Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!wuarchive!emory!gatech!udel!princeton!pucc!PSYCH@TCSVM From: harnad@phoenix.Princeton.EDU (Stevan Harnad) Newsgroups: sci.psychology.digest Subject: PSYCOLOQUY V1 #16 (Discussion Paper: Monkey Friendship/Rasmussen(576 l) Message-ID: <9012050027.AA05243@reason.Princeton.EDU> Date: 4 Dec 90 23:15:39 GMT Sender: VMNNPOST@pucc.Princeton.EDU (Listserv to Netnews Gateway) Organization: Listserv to Netnews Gateway at pucc.Princeton.EDU Lines: 571 Approved: PSYCH@TCSVM PSYCOLOQUY Tue, 4 Dec 90 Volume 1 : Issue 16 Paper: Monkey Friendship, Dennis R. Rasmussen ---------------------------------------------------------------------- [Editor's Note: This paper has been refereed by a member of Psycoloquy's Editorial Board and has been accepted for "skywriting" discussion. All subsequent discussion elicited on this topic will appear under the header: "Monkey Friendship/Rasmussen." Comments as well as discussion papers on other topics are invited. All contributions will be refereed.] From: "Dennis R. Rasmussen" Subject: Paper: Monkey Friendship This article bears on the following areas of research: Cognition; Comparative Psychology; Deception; Demography; Ethology; Primatology; Sociobiology. I would like to solicit comments from readers who are interested in all these fields. In particular, I would value the comments of my colleagues who study cognition in nonhuman animals; I may not agree with them but wish to try to understand their views more thoroughly. Like Skinner, I think we only see the behavior of other individuals. Hence the study of thoughts must always be studies of behavior; in humans the behavior may be very complex verbal and written behavior but it is still behavior. This is the most "cognitive" research article I've ever produced; it deals with "meanings" of behavior. I hope psychologists will be struck by the immense amount of potential research on the relationships between various types of affiliation: specific combinations of "affiliation" may each have a different meaning. Primatologists, myself included, have only scraped the surface of this level of understanding of how one nonhuman and nonverbal primate communicates with another. Not only do we need to study amounts and contexts of behavior, such as grooming, but we need to study how these amounts are associated with other patterns of behavior. It is not difficult to imagine a coding scheme where combinations and intensities of dozens of forms of affiliative behavior convey messages on the type and degree of an overall affiliative relationship. I would also value the comments of colleagues who work at the interface between Psychology and Demography. Sadly this is a somewhat undeveloped area. Some of the differences I have observed in human behavior in contracepting and noncontracepting, low birth rate and high birth rate populations seem parallel to those I've observed in the rhesus groups. ------------------------------------------------------------------------------ CONTEXTUAL VARIATION IN RECIPROCITY AND COMPLEMENTARITY OF RHESUS FRIENDSHIP: COVARIATION IN MEASURES OF AFFILIATION IN A REPRODUCTIVE AND A NONREPRODUCTIVE GROUP Dennis R. Rasmussen Wisconsin Regional Primate Research Center, University of Wisconsin, and Animal Behavior Research Institute, Madison, Wisconsin 53715 U.S.A. ABSTRACT The subjects of this research were in two groups of 11 rhesus (_Macaca_ _mulatta_) matched by sex, age, and previous housing experience. Mature males in one group were vasectomized so females did not conceive. In this group there were higher rates of sexual behavior because of the females' repeated nonpregnant estrous cycles and the conception and pregnancy of the mature females in the reproductive group. Seven measures of affiliation were found to assess similar aspects of affiliation across social contexts represented by subcategories of individuals within groups and the reproductive and nonreproductive groups. There was, however, considerable variation across interaction categories in both the concordance of variables within groups and interrelationships between variables across groups. Intrasexual interactions were, for example, more discordant in the nonreproductive group. Intrasexual competition in the sexually active nonreproductive group was the apparent immediate cause of the more discordant patterns of intrasexual affiliation. In our interactions, overlap in means of conveying friendship is important: If a person says they like you, nods their head when saying this, and writes expressing friendship, the consistency of these sources of information increase confidence in the friendship. Inconsistency in sources of information may make us less confident of friendship and, perhaps, suspect deception. Among rhesus there is also variation in consistency of affiliative interactions, variation that may convey information on degree of affiliation, relative status of individuals, and that may deceive. INTRODUCTION Affiliation is often defined by elaboration of the variables that are used for its assessment in primatology (O'Keeffe et al., 1983; Baker & Estep, 1985; Ehardt & Bernstein, 1987). The most universally used measures of affiliation are proximity and grooming (Rasmussen, 1984; Byrne et al., 1989). Measures of behavioral patterns associated with proximity (such as approaches, leaves and follows) and grooming presents, presents, and mounts are sometimes used to assess affiliation (Rasmussen, 1984; Chadwick-Jones, 1989). Vocalizations may also been used to assess affiliation (Biben et al., 1986; Masataka & Biben, 1987). Measures used to assess primate affiliation generally have three characteristics: They are associated with either distance reduction or proximity maintenance between individuals, they do not evoke escape responses, and they are not agonistic behavioral patterns. Affiliation is an intervening variable (MacCorquodale & Meehl, 1948; Miller, 1959; Hinde, 1985) since it is a tendency that is measured by many variables fitting the above characteristics. Few studies have focused on the degree of association between measures of affiliation; such studies help determine the utility of an intervening variable (Hinde & Datta, 1981). The ambiguous distinction between affiliative and sexual behavior provides an additional reason for analyses of the associations between measures of affiliation: sexual interactions may fit all characteristics of affiliation. Sexual behavior is functionally defined as behavior that has been associated with conception during the phylogenetic past of an organism (Scott, 1956; Tinbergen, 1965; Rasmussen, 1984). Presents and mounts have received the most theoretical and empirical attention as measures of affiliation perhaps because they do not neatly fit into any single behavioral category. This is particularly true for intrasexual presents and mounts since they are not sexual within a functional definition of sexual behavior. Intrasexual presents and mounts have been interpreted as affiliative (Reinhardt et al., 1986). Presents and mounts have also been interpreted as agonistic since they may be used during submission, appeasement, tension reduction, or the enlistment of the aid of others in aggressive interactions (Chadwick-Jones, 1989). A few studies have reported on the influence of social context on relationships between measures of affiliation. Heterosexual affiliation has, for example, been found to increase among rhesus (_Macaca_ _mulatta_) during breeding seasons (Hill, 1986). In comparisons between matched groups of rhesus and bonnet (_M_. _radiata_) macaques, heterosexual affiliation has been found more frequent in the groups with higher rates of sexual activity (Rasmussen, 1984, in prep.; Rasmussen & Goy, 1988). The age and sex of interacting individuals provide a social context that may influence their affiliative behavior. Male => male* or female => female mounts could have a different degree of association with other affiliative variables than male <=> female mounts. It is also possible that male => female mounts differ in use from female => male mounts. The validity of measures for assessment of affiliation as an intervening variable is therefore analyzed as a function of the age and sex of the individuals involved in the interactions. ------------------------------------------------------------------------------ * <=> symbolizes bidirectional behavior or a measure of the distance between a dyad. When, for example, analyses are focused on grooming of males by females and grooming of females by males this is symbolized as male <=> female grooming. => symbolizes directional behavioral interactions. Male grooms of females are therefore symbolized as male => female grooming. Interactions directed by one individual to another are referred to as directional dyads. Affiliative interactions directed by the oldest male to the oldest female therefore constitute a directional dyad. ------------------------------------------------------------------------------ The influence of social context is further evaluated by comparison of the relationships between the affiliative measures in a reproductive and a nonreproductive group. There were significantly higher rates of sexual behavior in the nonreproductive group (Rasmussen, in prep.; Rasmussen & Goy, 1988). Mature females in that group had repeated nonpregnant estrous cycles and engaged in sexual behavior during each of the cycles (Michael & Zumpe, 1988). Sexually mature females in the reproductive group conceived and were pregnant throughout the duration of observations. They therefore engaged in less sexual behavior (Wilson et al. 1982; Hill, 1986). METHODS Subjects and Housing The nonreproductive group was composed of a 5 year old vasectomized male, a 4 year old vasectomized male, an intact 2 year old male, four 4 year old females, one 3 year old female, and three 2 year old females. The reproductive group was sex and age matched. Reproduction was prevented with vasectomy since it has the minimum direct effects on the hormones and behavior of the sterilized animal (Phoenix, 1973) and it could be used on the fewest subjects. Subjects were the rhesus available who were most closely matched by age, weight and housing history (the amount of time they were housed at the Vilas Park Zoo in Madison, in group cages, as pairs, by themselves, and with their mothers). All females were nulliparous and thus did not vary in parturitional, lactational, or infant rearing experience. The groups were housed in identical indoor pens measuring 6.7 m in length, 2.5 m in width and 2.6 m in height. The pens were separated by a minimum distance of 1.2 m and in a room with two additional identical pens containing breeding rhesus groups. Lights were automatically turned on at 06.00 hours and turned off at 18.00 hours. Two frosted windows next to the pens let in ambient light. Behavioral Sampling The data were collected from January 2, 1987 until the day before the birth of the first infant in the reproductive group, June 1, 1987. I collected the observations for 5 days each week from 15.00 to 18.00 hours. Individual group members were the focus of 14 min sampling sessions. Focal subjects were selected sequentially from a list of all individuals in both groups. Focal sampling (J. Altmann, 1974) was used for the variables requiring constant monitoring of the subject. Concurrent samples (Hausfater, 1974; Chapais, 1986) were collected on all occurrences of variables (Martin & Bateson, 1986) that could be simultaneously observed for all group members. Data were recorded on a Tandy 102 computer. An auditory cue preceded 2 min intervals by 15 sec. to start focus of attention on the variables sampled instantaneously. Data reduction and analysis were conducted with SPSS/PC+ (Norusis, 1988a, 1988b) and UNIX. The analyses are based on 2445 2 min interval samples collected during 14 min sampling sessions. Behavioral Variables: Sampling Method The unit of observation and the method used to sample each variable are summarized in Table 1. ------------------------------------------------------------------------------- Table 1. Variables, Observation Method and Sampling System ------------------------------------------------------------------------------- Variable: Unit of Observation Sampling Method ------------------------------------------------------------------------------- 1. Nearest Neighbor Distance individual-focal instantaneous 2. Close Distance to Nearest individual-focal instantaneous Neighbor 3. Approaches, Leaves & individual-focal frequency Follows (ALF) 4. Grooming all individuals 1/0 5. Grooming Presents individual-focal frequency 6. Presents individual-focal frequency 7. Mounts all individuals frequency ------------------------------------------------------------------------------- Analytic Strategy Several methods are used to describe and analyze the relationships between measures of affiliation and differences in these relationships between the two groups. The methods are first applied to all group members to determine broad patterns. Patterns in affiliative interactions between subpopulations of individuals in each group are then conducted. For example, mature female => mature male interactions are analyzed as a subpopulation of interactions between all group members. As in Fisher's protected t-test, tests of significance were not conducted on subcategories unless the tests conducted on all dyads, and on the immediately higher category of interaction, were significant (Cohen & Cohen, 1983; Rasmussen, 1984). Statistical Control of Days Together before Group Formation Some pairs of individuals spent more time together than others before group formation. Differential amounts of time spent together before observation could alter the relationships between the variables. For example, individuals who spent more time together before observations might engage in less sexual behavior but groom more often (Takahata, 1982a, 1982b). Groups of nonhuman primates cannot yet be as closely matched as, say, groups of inbred rodents. Previous studies in which matched groups are compared have seldom used subjects as closely matched as those in this project, matching made possible by the large population of rhesus maintained by the Wisconsin Regional Primate Center. Previous studies (Boccia et al., 1982; Rasmussen, 1984; Boccia, 1989) have also not attempted the statistical control of differences possible with the methods developed for this purpose. Here influences of days dyads spent together before group formation were statistically controlled by the regression of the affiliative directional dyadic interactions, as assessed by each variable, on this nuisance variable. Transformations were used, when appropriate, to normalize residuals from regression. Linear and quadratic fits to Days Together were tried for every dependent variable. For all dependent variables, except Grooming, the quadratic aspect of Days Together did not appreciably increase R; only linear fits were therefore used. 1/0 Grooming Rate was regressed on both the linear and quadratic aspects of Days Together. The regession of the variables on Days Together were not tested for statistical significance since control of a nuisance variable is not predicated on either the magnitude or significance of the influence (Cohen & Cohen, 1983). All descriptive statistics and analyses are based on the residualized variables. SPEARMAN CORRELATIONS BETWEEN VARIABLES: Spearman rank order correlations (Siegel & Castellan, 1988) were calculated between the variables in each group. These correlations are used solely for description of the way directional dyads are ranked by pairs of affiliative variables; they are not tested for statistical significance. If, for example, monkey "A" Grooming Presents at a high rate to monkey "B" does it also tend to Approach, Leave or Follow monkey "B" at a high rate? Spearman correlations were used so that curvilinear relationships between the variables would not influence the magnitude of their association. There were 21 correlations between variables (the half matrix minus the diagonal). Description of linear and curvilinear fits between variables would be tedious and their complex interpretation would obscure the focus of this paper. The distance of monkey "A" to monkey "B" is necessarily the same as the distance of "B" to "A". There were therefore 55 ([11 x 10]/2) unique nondirectional dyads on which Nearest and Close Neighbor Distance could be calculated in each group. Behavioral variables are directional: Monkey "A" Mounting "B" may have a different social significance than monkey "B" Mounting "A". The behavioral variables were therefore calculated for the 110 (11 x 10) directional dyads in each group. Duplicate values of neighbor distances were matched with directional behavioral interactions so their association could be described. For example, the rate of Grooming of the 4 year old male by the 5 year old male in the nonreproductive group was paired with the same distance value used with the rate of Grooming of the 5 year old male by the 4 year old male. Although Nearest and Close Neighbor Distance are not unidirectional, correlations with these variables are included in analyses of these interactions, such as those directed by females towards males, so that the results are comparable to the other analyses. MATRIX CORRELATIONS: A Pearson correlation was calculated between the Spearman correlation matrices from the groups. This correlation between paired values of correlation coefficients is referred to here as a "matrix correlation". The matrix correlation describes the similarity of the variables' interrelationships in the two groups. Like all correlations (Cohen & Cohen, 1983), matrix correlations are not influenced by linear transformations of the coefficients in either matrix. They therefore assess similarities in relative values of correlation coefficients. The significance of the matrix correlations was determined with a Monte Carlo test based on 10000 permutations of the matrices (Dow et al., 1987). The Association between Measures of Affiliation within each Group: Distances to neighbors decrease with greater affiliation, and all the behavioral measures increase with greater affiliation. If the measures assess affiliation as a unitary intervening variable, then measures of distance to neighbor should be positively correlated; the behavioral measures of affiliation should be positively correlated, and the measures of distance to neighbor and the behavioral measures should be negatively correlated. The signs of the 21 correlations between the measures of affiliation within each group are therefore used as an initial index of whether they tend to assess the same underlying affiliative tendency. The degree of similarity in the way directional dyads were ranked by the affiliative variables is then assessed with the Kendall Coefficient of Concordance, W (Siegel & Castellan, 1988). The coefficient of concordance provides a measure of the consistency with which the variables rank directional dyadic interactions. The coefficient of concordance was calculated by ranking Nearest Neighbor Distance and Close Nearest Neighbor in descending order and the other variables in ascending order. The initial assumptions about the way variables evaluate affiliation are based on their usual interpretation in many studies of nonhuman primates (Rasmussen, 1984; Bernstein & Ehardt, 1986). Each pattern of affiliation is therefore initially interpreted as reciprocal (Hinde, 1987): if, for example, monkey "A" Grooming Presents more to monkey "B", "A" is assumed to more often Groom "B". This might be thought of as a form of a monkey "golden rule". Patterns of behavior in which monkey "A" is the actor and monkey "B" the recipient are positively associated with patterns in which monkey "A" is the recipient and monkey "B" the actor. If Monkey "A" Grooms monkey "B" more, Monkey "A" also Grooming Presents to monkey "B" more. If Monkey "A" Mounts monkey "B" more, Monkey "A" also Presents to monkey "B" more and so on. More complex, and sometimes less nice, relationships are possible and probable (Seyfarth, 1977). These initial interpretations are therefore null hypotheses about possible relationships between measures of affiliation and are referred to as the expected reciprocal direction. MEAN SQUARED CORRELATIONS: The mean strength of agreement between each measure of affiliation and all others is described with the mean of its squared correlations. Correlations between variables opposite to that expected are given a value of 0 when calculating the mean. The mean squared correlation may therefore be interpreted as the mean proportion of affiliative variation shared between dyads ranked by one variable and all others. Differences in mean squared correlations between groups are used to pinpoint the measures of affiliation that are most dissimilar in relationships with others and, therefore most sensitive to the contextual differences between groups. RESULTS The positive and significant matrix correlations for every category of interaction and significant coefficients of concordance for every category of interaction in both groups were striking outcomes of the analyses (Table 2). Since the coefficients of concordance were significant, the variables do tend to measure similar aspects of behavior across the social contexts of the two groups and across interaction categories. This suggests that affiliation is a useful intervening variable and the variables used for its measure in previous studies were correctly chosen. There were positive, strong, and significant matrix correlations for every category of interaction. The ways in which the variables assessed affiliation therefore tended to remain similar in the two groups across categories of interactions. There was, however, variation in the matrix correlations, the number of correlations in the expected reciprocal direction, the coefficients of concordance, and differences between groups. The utility of measures for the assessment of affiliation is thus partially contingent on who is interacting with whom and the group in which the interactions occur. ------------------------------------------------------------------------------ Table 2. Summary of the variables used to describe the interrelationships between the affiliative variables for each analyzed dyadic composition. ------------------------------------------------------------------------------ Category of N Matrix Concordance r/N >1 "Golden Rule" Interactions r RG NG RG NG ------------------------------------------------------------------------------ all 110 +.95* +.55* +.50* .86 21 21 all sexually mature 42 +.92* +.55* +.45* .86 19 21 all male => male 6 +.65* +.84* +.51* .86 17 21 all female => female 56 +.90* +.49* +.48* .43 19 21 mature female => female 20 +.75* +.55* +.36* .86 16 21 male <=> female 48 +.97* +.55* +.53* .67 21 21 male => female 24 +.93* +.55* +.56* .29 21 21 mature male => female 10 +.78* +.49* +.71* .00 21 18 female => male 24 +.97* +.58* +.54* .57 20 21 mature female => male 10 +.93* +.60* +.67* .33 21 21 ------------------------------------------------------------------------------ 1 r/N > Proportion mean squared correlations greater in the Reproductive Group * Statistically significant, P<.05 ------------------------------------------------------------------------------ Matrix Correlations: Interrelationships between Variables The matrix correlations were less than +.90 (Table 2) for three interaction categories; contextual differences in the two groups therefore had the greatest influence on the relationships between the affiliative variables for these categories. The smallest matrix correlation was for male => male interactions, the next smallest correlation for mature female => female interactions, and the third smallest correlation for mature male => female interactions. The contextual differences between the two groups therefore had the greatest influence on the variables' interrelationships for isosexual interactions and on interactions directed by mature males to females. Greater intrasexual competition in the more sexually active nonreproductive group seem the likely cause of the decreased similarities between the correlation matrices composed of male => male and mature female => mature female interactions. The variables in the nonreproductive group appeared to be used more frequently in agonistic contexts and to convey information on agonisitc rank. Intrasexual Presents were, for example, more frequently used for appeasement and less often for affiliation. The use of Presents for appeasement resulted in a negative correlation between male => male Grooming Presents and Presents in the nonreproductive group. Males of higher rank "requested" Grooming with Grooming Presents and were Presented to by the males from whom they "requested" Grooming. Information on relative status was therefore conveyed by the complementary direction of affiliative interactions. In contrast, Grooming Presents and Presents were strongly and positively correlated in the reproductive group: Intrasexual affiliation was therefore more reciprocal and less related to status. Reproductive males were, for example, more likely to Groom a male to whom they Grooming Presented. A similar difference, but of lower magnitude, existed between groups for mature female => female interactions. Mature male => female interactions had the third lowest matrix correlation. This was the result of the stronger concordance of affiliative variables in the nonreproductive group. The stronger concordance was paralleled with a stronger mean squared correlation for every variable in the nonreproductive group. The stronger concordance and mean squared correlations reflect the much greater reciprocity of mature male => female interactions in the nonreproductive group. Nonreproductive adult males had, for example, a strong tendency to Groom most frequently the adult females to whom they most frequently Grooming Presented whereas there was a faint tendency in the opposite direction in the reproductive group. The greater reciprocity of mature male => female interactions in the nonreproductive group may have been the result of the greater synchronization of affiliative interactions occurring between sexually interacting pairs and the more solicitous and tolerant behavior (Carpenter, 1942) of the males in those pairs. Correlations with Grooming Presents differed most between groups in the analyses conducted on the three interaction categories with the lowest matrix correlations. The social use of Grooming Presents is therefore particularly strongly influenced by contextual differences between groups. In the nonreproductive group, intrasexual Grooming Presents were directed to those with whom appeasement was not necessary, to those of lower agonistic rank. Intrasexual grooming Presents were more reciprocal in the reproductive group. Heterosexual Grooming between sexually active pairs was more reciprocal in the nonreproductive group. Grooming Presents were therefore strongly correlated with Grooming; these variables were not associated in the reproductive and less sexually active group. Depending on social context, Grooming Presents may therefore be used in either complementary or reciprocal affiliative interactions. Coefficients of Concordance There was stronger concordance in the way the variables ranked directional dyadic interactions in the reproductive group for 7 of the 10 interaction categories. Male => male interactions had the greatest difference in coefficients of concordance, mature male => female interactions had the second greatest, and the third greatest difference was in mature female => female interactions. The three interaction categories with the greatest difference in concordance were also those with smallest matrix correlations. Two of the three greatest differences in the coefficient of concordance arose for intrasexual interactions. Intrasexual competition associated with higher rates of sexual behavior is, again, the probable cause of the lower concordance between affiliative variables in the nonreproductive group. Decreased reciprocity of intrasexual interactions in the nonreproductive group is sometimes a form of intrasexual competition: one individual in the dyad may receive decreased social resources compared to the other. If, for example, a nonreproductive male more frequently Presented for Grooming to another male he was less likely to Groom that male. Greater discordance between measures of affiliation suggests less consistent and more conflicting social signals, an inconsistency that may grade into deception. In the nonreproductive group, for example, a strong tendency for female "A" to Groom "B" had close to no covariation with rate at which female "A" Grooming Presented to "B". Analyses of other patterns of behavior, such as aggression, would permit further detection of intrasexual deception in the nonreproductive group. For example, ALF rate, Grooming, and agonistic behavior appeared to be more positively associated in the nonreproductive group, a deceptive blend of affiliative and agonistic interactions: Instead of "An I'll scratch your back if you will scratch mine" pattern of interaction; those in the nonreproductive group might more closely approximate a pattern summed up as "I'll let you scratch my back and then bite yours". Sequential data analyses would help differentiate this possibility from conciliation and reconciliation (de Waal & Yoshihara, 1983). It is, of course, not impossible that conciliation and reconciliation could deceptively mask agonistic behavioral patterns. The severity of wounds could far exceed the positive benefits of conciliation and reconciliation; the total valence of interactions might be overwhelmingly negative. The second greatest difference in the coefficients of concordance between groups was for mature male => female interactions. Exactly opposite to the intrasexual interactions, there was a much stronger coefficient of concordance in the nonreproductive group. The greater concordance was paralleled by larger mean squared correlations for every variable in the nonreproductive group. As with the low matrix correlation, the greater reciprocity of mature male => female interactions appeared to cause the difference in the coefficients of concordance between the two groups. Number of Correlations in the Expected Reciprocal Direction The number of correlations in the expected reciprocal direction differed across groups and across interaction categories (Table 2). In the reproductive group all but one interaction category had all 21 correlations in the expected reciprocal direction. Only half of the interaction categories had all correlations in this direction in the nonreproductive group. As a whole, the monkey "Golden Rule" was followed in more interactions in the reproductive group than in the nonreproductive group: if, for example, monkey "A" Groomed "B" at a high rate, monkey "A" also tended to Grooming Present to "B" at a high rate. This difference between groups was absolute for intrasexual interactions. The only deviation from the trend was for mature male => female interactions; for these, all correlations were in the expected reciprocal direction in the nonreproductive group whereas 18 of 21 were in this direction in the reproductive group. Proportion of Mean Squared Correlations Greater in the Reproductive Group The three interaction categories with the lowest proportion of mean squared correlations greater in the reproductive group were all heterosexual: mature male => female, male => female, and mature female => male. The greater synchronization of affiliative interactions between sexually interacting pairs appears to be responsible for these results. One of these three interaction categories, mature male => female interactions, was found most different from the others in matrix correlations, number of correlations in the expected reciprocal direction and differences between coefficients of concordance. By all measures of relationships between the variables, mature male => female interactions were markedly influenced by contextual differences between groups: these interactions were more reciprocal in the nonreproductive and more sexually active group. CONCLUSIONS The differential concordance of the measures of affiliation suggest that partially redundant sources of information are used by monkeys to signal their affiliative tendencies towards each other and that discordance of affiliative interactions might be used to deceive. In human exchange we tend to feel more confident say, that another person means yes when they nod yes, say yes and write yes. When a person nods yes, says yes and writes no or, vice versa, then meaning becomes more difficult to interpret and we may feel deception of ourselves, or others, is possible if not probable. Analogous concordance and discordance of affiliative interactions occur in rhesus. These analyses have only concentrated on the agreement between 7 measures of affiliation. Further analyses are necessary to determine how these measures are associated with unambiguously sexual and agonistic interactions. Analyses of the variability in degree reciprocity between dyads for each variable would provide further insight into the ways patterns of affiliation are used. Such analyses will be necessary for a more thorough understanding of the subtleties in use of affiliative interactions between rhesus macaques. Further analyses are also necessary on the use of affiliative interactions, such as Grooming Presents, in status interactions. When affiliative interactions are used in status interactions they may simultaneously convey both agonistic and affiliative information. Analogously, bowing between people, and the depth of the bows, may simultaneously signal affiliation and differences in status. ACKNOWLEDGEMENT Drs. R. Goy, F. De Waal and V. Reinhardt made useful suggestions on aspects of the theory and analyses. Dr. V. Reinhardt performed the vasectomizations and helped select the animals for the study. Dr. S. Sholl wrote the communication program, COMX, used to transfer data between computers. Paul DuBois programmed my data collection method for use on Tandy 102 lap top computers. This research was supported by NIMH National Research Service Award 1 F32 MH09419-01 RERA, NIH Grant RR00167 and NSF Grant 880414. REFERENCES [available from author; deleted from email version -- ed.] ------------------------------ PSYCOLOQUY is sponsored by the Science Directorate of the American Psychological Association (202) 955-7653 Co-Editors: (scientific discussion) (professional/clinical discussion) Stevan Harnad Perry London, Dean, Cary Cherniss (Assoc Ed.) Psychology Department Graduate School of Applied Graduate School of Applied Princeton University and Professional Psychology and Professional Psychology Rutgers University Rutgers University Assistant Editors: Malcolm Bauer John Pizutelli Psychology Department Psychology Department Princeton University Rutgers University End of PSYCOLOQUY Digest ******************************