Chapter 7 of Interpersonal Perception: The Foundation of Social Relationships. See especially pages 178-183.
The degree to which a person sees him or herself as do others. Using the Social Relations Model, self-other agreement is assessed by the correlation between a person's self-rating and that person's target effect. Self-other agreement requires that there be target variance in the trait rating. If there were no target variance, then self-other agreement cannot be measured. Note too it defined as the correlation with the target effect (self with many) and not the judgment of a single perceiver (self with one). Using Laing notation, it is symbolized as A(B) = B(B).
There has been considerable interest in self–other agreement, especially in accuracy research. Traditionally, self-perceptions have been used as the measure of the truth in accuracy research, and so self–other agreement has been a traditional way to determine whether personality ratings are accurate. Perhaps the best-known proponent of this point of view is David Funder in his 1995 Realistic Accuracy Model.
The simplest explanation of self–other agreement is that both self and other observe the target’s behavior, and that is why they agree with each other. In such a model, the target’s behavior is viewed as the explanatory or “confounding” variable. Daryl Bem in his 1972 article “Self-Perception Theory” argued that self-perceptions
arose from self-observation.
Presumably, the level of self–other agreement would depend on the extent to which the behaviors being judged were either internal or external. The self has special access to inner experiences and thoughts to which others do not have access. For instance, the self has direct access to internal feelings of guilt and anxiety, whereas others may have a more difficult time knowing such feelings. However, for highly external or observable traits, such as “sociable” and “friendly,” presumably both the self and other would have access.
Communication and social influence also play a role in self–other agreement. As has been argued by William Swann in his self-verification theory in 1983, people very actively try to get others to see them as they see themselves. However, influence can also run the other way: Others attempt to influence a person to view him- or herself the same way that they do, something called behavioral confirmation. The idea that others create self-perceptions is a fundamental part of the theory called symbolic interactionism, which has a long history going all the way back to the 19th century and George Herbert Mead (1934). The competition between self and other is the focus of the 1984 article by William Swann and Robin Ely.
The earlier of the two papers is a 1993 paper by Oliver John and Richard Robins. In their first study, they had 50 college students who were judged by four others in the same dormitory or off-campus housing complex. Participants were relatively familiar with each other (3.8 on a 1–5 scale). Ratings were made on 76 unipolar traits that were Big Five markers. Their second study involved a community sample, with 218 participants ranging in age from 30 to 90 years who were judged by two to four peers who had known the targets for an average of 18 years. Ratings were made on 80 bipolar traits. For their first study, consensus averaged to .25, and self–other agreement was .19. The difference between the two is statistically significant and held across all of the Big Five. For the second study, consensus averaged to .22, and self–other agreement was .20. Although the difference between consensus and self–other agreement was smaller in this second study, it is nonetheless statistically significant. Thus the two studies point to the conclusion of self–other agreement being about .20 and less than consensus.
The second major survey is the 2010 meta-analysis that Tessa West and I conducted. There were 24 studies with a total of 118 variables and 2,992 participants. Each study was a round-robin study in which each person judged other members of their group. The level of familiarity of the participants was rather low. Our meta-analysis found that the average level of self–other agreement was .21, whereas consensus was .27. These results are consistent with the John and Robins results.
On the basis of these studies, we find that the average self-other correlation is about 82 percent of the consensus correlation. Thus if consensus is abut .40 for long-term acquaintance, self-other agreement would be .33. However, as reported on the Consensus page, consensus is lower for the people judging the target, which results in consensus correlation of .29 across contexts.
Three cross-sectional studies examined the effect of acquaintance on self–other agreement. The first, which is reviewed in Chapter 4, is by Jeremy Biesanz and his colleagues in 2007. They found small but statistically significant increases in self–other agreement with increased acquaintance, approximately .02 a year. The second study was conducted by Brian Connelly and Deniz Ones in 2010. They found substantially more self–other agreement in well-acquainted dyads (r = .46) than for strangers and casual acquaintances (r = .38). The third study, by Jüri Allik and colleagues in 2016, found a weak nonsignificant but positive correlation between self– other agreement and acquaintance in two large cross-sectional studies. Thus these cross-sectional studies support the view that increasing acquaintance is associated with greater self–other agreement, although the relationship is not very large. However, West and I, in our 2010 meta-analysis, found that acquaintance or familiarity actually was negatively associated with both self–other agreement and consensus. We were honestly quite dubious about that conclusion because the studies did not vary much in terms of acquaintance.
The one review of longitudinal studies is in the 1994 Interpersonal Perception book (see pp. 196–198), which finds that self–other agreement increases with greater acquaintance. Additionally, in 1995,
Del Paulhus and Shawn Reynolds found a statistically significant increase in self–other agreement in their longitudinal study. In 1998, Melinda Blackman and David Funder found an increase of idiographic self–other agreement, at least of visible traits. However, in 1997, Bernadette Park and her colleagues found no increase over time in self–other agreement.
Despite some exceptions, the longitudinal and cross-sectional results converge in showing that increased acquaintance leads to greater self–other agreement. This conclusion is in agreement with that of Mitja Back and Simine Vazire in 2012, who conclude that “self–other agreement . . . increases with level of acquaintance . . . , a well established finding” (p. 139).
Visibility, also called observability and externality, is a strong positive predictor of consensus. John and Robins, as well as West and I, found that visibility correlated positively with self– other agreement. Again there is an exception: Jennifer McDonald and Tara Letzring in 2016 did not find any relationship between observability and self–other agreement. Nonetheless, the preponderance of the evidence is that observability is related to self–other agreement, which explains why the Big Five factor of Extraversion has highest level of self–other agreement. To the extent to which the trait is internal and therefore affords the self privileged access to that information, there is lower self–other agreement.
In 2010, Jüri Allik and colleagues made an important point that often traits differ in how much variance there is in both self-judgments and impressions. It is well known that correlations are weakened by having what is called a restriction in range, and consequently traits with more variance should have higher self–other correlations. Allik and colleagues show that much of the differences in self–other agreement by trait can be explained by differences in variability. The point, then, is that visibility, for example, creates more self–other agreement because targets differ more from one another on traits that are high on observability. However, likely more variance is due to greater observability than vice versa.
Positive and negative traits are high on evaluativeness, and neutral ones are low. In the two aforementioned surveys, the effect of evaluativeness on self–other agreement correlations was investigated. John and Robins found strong support for the effect that greater evaluativeness of the trait being judged led to lower self–other agreement. Additionally, they noted that the negative effect of evaluativeness was stronger for self–other agreement than for consensus. West and I failed to confirm this result. Likely, there is a greater negative effect of evaluativeness on self–other agreement than consensus, although it would be reassuring to see the result replicated.
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