char-acteristics of the targets (Study 1) and when the communication

EFFECTS OF COMMUNICATION, OVERLAP, AND CONSISTENCY 279

instruction was highly focused and directed perceivers to discussspecific trait dimensions (Studies 2 and 3).

In Studies 2 and 3, we were able to assess the interactiveeffect of perceiver communication and overlapping stimulus in-formation. However, there was some variation in the specificlevels of the overlap manipulations across studies (10% or 80%in Study 2 and 0% or 100% in Study 3) and the nature of thestimulus targets (real people videotaped while engaging in adiscussion in Study 2 and hypothetical targets described by traitadjectives in Study 3) . Further, because we observed that targetbehavior in Study 2 was highly consistent across the 15-mindiscussion, we compared its results with the equivalent resultsfrom Study 3 only under the condition of target consistency.When the variances from Studies 2 and 3 (high consistencyonly) were averaged in a single 2 (communication) x 2 (over-lap) matrix (26 groups of judges per cell), ignoring the differ-ences in the degree of overlap across studies, we found thatcommunication about highly overlapping information producedgreater consensus than any other combination of the communi-cation and overlap manipulations. Conversely, in Study 3, underthe condition of target inconsistency across situations, the lowestlevel of consensus was observed under the joint conditions ofzero overlap and no communication. When targets were incon-sistent across situations and judges viewed different samplesof behaviors that were not discussed, there was essentially nointerrater agreement.

We can not know with certainty why Chaplin and Panter(1993) failed to observe a communication effect on agreement,but we have considered two plausible explanations. First, thecommunication intervals they used in their manipulations were1 and 3 min, whereas in the present studies, communication was10, 24, and 21 min in Studies 1, 2, and 3, respectively. Inaddition, Chaplin and Panter's instructions to perceivers to "geta good sense of what the person is like" may have produced aperception of targets that was less sensitive to influence bycommunication.

Broader Theoretical Implications

W\M specifies stimulus effects (consistency, overlap, ac-quaintance), perceiver effects (meaning systems, use of extrane-ous information), and interpersonal effects (communication)on consensus. The present studies considered the joint effectsof two stimulus characteristics (consistency and overlap) andinterpersonal communication while controlling acquaintanceand the perceiver effects with the design and analysis strategyused.

The data reported here pertaining to the communication, con-sistency, and overlap variables, as well as the work on meaningsystems (Chaplin & Panter, 1993; Park et al., 1994) and targetconsistency (Park et al., 1994), provide clear support for therole of the theoretical parameters of W\M as determinants ofconsensus. More important, support for the predicted interactionof these variables was provided by the experimental results aswell as by the mathematical simulations that used the data andassumptions about parameters from Study 3. Aside from docu-menting the effect of communication, these results also provideinformation relevant to a broader theoretical question: "Whatis the relative impact of interpersonal and stimulus effects onsocial perception?" These data suggest that both processes oper-

ate in tandem to affect social perception. As emphasized bysociocultural (Vygotsky, 1962, 1978) and social learning theo-ries (Bandura, 1986), interpersonal processes such as communi-cation and modeling are assumed to produce socially sharedconsensus. In fact, the communication manipulation producedthe largest effect on consensus relative to the other manipula-tions in this study. Yet when the communication parameter wasestimated in the mathematical simulation that used Study 3 data,it was smaller (a = .137 in a 0 -1 metric) than might be antici-pated given the length and focused nature of the communicationin this study. However, this particular estimate of parameter ageneralizes only to Factor I judgments of stimulus targets thatexist only as sentences.

The stimulus effects observed in the absence of and in combi-nation with communication suggest that consensus is alsorooted, to a significant degree, in the objective properties ofstimulus features (Brunswik, 1956; Funder, 1995; McArthur &Baron, 1983). Data consistent with this conclusion were re-ported recently by Baron, Albright, and Malloy (1995), whoshowed that unambiguous, judgment-relevant stimulus informa-tion (actual academic performance) had a much stronger effecton social perception (judgments of academic ability) than didsocial class information, which was not directly relevant to thejudgment task. Presumably, intrapersonal, interpersonal, andstimulus effects on social perception operate jointly to increasethe likelihood of functional adaptation to the environment.

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Received November 4, 1996Revision received March 3, 1997

Accepted March 3, 1997 •

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