Social Psychology: WhoWe Are andWhatWe Dodtg/TESSER_BAU.pdfpages in the two-volume GFLHandbook5 and 12 or morepagesinthesingle-volumeHKHandbook.These cutoffs are arbitrary, but they

Personality and Social Psychology Review2002, Vol. 6, No. 1, 72-85

Copyright © 2002 byLawrence Erlbaum Associates, Inc.

Social Psychology: Who We Are and What We Do

Abraham Tesser and Jinn Jopp BauInstitute for Behavioral Research

University of Georgia

The author index of the Handbook of Social Psychology (Gilbert, Fiske & Lindzey,1998) and of Social Psychology: Handbook of Basic Processes (Higgins & Krug-lanski, 1996) served as the basis for identifying and describing some of the peopleconstructing social psychology in the 1990s. Over 10,000 names are mentioned, butrelativelyfew are mentioned several times. The 106 contributors who were mentionedmostfrequently are identified and described. They are mostly men about 20 years be-yond the PhD. The select set of institutions at which they work andfrom which theyobtained their degrees are also identified. Similarities among contributors were cal-culated on the basis of the proximity of their mentions in the handbooks. An analysisof those similarities yielded eight "contributor factors": social cognition, attitudes,motivated attribution, self, interpersonal influence, intergroup relations and stereo-

types, culture and evolution, and interpersonal relationships.

I have been fascinated with the subject matter andtheoretical thinking in social and personality psychol-ogy since I began graduate school. Now, on the thresh-old of a new millennium, it is the field of social psy-chology as it currently stands that I attempt todescribe-because I am a psychologist, I focus on thepeople that do social psychology. Who are they?Where are they now and where do they come from?What are the topics that drive their inquiry, explora-tion, and analysis?A current description of the field should be com-

prehensive, and there should be some defensible cri-terion for including this and excluding that. A reflexfor many of us is to take a data-driven approach-thatis, to focus on something that can be counted and an-alyzed. In this instance, a data-driven approach maybe no more valid than a qualitative narrative. How-ever, it has the advantage of making many of us, my-self included, more comfortable.

Where might we find something to count that wouldgive a good description of the field? One could collectnew data, perhaps a survey of the membership of the So-ciety of Personality and Social Psychology. Respon-dents could be asked to indicate theirown research inter-ests, the areas they consider to be most important, and

the people who they believe currently have the most in-fluence in the field. The result of such a survey would beinstructive. However, such an approach is expensive,subject to distortion by subject loss, and likely to reflectmostly the current top-of-the-head thinking of the re-spondent rather than a more thoughtful analysis.

Another reasonable solution would be to sample thecurrently available textbooks. The table of contents formany texts, however, are formulaic and may unduly re-flect "tradition" in their coverage; in many instancesthe coverage is more superficial than might be the casein more sophisticated sources. Perhaps the ideal ap-proach would be to sample the authors and content ofour best journals. This would be timely, and the contentwould have the appropriate depth. Regrettably, how-ever, such an approach would have required more re-sources than I had for this particular project. I settledon a compromise somewhere between the textbook ap-proach and the journal approach. Much of what fol-lows is based on analysis of the author index of two re-cently published handbooks of social psychology:1Handbook of Social Psychology2 (Gilbert et al., 1998)and Social Psychology: Handbook ofBasic Principles(Higgins & Kruglanski, 1996).

The fourth edition of the Handbook of Social Psy-chology (GFL Handbook; Gilbert et al., 1998) was pub-

This article is based on Abraham Tesser's presidential address tothe Society for Personality and Social Psychology at the AmericanPsychological Association, August 2000. In keeping with that ad-dress, most of the first-person references are in the singular. JinnJopp Bau was responsible for the substantial data processing, partic-ularly as reflected in the section on Similarities Among Contributors.

Requests for reprints should be sent to Abraham Tesser, Institutefor Behavioral Research, Barrow Hall, University of Georgia, Ath-ens, GA 30602. E-mail: [email protected]

1Regrettably, the most recent handbook of social psychology,The Blackwell Handbook of Social Psychology (Hewstone &Brewer, 2001) lacks a name index in one of its four volumes (Tesser& Schwarz, 2001), and the analyses reported here could not be car-ried out on these volumes.

21 am grateful to McGraw-Hill Publishers for providing an elec-tronic version of these two indexes. Thanks also to Dan Gilbert forfacilitating this acquisition.

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SOCIAL PSYCHOLOGISTS

lished in 1998 by McGraw-Hill. It was edited by DanielT. Gilbert, Susan T. Fiske, and Gardner Lindzey andconsists of 2 volumes and 37 chapters. The GFL Hand-book, starting with the first edition in 1935, has been astandard reference work in social psychology. It is in-tended to cover the breadth of the field. I believe that theMcGraw-Hill volumes are highly successful in achiev-ing their goals. The current edition, was, at the time ofthis writing, the most timely and comprehensive singlecollection for serious scholarship in social psychologythat was available (see footnote 1). Moreover, the au-thors are recognized experts in each of their fields.

Any one work is likely to reflect, at least in part, idio-syncrasies associated with the editors, specific authors,and publishers. To derive a more general picture it isprobably prudent to have at least one other comprehen-sive description of the field from which to draw. TheHiggins and Kruglanski (1996) handbook, Social Psy-chology: Handbook of Basic Principles (HK Hand-book) published by Guilford Press, appeared in 1996.This single-volume handbook contains 28 chapters andalso attempts a comprehensive view ofthe field of socialpsychology but from a different perspective. Instead ofan organization around areas of social psychology, thisvolume is organized around basic principals and pro-cesses. According to the authors' preface, other works ofthis type focused on social psychological phenomenaand social issues. The HK Handbook "complementsthese by searching for specific principles underlyingmany different social-psychological phenomena ratherthan focusing on the phenomena themselves" (Higgins& Kruglanski, 1996, p. vii). Like the GFL Handbook,the HK Handbook is a well-respected source work. It isedited and written by some of the field's best-known ex-perts. Because the handbooks differ with respect to or-ganization, editors, authors (to some extent), and pub-lisher, what is common to both volumes should give us amore general view of social psychology in the closingdecade of the second millennium than either volumeconsidered by itself.

Who Are We?

The first set of questions that I address concern thepeople who are currently influential in the constructionof our discipline. It turns out that there are a lot morepeople contributing to the discipline then I would haveguessed. In the GFL Handbook there are over 10,000persons (10,020 to be exact) named in the index as be-ing cited in the text3 at least once. However, the number

3These counts include mentions in the narrative of the chaptersonly and not the specific bibliographic information to which themention refers. Thus, a single bibliographic entry might be men-tioned multiple times in the same chapter and the author would getcredit for those multiple entries. I believe this approach partially sep-arates the number of publications from the impact of the work.

of contributors falls quickly as we raise the number ofmentions. (Note that I use the word mentions as short-hand for the number of pages on which a person is citedat least once.) Thus, although there are almost 6,000contributors cited on only one page of the text (5,959 tobe exact), there are fewer than 1,800 (1,760 exactly)mentioned on two pages and substantially less thanhalf that number cited on three different pages. Indeed,the 90th percentile for mentions is somewhere betweenonly four and five mentions over all 37 chapters of thetwo-volume set.

This dramatic falloff in citations is nicely illustratedin Figure 1, in which the number of investigators isplotted against the number of text pages on which theywere cited in the GFL Handbook. In approximate num-bers, 10,000 were mentioned on at least one page,4,000 were mentioned on two or more pages, 2,000 onthree or more pages, and so on. So, there are a lot of us.However, the number of us whose contributions arebroad enough or important enough to be mentioned inmultiple contexts quickly drops off.4Who are the people that are making contributions

important enough to be mentioned in multiple con-texts? To answer this question, we focused on thosecontributors whose work is mentioned on 20 or morepages in the two-volume GFL Handbook5 and 12 ormore pages in the single-volume HK Handbook. Thesecutoffs are arbitrary, but they helped us develop aworkable sample (n = 154 in the GFL Handbook and n= 194 in the HK Handbook). We then compared thenames on each list and generated a list of all the peoplewho are mentioned on both lists.

Are the same top people identified in both volumes?The answer is yes, for the most part. Almost 70% (n =106) of the 154 persons identified as being cited mostfrequently on the GFL Handbook list are also amongthe most cited in the HK Handbook.6 The agreementgoes beyond simply identifying the same people. Evenwithin this highly restricted sample (e.g., 106 out ofmore than 10,000 in the GFL Handbook), there is goodagreement as to the rank ordering. The correlation be-tween number of mentions in GFL and HK is .63.

Table 1 presents the names of the 25 most fre-quently mentioned contributors (FMCs) across both

4There is a similar trend in the HK Handbook. However, becausewe did not have the index in electronic form, we did not attempt toprepare a detailed plot.

5Note that in the original index of the GFL Handbook, some ref-erences to Brown, R. are actually references to Brown, R. J.; some ofthe references to Snyder, M. L. are actually references to M. Snyder.The table provides the corrected counts for Brown, R. J. and Snyder,M. The references to Hatfield, E., Walster, E., and Walster, E. H.were combined into the entry Walster-Hatfield, E. H.

6Note that 106 is only 55% of the 194 identified in the HK Hand-book. However, because the lists are of different length, even if everyperson on the shorter list were on the longer list the overlap would beonly 79%. Correcting for this ceiling by dividing 55% by 79% yieldsthe same overlap, 70%, reported in the text.



TESSER & BAU

12000

6000 -

4000

2000

0

1 11 21 31 41 61 61 71 81 91 101 111 121

Number of Mentions

Figure 1. Frequency of citations against number of investigators. Each data point represents the number of contributors (investigators)who were mentioned at least some number of times. For example, in approximate numbers, 10,000 were mentioned on at least one page,

4,000 were mentioned on two or more pages, 2,000 on three or more pages, and so on.

handbooks. Because the handbooks differ in number ofpages, chapters, and volumes, the mean and standarddeviation in mention frequency should also differ.Therefore, Table 1 presents the raw number of men-tions in the handbooks (N in the GFL, N in the HK),

Table 1. Twenty-Five Most Frequently MentionedContributors

GFL HKHandbook Handbook

Contributors M N(z) N(z) N N(z) N

Higgins, E. T. 3.33 1.52 75 5.13 141Fiske, S. T. 3.30 4.10 130 2.50 85Bargh, J. A. 2.79 1.85 82 3.72 111Chaiken, S. 2.34 1.85 82 2.83 92Kelley, H. H. 2.13 1.85 82 2.40 83Eagly, A. H. 1.94 2.32 92 1.56 65Taylor, S. E. 1.89 1.85 82 1.93 73Petty, R. E. 1.77 1.94 84 1.60 66Jones, E. E. 1.58 2.79 102 0.38 40Cacioppo, J. T. 1.56 1.34 71 1.79 70Fazio, R. H. 1.02 1.19 68 0.85 50Nisbett, R. E. 0.95 1.66 78 0.24 37Gilbert,D. T. 0.88 1.38 72 0.38 40Schwarz, N. 0.84 0.12 45 1.56 65Brewer, M. B. 0.83 1.76 80 -0.09 30Markus, H. R. 0.81 1.19 68 0.43 41Ross, L. 0.74 0.91 62 0.57 44Festinger, L. 0.74 1.05 65 0.43 41Zajonc, R. B. 0.69 1.29 70 0.10 34Zanna, M. P. 0.65 1.10 66 0.19 36Kruglanski, A. W. 0.63 -0.54 31 1.79 70Snyder, M. 0.51 0.91 62 0.10 34Berscheid, E. 0.51 1.05 65 -0.04 31Smith, E. R. 0.48 0.77 59 0.19 36Kahneman, D. 0.39 0.35 50 0.43 41

Note: GFL = Gilbert, Fiske, and Lindzey (1998); HK = Higgins andKruglanski (1996).

and the standardized number of mentions (N(z)in theGFL, N(z) in the HK). The standardized number ofmentions is the z score derived separately for eachhandbook. The final rank order was based on the meanz score obtained by averaging over the GFL and the HKz scores. (The reliability of this combined ranking,based on the Spearman-Brown formula, is .77.) Thetop-20 list holds few surprises. It includes Tory Hig-gins, Susan Fiske, John Bargh, Shelly Chaiken, HalKelley, Alice Eagly, Shelley Taylor, Rich Petty, NedJones, John Cacioppo, and other very well-known gi-ants in the field.

Earlier I mentioned the possibility of doing the kindof analyses presented here using textbooks or journalsas the source of information. Gordon and Vicari (1992)examined such sources in social psychology for the1980s. In one of their analyses, they rank ordered the104 most frequently cited contributors across eightleading textbooks of the period 1987 to 1990. In an-

other, they rank ordered the top 100 contributors (interms of authorship, weighted for order of authorshipin multiple author pieces) across three of our mostprestigious journals for the period 1980 to 1989: Jour-nal of Personality and Social Psychology, Journal ofExperimental Social Psychology, and Personality andSocial Psychology Bulletin.A comparison of the present FMCs with the lists

published by Gordon and Vicari (1992) may be of in-terest. An overlap between this list and their lists pro-

vides further validity for our data. An overlap impliesthat there is at least some temporal stability in the lead-ers of the field. It also goes beyond the overlap betweenthe GFL and HK Handbooks noted earlier. The earlieranalysis implies some generality across handbooks.An overlap between our data and the Gordon and

74

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Vicari data would imply that this list is not due tosomething special about handbooks but that they re-flect the field more generally.

Analyses reveal both temporal stability in the listand generality across sources of data. The overlapamong the present FMCs and the most frequently text-book cited authors for the late 1980s is over 50%: 53 ofthe 104 contributors identified as most frequently citedin textbooks are also among our FMCs. Further, theFMCs identified by the earlier textbooks are higher onthe FMC list (M = .29) than the FMCs not so identified(M = -.29). There is also some overlap between ourFMCs and the list of most frequent contributors to thethree major journals in the 1980s. A third of the 100most frequent contributors in the 1 980s is on our list ofFMCs. Also, FMCs identified as being a heavy con-tributor to the journals in the 1980s have higher stan-dard scores (M = .31) than FMCs that are not so identi-fied (M = -.14). It is interesting to note that ourhandbook data are more closely related to the text-books citations list than it is to publication of journalarticles list. Interpreting such a difference is very diffi-cult. There are differences in time of publication, in-tended audience, emphasis on history, and so forth, aswell as source. However, it is tempting to speculate thatgatekeepers of organized representations of the field-that is, handbook and textbook writers-may be pay-ing more attention to and agreeing on the "importance"or interest value of primary publications rather than thesimple presence (frequency) of publications.

As a tribute to what all of these FMCs have done forthe field, the complete list of all 106 names is presentedin Table 2. They are in alphabetical order so you caneasily see if the person who inspired you most is on thelist-or, perhaps more likely, so you can see if yourown name, your major professor's name, or your grad-uate school rival's name is on the list.

Self-Serving Bias? An Aside

You will notice that a number of people well placedon the list are also GFL or HK Handbook editors andchapter authors. The frequent appearance of thesenames may be due to bias. For example, it could be dueto an author's greater familiarity with his or her ownwork, or it could be a simple self-serving bias (i.e., wemention our own work because we are convinced of itsimportance). On the other hand, clearly the editorswould invite the most accomplished from among us towrite these chapters. Moreover, the authors' own workwould fall most squarely in the area that they were re-viewing. Before engaging any of these explanations,however, it would be useful to first see if authors wereactually mentioned "too frequently."

If, overall, the authors ofone handbook are samplingthe same field as the authors ofthe other handbook, then

Table 2. All Frequently Mentioned Contributors

GFL HKHandbook Handbook

Contributors

Abelson, R. P.Ajzen, I.Allport, G. W.Asch, S. E.Banaji, M. R.Bandura, A.Bargh, J. A.Baumeister, R. F.Bern, D. J.Berscheid, E.Bond, M. H.Brehm, J. W.Brewer, M. B.Brown, J. D.Brown, R. J.Bruner, J. S.Buss, D. M.Cacioppo, J. T.Cantor, N. E.Carlston, D. E.Carver, C. S.Chaiken, S.Cialdini, R. B.Clark, M. S.Cooper, J.Crocker, J.Darley, J. M.Davis, K. E.Deaux, K.Deutsch, M.Devine, P. G.Eagly, A. H.Ekman, P.Fazio, R. H.Festinger, L.Fishbein, M.Fiske, S. T.Gilbert, D. T.Greenberg, J.Greenwald, A. G.Hamilton, D. L.Hastie, R.Heider, F.Higgins, E. T.Hilton, J. L.Hixon, J. G.Hogg, M. A.James, W.Janis, I.Jones, E. E.Kahneman, D.Kelley, H. H.Kenny, D. A.Kitayama, S.Kruglanski, A. W.Kunda, Z.Levine, J. M.Lewin, K.Mackie, D. M.Markus, H. R.

MN(z)

-0.13-0.39-0.22-0.36-0.72-0.532.790.36

-0.720.51

-0.97-1.000.83

-0.81-0.110.04

-0.151.56

-0.64-0.53-0.342.34

-0.22-0.81-0.60-0.22-0.29-0.88-0.62-0.290.131.94

-0.621.020.74

-0.573.300.88

-0.53-0.50-0.50-0.22-0.273.33

-0.76-0.90-0.41-0.67-0.861.580.392.13

-0.150.040.63

-0.64-0.32-0.10-0.150.81

N(z)

0.16-0.590.070.12

-0.49-0.731.850.91

-0.541.05

-1.06-1.061.76

-0.960.54

-0.450.121.34

-0.96-0.77-0.821.850.35

-1.01-0.870.12

-0.26-0.96-0.31-0.450.302.32

-0.401.191.05

-0.734.101.38

-0.68-0.21-0.68-0.31-0.211.52

-1.06-0.87-0.68-1.06-0.962.790.351.850.400.49

-0.54-1.06-0.210.02

-0.211.19

N N(z) N

46 -0.4230 -0.1944 -0.5145 -0.8432 -0.9427 -0.3382 3.7262 -0.1931 -0.8965 -0.0420 -0.8920 -0.9480 -0.0922 -0.6654 -0.7533 0.5245 -0.4271 1.7922 -0.3326 -0.2825 0.1482 2.8350 -0.8021 -0.6124 -0.3345 -0.5637 -0.3322 -0.8036 -0.9433 -0.1449 -0.0492 1.5634 -0.8468 0.8565 0.4327 -0.42130 2.5072 0.3828 -0.3738 -0.8028 -0.3336 -0.1438 -0.3375 5.1320 -0.4724 -0.9428 -0.1420 -0.2822 -0.75102 0.3850 0.4382 2.4051 -0.7053 -0.4231 1.7920 -0.2338 -0.4243 -0.2338 -0.0968 0.43

232821141225

11128133113123018164323702526359215192520251512293165145041238540241525292514122122926164041831723702723273041

(continued)



TESSER & BAU

Table 2. (Continued)

Contributors

Martin, L. L.McGuire, W. J.Messick, D. M.Miller, D. T.Mills, J.Mischel, W.Moreland, R. L.Nisbett, R. E.Petty, R. E.Pittman, T. S.Pratto, F.Pruitt, D. G.Pyszczynski, T. A.Reis, H. T.Rholes, W. S.Ross, L.Ross, M.Ruble, D. N.Schachter, S.Scheier, M. F.Schwarz, N.Sherman, S. J.Singer, J. E.Smith, E. R.Snyder, MSrull, T. K.Stangor, C.Steele, C. M.Strack, F.Swann, W. B., Jr.Tajfel, H.Taylor, S. E.Tesser, A.Tetlock, P. E.Thibaut, J. W.Triandis, H. C.Turner, J. C.Tversky, A.Wegener, D. T.Wegner, D. M.Wicklund, R. A.Wilson, T. D.Wood, W.Wyer, R. S., Jr.Zajonc, R. B.Zanna, M. P.

MN(z)

-0.10-0.46-0.79-0.06-0.97-0.22-0.670.951.77

-0.65-0.95-0.41-0.76-0.39-0.550.74

-0.43-0.17-0.15-0.550.84

-0.57-0.790.480.51

-0.06-0.62-0.43-0.24-0.27_0.181.890.13

-0.060.08

-0.67-0.010.32

-0.270.15

-0.95-0.62-0.69-0.100.690.65

GFLHandbook

N(z) N

-1.01 21-0.31 36-1.06 20-0.45 33-1.06 20-0.77 26-0.54 311.66 781.94 84

-0.40 34-1.06 20-0.45 33-1.06 20-0.26 37-1.06 200.91 62

-0.73 27-0.21 380.26 48

-0.96 220.12 45

-0.96 22-0.96 220.77 590.91 62

-0.68 28-0.82 250.07 44

-0.92 23-0.31 36-0.02 421.85 820.12 450.26 48

-0.16 39-0.40 34-0.16 390.40 51

-0.16 390.30 49

-0.96 22-0.31 36-0.73 27-0.12 401.29 701.10 66

HKHandbook

N(z) N

0.80 49-0.61 19-0.51 210.33 39

-0.89 130.33 39

-0.80 150.24 371.60 66

-0.89 13-0.84 14-0.37 24-0.47 22-0.51 21-0.04 310.57 44

-0.14 29-0.14 29-0.56 20-0.14 291.56 65

-0.19 28-0.61 190.19 360.10 340.57 44

-0.42 23-0.94 120.43 41

-0.23 27-0.33 251.93 730.14 35

-0.37 240.33 39

-0.94 120.14 350.24 37

-0.37 240.00 32

-0.94 12-0.94 12-0.66 18-0.09 300.10 340.19 36

Note: GFL = Gilbert, Fiske, and Lindzey (1998); HK = Higgins andKruglanski (1996).

the number ofmentions in one handbook should be pro-portional to the number of mentions in the second hand-book regardless of status as an author. Therefore, we re-gressed the number of mentions for each FMC in onehandbook on three predictors: (a) the number of men-tions in the other handbook, (b) author status in the crite-rion handbook (coded author = 1, nonauthor = 0), and (c)author status in the predictor handbook (coded author =1, nonauthor = 0). Again, ifmentions frequency is unbi-

ased, we would expect number of mentions in onehandbook to be predicted by number of mentions in thesecond handbook, and authors' status should make littledifference. Suppose authors are objective but are peoplewho have made particularly noteworthy contributions.Author status would have a positive impact on mentions.However, if that impact is objective, then it should be re-flected in both handbooks-that is, being an authorshould have a similar positive weight regardless ofwhether he or she is an author for the GFL orHK Hand-book. In sum, if mentions are objective, then author sta-tus should have no impact-or author status should havea similar impact-regardless of handbook. If, however,authors are self-serving, then being an author in the cri-terion handbook should have a more positive impact onnumber of mentions than being an author in the predic-tor handbook.

The resulting equations for predicting mentions inboth handbooks were similar. The R2 for predictingnumber of mentions in HK is .57, p < .001. The mostreliable predictor of number of mentions in the HKHandbook is the number of mentions in GFL Hand-book, B = .77, t(102) = 10.06,p < .001. Being an authorin the HK Handbook also has a huge impact on numberof mentions in the HK Handbook. Authors are men-tioned much more frequently than nonauthors, B =17.76, t(102) = 5.28, p < .001. If authors are mentionedmore frequently because they are particularly notewor-thy, then author status in the GFL Handbook shouldsimilarly impact number of mentions in the HK Hand-book. Author status in the GFL Handbook does have asizeable impact on mentions in the HK Handbook, butit is opposite in sign, B = -16.70, t(102) = -4.74, p <.001. There are four classes of author status. FMCswho are authors in HK but not in GFL are mentioned17.76 times more often than would be expected basedon the number of mentions in GFL. FMCs who are au-thors in HK (add 17.76 mentions) and also authors inGFL (subtract 16.70) come out close to what would bepredicted by the number of mentions in GFL. How-ever, if there is a self-serving bias, then the number ofmentions in GFL is already inflated by authors in GFL.The subtracted mentions are simply a correction forthat inflation. Similarly, contributors who are not au-thors in HK but are authors in GFL appear to be under-mentioned by 16.70 in HK. Again, we may simply besubtracting out the number of self-serving mentions inGFL. Finally, number of mentions in HK for FMCswho are authors in neither volume are simply predict-able from the number of mentions in GFL. We interpretthis pattern as being consistent with a self-serving bias.

The pattern for predicting number of mentions inGFL is very similar: R2 = .64, p < .01; the coefficientfor predicting number of mentions in GFL from HK isB = .65, t(102) = 10.06, p < .001; the coefficient forpredicting mentions in GFL from being an author inGFL is B = 22.75, t(102) = 8.25; p < .00 1; the coeffi-




cient for predicting mentions in GFL from being an au-thor in HK is negative, B = -11.40, t(102) = -3.47, p <.001. As noted previously, the pattern of coefficientsassociated with author status seems consistent with aself-serving bias interpretation.

Characteristics of the FMCs

Now that we have an idea of who are among themost influential social psychologists of the 1990s, dowe know anything else about them? Yes, we do. Ilooked up each of the FMCs in the American Psycho-logical Association (APA) directory (2000 APA Mem-bership Register, 2000) and the American Psychologi-cal Society directory (Membership Directory of theAmerican Psychological Society, 1998), checked theInternet, wrote directly to a few colleagues, and usedmy own knowledge to fill in some of the informationabout each of these people.

Gender

The FMCs are mostly male, about 83%. Only 18 ofthe 106 FMCs are female. Clearly the number ofwomenin the sample is not representative of our discipline. Ac-cording to the 1997 APA Directory Survey (APA Re-search Office, n.d.), with new member updates for 1998,Division 8 (Society for Personality and Social Psychol-ogy) of the APA is 65% male. Overall, there is propor-tionally twice the number ofwomen in the division as awhole as there are among the FMCs. More interesting,however, is the gender breakdown by status in the divi-sion. As can be seen in Figure 2, almost 50% ofthemem-bers at the Associate level are women. This drops to 21%at the Fellow level, a figure that is only 4% higher thanthe proportion in our elite sample.

a)

a)4a0c

1009080706050403020100

. | E 77 | ~~ingWomen1

!

Associate Member Fellow (Na FMCs

(N=170) (N=2,133) 755) (N=106)

Division 8 Status, FMCs

The gender difference has no easy explanation. In-deed, many of us in social psychology are engaged inshowing how such differences can emerge even if thereare no differences in ability or productivity. Part of it, atleast, may be a simple cohort effect. Indeed, the aver-age degree date (see the following) for male FMCs ismore than a decade later than it is for women, 1965 ver-sus 1978, respectively. To look at it another way, thereare no women among the quartile of FMCs with theoldest degrees, four in the next quartile, seven in thenext, and seven in the quartile containing FMCs withthe most recent degrees. We see in the next section thatthe most productive among us have been around for awhile. Thus, although the gender difference may re-flect bias, it also may simply reflect the demographicsof the field for the period in which the work was done.

It is noteworthy that the female FMCs, as few asthere are, are on average more influential than the men.The mean number of standard mentions (averaged overHK and GFL Handbooks) is .34 for women versus -.07for men. Because of the huge skew in the mentionsdata, however, the median of the standard mentions(averaged over HK and GFL Handbooks) may be amore appropriate index of central tendency. Here, too,the women do a bit better than the men with respectivemedians of-.16 versus -.27.

Age of Degree

How long have our FMCs been at it? One piece ofinformation posted for each contributor is the year inwhich his or her PhD was awarded. This distribution ofthese years is shown in Figure 3 (N = 106).

There are several observations to make about thisdistribution. First, there is some, but not very much, fo-cus on our history. There is very little acknowledge-ment of our classical roots in philosophy; rather, wetend to cite modern contributors to social psychology.The person with the oldest degree to appear on this listis William James, who received his MD degree in1869. He is followed in time by Kurt Lewin (1916),

10

a)

LL.

Figure 2. Gender distribution in APA's Division 8 by member-ship status and in the current set of FMCs. (Source of Division 8data is an APA Research Office document titled "1997 APA Di-rectory Survey, with new member updates for 1998," n.d.)

8

6

4

2

01930 1940 1950 1960 1970 1980 1990

Year of Degree

Figure 3. Frequency distribution of year of highest degree forgroup ofFMCs. Note that the year 1930 represents the year 1930and all of the previous years.



TESSER & BAU

Fritz Heider (1920), Gordon Allport (1922), and Solo-mon Asch (1932); with those five names, we are al-ready into the 1940s.

Figure 3 shows a steady decrease in the number ofpersons frequently mentioned as their degree getsmore than 20 years from the handbook publicationdates. Indeed, 88% of this group of contributors werealive when the handbooks were published. This em-phasis on the work of contemporary scientists proba-bly reflects a number of things. The discipline hasbeen growing, and there were simply fewer socialpsychologists around in the olden days (i.e.,pre-1977); or, it could reflect the emphasis on newer,often more sophisticated research findings (Reis &Stiller, 1992); or it could reflect the lack of a "stan-dard paradigm" with well-developed historical roots.Therefore, we are not particularly driven by historicaltradition as reflected in the work of a pantheon ofearly giants. Perhaps this is a good thing for a scien-tific discipline with an empirical base.

On the other hand, it does take some time to build acareer. Figure 3 clearly shows a drop in the number ofFMCs with degrees more than 20 years old, but it alsoshows a drop in the number of contributors with de-grees less than 20 years old. Ninety percent of the sam-ple received their degree in 1950 or more recently.Only 15% of the sample received their doctoral degreemore recently than 1985, and 15% received their de-gree in 1954 or earlier. So 70% of our frequent contri-butors received their degree in a 35-year window. Halfof our frequent contributors received their degree in an18-year window between 1961 and 1978. The hand-books were published in 1996 and 1998. The contribu-tions of FMCs are acknowledged 20 to 37 years afterthe degree. In round numbers, it takes an average of 20to 35 years of productivity to be recognized as particu-larly influential in our field, and that recognition ap-pears to continue for about 20 to 30 years.A comparison between Division 8 Fellows (APA

Research Office, n.d.) and our HK and GFL HandbookFMCs may be of interest. As can be seen in Figure 4,the FMCs are a bit younger than the Fellows: Using1997, the average publication date of the handbooks, asthe standard, about 46% of the FMCs had their degreeless than 25 years compared to about 25% of the Fel-lows; that is, almost 75% of the Fellows have had theirdegrees for more than 25 years and only about 54% ofthe Fellows have had their degrees for more than 25years-and that includes the FMCs who are deceased.

There is one obvious potential explanation for whyour elite FMC sample is younger than our respectedFellows. Once Fellow status is achieved, it is held forlife. Persons may continue to be Fellows even afterthey are actively producing scholarship. By contrast, aparticular work does not continue to be cited unless thework is seminal and the topic remains lively. Citationsdepend on their timeliness and relevance to question at

80

a) 70

E 60C 504-o 40

C 30a)( 20a)IL 10

0

O3 Fellow

C-------- - :----

<10 10-14 15-19 20-24

Age of Degree in Years>24

Figure 4. Comparison of the age of the degrees of APA Division8 Fellows and the FMCs. Note that age of degree is computedfrom 1997, the year between the publication of the GFL (1998)and the HK (1996) Handbooks.

hand, regardless of the investigator's previous achieve-ments. Fellow status depends critically on a corpus ofwork that may take many years to accumulate.

Even for the FMCs, however, it is unusual to haveone's work recognized by frequent citations very earlyin one's career-that is, within the first 15 years.Therefore, I would like to recognize the eight most re-cent graduates in this category by mentioning theirnames in the order of their degree date: DuaneWegener, 1994; J. G. Hixon, 1991; Felicia Pratto,1988; Shinobu Kitayama, 1987; and the wonderfulclass of 1986-Mahzarin Banaji, Trish Devine,Jonathon Brown, and Chuck Stangor.

Current Affiliations

Where do our FMCs work? I was able to determinethe location for 99% (n = 105) of these people for thetime that the handbooks came out (1996-1998), or inthe case of the deceased contributors, where they lastworked. It seems as if there are highly visible and pro-ductive people almost everywhere. Nevertheless, thereare some institutions that are home to a disproportion-ate number of our FMCs. These places will come as nosurprise to most of you.

As can be seen in Table 3, they include the usualsuspects: Princeton, Stanford, Michigan, Columbia,New York University, Ohio State, and Yale. The pres-ence of the University of Waterloo in the top half of thelist reminds us that social psychology is internationaland that influences outside of the United States are be-coming more important. Indeed, I think the handbooksprovide only a hint of the increasing importance ofthose influences in the most recent developments inour science.

Figure 5 plots the cumulative percentage of FMCsagainst the institutions rank ordered for the number ofFMCs they employ. This figure helps to show the dis-proportionate number of home institutions to numberof scholars. First, all 105 FMCs are employed by only




Table 3. Affiliations ofFrequent Contributors

Affiliation N

Princeton University 6Stanford University 6University of Michigan 5Columbia University 4New York University 4The Ohio State University 4Yale University 4Harvard University 3Purdue University 3University of Connecticut 3University of Illinois 3University of Maryland 3University of Waterloo 3Carnegie-Mellon University 2Indiana University 2Northwestern University 2Texas A & M 2University of California, Santa Barbara 2University of Georgia 2University of Kansas 2University of Massachusetts 2University of Minnesota 2University of Pittsburgh 2University of Texas 2University of Virginia 2University of California, Los Angeles 2Institutions with a Single FMC 28

Note: FMC = frequently mentioned contributor.

54 institutions. Moreover, these 54 institutions are notequal among themselves. An even distribution ofscholars to institutions would generate a straight line.As can be seen in Figure 5, there is a decided bend inthe curve indicating disproportionality. Indeed, the top4 institutions are home to more than 20% of the FMCs;the top 10 institutions employ 40% of the FMCs. Our

100%

90%

80% -

70% -

60%-.C00 50%-0

. 40%-C

FMCs are well respected and desirable, so they havechoices as to where they will be. Clearly there aremany factors that affect such choices. They maychoose to be among other FMCs, but geographicalpreferences, salaries, resources, institutional prestige,and so forth also certainly play a role.

Degree Institutions

Our FMCs tend to work at the same institutions. Didthey also go to the same schools? Table 4 lists the insti-tutions granting PhDs to the largest number of frequentcontributors. (Data was available on 105 FMCs.) Notsurprisingly, the degree-granting institutions are muchthe same as the institutions at which these scholarswork. Again, also tucked in among the familiar, presti-gious U.S. universities, there is a hint of the increasinginternationalization of the discipline. We can see theinfluence of Henri Tajfel with the presence of the Uni-versity of Bristol on the list. The University ofMannheim in Germany is also on the list. Again, how-ever, on the whole the present data may underrepresentnon-U.S. social psychology.

Perhaps what is most striking when looking at thedistribution of the institutions at which our FMCsearned their PhD is its skew. We saw this kind ofskew when we looked at current affiliations; however,the inequality among degree-granting institutions iseven greater. It takes 54 institutions to describe wherethe FMCs work (see Figure 5); it takes only 34 insti-tutions to describe where they received their degree.Three schools-Michigan, Harvard, and Yale-ac-count for almost 30% of the PhDs of our FMCs. Ifwe include Princeton, Columbia, Stanford, OhioState, and University of California, Los Angeles, we

1 6 11 16 21 26 31 36 41 46 51

Rank Order of Institutions (Most to least affiliations)

Figure 5. Cumulative percentage of frequent contributors plotted against rank-ordered institutions of employment. The institution em-ploying the largest number of affiliated FMCs is ranked 1.



TESSER & BAU

Table 4. Degree Granting Institutions ofFrequentContributors

Institution N

University of Michigan 12Harvard University 9Ohio State University 7Princeton University 7Yale University 6Columbia University 5Stanford University 4University of Illinois 4University Minnesota 4University of Texas, Austin 4University of California, Los Angeles 4MIT (Massachusetts Institute of Technology) 3New York University 3University of Bristol 3University of Iowa 3University of North Carolina 3Duke University 2Northwestern University 2University of California, Berkeley 2University of Kansas 2University of Mannheim 2University of Massachusetts 2Single Mentions 12

have accounted for the degrees of over half (55%) ofthe group of FMCs!

Perhaps the relative inequality can be seen mostclearly in Figure 6. The straight line is simply a point ofcomparison. It describes what would happen if all in-stitutions were equal and each institution employedtwo current FMC affiliates, or granted degrees to twoFMCs, or both. This line already implies some concen-tration of talent in that there are many more de-gree-granting institutions than 53. The steep increase(relative to the straight line) of both the current affilia-tion curve and the degree institution curve indicate that

100% /

O 60%-Degree0 ~~~~~~~~Institutions

.2 40% Current40 affiliations0

CL ~~~~~~~~~Equal220%/ ~~~~~~~~~distribution0%

0 10 20 30 40Rank Ordered Institutions

there is an even greater concentration of talent at rela-tively few institutions. Moreover, the concentration isclearly greater at the degree-granting institutions thanat the current affiliations.

There are a number of possible explanations for thegreater concentration of talent at the degree-grantinginstitutions. Perhaps one's initial training has a greaterimpact on productivity than one's immediate col-leagues. Having been trained at a great institution al-lows one to be productive anywhere. Another possibil-ity is that students turn over more quickly than dofaculty, so there is simply a greater throughput of stu-dents than faculty in the most prestigious universities.Even at a place like the University of Michigan, wherethe number of social psychologists is large, the numberof faculty does not come close to the number of PhDsthey have produced in the last 50 or 60 years. Perhapsthe lesser skew among current affiliation institutionsthan among degree-granting institutions reflects therelative youthfulness of the discipline. Perhaps as morecenters of excellence become prominent around theworld, there will be a more even distribution in theplaces where productive scientists get their degree.

Similarities Among Contributors

Each of the people in this sample has made a uniquecontribution to social psychology. However, there maybe similar patterns of contributions, and it may be in-structive to see groups of people who have a similarthread in their work. Again, I turned to the author indexof the handbooks to address this set of questions. I rea-soned simply that if two contributors were discussed inthe same context, then their work is more similar to oneanother than if they were discussed in separate con-texts. On the basis of this reasoning, I constructed anindex of similarity for all pairs of contributors.

Within each handbook, each mention of each con-tributor was compared to every other mention for everyother person in the sample. If the two mentions were inthe same chapter, then 1 similarity point was issued; ifthey were within two pages of one another, a 2nd pointwas given; within one page, a 3rd point; and if on thesame page, a 4th point. All other mention locations re-ceived no points. The points for a single mention ofContributor X were summed over all the mentions ofContributor Y The maximum similarity between Con-tributor X and Contributor Y for a single mention ofContributor X was set to 4 points.8 The overall similar-

Figure 6. Cumulative percentage of frequent contributors plot-ted against institution rank ordered for (a) number of degreesgranted to FMCs (institution granting degrees to the largestnumber of FMCs is ranked 1) and (b) number of FMCs em-ployed by institution (institution employing the largest numberof FMCs is ranked 1). The "equal distribution" line is a hypo-thetical baseline that assumes that each institution has twoFMCs associated with it.

7Reference pages were omitted for this analysis.8Theoretically, and in practice, the number of points for a single

mention between one contributor and anothercan exceed 4. For exam-ple, for a single mention for Contributor X, Contributor Y might haveone mention on the same page (4 points) and another mention on thenext page (3 points), yielding a total of 7 points. As noted in the text,point balances of more than 4 for any single mention were set to 4.




ity of ContributorX to Contributor Y is the similarity ofX to Y averaged over all mentions of X.

This index of similarity is crude, but it has some fea-tures worth noting. First, a high similarity score can re-flect several mentions in the same broad "ballpark," ora single closely related mention, or some combinationof these. Second, combining information at the singlemention level is nonlinear; there is a maximum similar-ity. Finally, because the similarity ofX to Y is averagedover the number of mentions of X, and the similarity ofY to Xis averaged over the number of mentions of Y, thesimilarity of Contributor X to Contributor Y is not nec-essarily equivalent to the similarity of Y to X. Accord-ing to Tversky (1977), this kind of asymmetry maymore realistically capture the psychology of similarityperception than symmetrical similarities.We found that the GFL Handbook and the HK

Handbook identified a highly overlapping set ofFMCs. Do these handbooks also identify the samestructure among the FMCs? Each FMC has a similar-ity to each of the other 105 FMCs in the GFL Hand-book and in the HK Handbook. If the structure in thetwo handbooks is similar, then the pattern of similari-ties of each FMC to all the others should be similar ineach of the handbooks. To assess this, for each of the106 FMCs we computed a correlation between thesimilarity scores in the GFL Handbook with the simi-larity scores in the HK Handbook across the 105other FMCs. The resulting correlations suggest thatthe two handbooks do structure the FMCs in a similarway. All 106 correlations are positive and signifi-cantly different from zero, p < .02. The median corre-lation is .60. Because both handbooks seem to struc-ture the FMCs in a similar way, for the sake ofsimplicity we simply averaged the 106 x 106 similar-ity matrix across handbooks.

Extracting the StructureAmong Contributors

There are many ways to analyze this 106 x 106 sim-ilarity matrix to extract commonalities among theFMCs. Most of these techniques boil down to two ap-proaches: One set of techniques groups contributorsinto qualitatively different clusters of people; the otherfinds contributor dimensions and computes weights or"loadings" for each person on each dimension.A problem with the clustering approach is that one

tends to interpret everyone in a group as equally repre-sentative of what is common to the group. However, asthe group increases in size, some people become moreperipheral than others. On the other side of the coin,once a person is placed into one group it becomes diffi-cult to see his or her connections with other groups. Adimensional or factor approach allows for persons tohave affinities to more than one commonality amongthe contributors; that is, an individual can have high

loadings on more than one factor. On the other hand, acontributor may be unique with little in common withothers. Such an individual would have small, or nearzero, loadings on all of the factors. Knowledge of theparticular people with high loadings on the same factorthen serves as the basis for interpretation.We decided to extract contributor dimensions using

a factor analytic approach. This approach typicallystarts with a symmetrical correlation matrix. Recallthat our matrix consists of similarity points, not corre-lations; and, it is asymmetrical, not symmetrical (i.e.,the similarity ofFMCX to FMC Yis not necessarily thesame as the similarity of FMC Y to FMC X). We con-verted the similarity matrix to a symmetrical correla-tion matrix as follows. As noted previously, each FMChas a similarity score to every other FMC. We simplycorrelated these vectors for every pair of FMCs. (Simi-larities involving the two FMCs whose vectors werebeing correlated were omitted, i.e., vectors were 104elements, not 106 elements, long.) This resulted in a106 x 106 correlation matrix in which each of the cor-relations reflects the extent to which the two FMCs arealike in their similarity to every other FMC.

The results of an initial analysis of this matrix sug-gested that we rotate eight factors. We selected aneight-factor solution for several reasons: An examina-tion of the scree plot showed some flattening after theeighth factor; the eigenvalue for the eighth componentwas greater than 2.3, and the ninth component was wellbelow 2.0; and a solution with eight factors seems par-simonious enough to be interpretable and large enoughto be inclusive. Reducing the number of factors ap-peared to merge distinctive lines of research, and in-cluding more factors seemed to stretch interpretability.Therefore we report an analysis in which eight factorswere extracted and subjected to a varimax (orthogonal)rotation. Together, these eight factors accounted for84% of the variance in the correlation matrix.

Contributor Factors

The first rotated factor, at 56%, easily accounts forthe lion's share of the explained variance in FMC simi-larity. Indeed, it accounts for more then four and a halftimes the variance of its nearest competitor. I am surethat you did not need convincing, but the 1990s is clearlya decade of social psychology that belongs to SocialCognition. There are manyFMCs with substantial load-ings on this factor. Table 5 lists the 20 FMCs with thehighest loading on this factor. The presence of nameslike Don Carlston, Tom Srull, Eliot Smith, WilliamRholes, Bob Wyer, Dave Hamilton, John Bargh, ToryHiggins, Lenny Martin, and Jerry Bruner make the iden-tity of this factor as Social Cognition fairly easy.

It is worth pointing out that this appears to be a uni-directional factor. The loadings range from very highpositive numbers to numbers around zero. Table 5 in-



TESSER & BAU

Table 5. FMC Factor 1: Social Cognition

Contributor Factor Loading

Carlston, D. E. .92Srull, T. K. .92Smith, E. R. .92Rholes, W. S. .89Wyer, R. S., Jr. .85Hamilton, D. L. .81Bargh, J. A. .81Higgins, E. T. .81Martin, L. L. .80Bruner, J. S. .78Strack, F. .76Schwarz, N. .76Hastie, R. .76Sherman, S. J. .76Stangor, C. .76Devine, P. G. .73Fiske, S. T. .71Banaji, M. R. .71Pratto, F. .69Gilbert, D. T. .69Pruitt, D. G. -.12Deutsch, M. -.15


eludes the two individuals with the lowest (most nega-tive) loading on this factor to illustrate the point. I makenote of it because unidirectionality in these factors ap-pears to be the usual case and it makes sense. For ex-ample, one may do social cognition research and thatwould be reflected in a positive loading; or, one may dowork that is largely independent of social cognitionand that would result in a low loading on the factor. It isdifficult, however, to even conceptualize what it meansto make contributions that are so antithetical to the so-cial cognition area so as to result in a substantial nega-tive loading on the factor.

The second factor accounted for approximately12% of the explained variance. Table 6 shows the 20top loading and the 3 lowest loading FMCs. This fac-tor, like Factor 1, appears easy to identify. The FMCswho lead the list have all made substantial and highlyvisible contributions to the attitudes area. They includeWendy Wood, Irv Janis, Bill McGuire, Rich Petty, Al-ice Eagly, Duane Wegener, Shelley Chaiken, JohnCacioppo, Marty Fishbein, and Icek Ajzen.

Factor 3 accounted for 9% of the explained vari-ance. I have named it Motivated Attribution, but thecommonality among the highest loading contributorsis not as clear to me as it was for Factors 1 and 2.Names like Jones, Miller, Darley, and Hilton have clearconnections to attribution theory; people like Ross,Kunda, Pyszczynski, and Greenberg have clearly ad-dressed motivational issues in attribution-as hasnearly everyone else on the list. There are at least acouple of other themes as well: Several of the FMCshave reported research on self-confirmation and inter-personal aspects of attribution theory-for example,

Table 6. FMC Factor 2: Attitudes


Wood, W. .93Janis, I. .93McGuire, W. J. .92Petty, R. E. .90Eagly, A. H. .90Wegener, D. T. .89Chaiken, S. .88Cacioppo, J. T. .86Fishbein, M. .77Ajzen, I. .74Mackie, D. M. .71Zanna, M. P. .68Bem, D. J. .67Greenwald, A. G. .67Cialdini, R. B. .66Fazio, R. H. .66Tesser, A. .65Cooper, J. .65Festinger, L. .64Kruglanski, A. W. .57Reis, H. T. -.07Bond, M. H. -.10


Snyder, Swann, Darley, and Hilton. There is even aPrinceton connection: Darley, Kunda, Hilton, Swann,Miller, and Jones. Table 7 lists the 20 highest loadingFMCs and a couple of low-loading FMCs.

Factor 4 accounted for 8% of the explained variance(see Table 8). The people who lead this factor are MikeScheier, Chuck Carver, Walter Mischel, Bob Wick-lund, Albert Bandura, Dan Wegner, Roy Baumeister,Nancy Cantor, Jack Brehm, and William James. It is

Table 7. FMC Factor 3: Motivated Attribution


Darley, J. M. .77Greenberg, J. .75Pyszczynski, T. A. .74Kunda, Z. .73Hilton, J. L. .72Swann, W. B., Jr. .70Miller, D. T. .65Snyder, M. .63Jones, E. E. .59Ross, M. .58Crocker, J. .57Pittman, T. S. .57Heider, F. .56Kruglanski, A. W. .56Nisbett, R. E. .55Taylor, S. E. .50Ross, L. .48Davis, K. E. .47Tetlock, P. E. .46Tversky, A. .45Moreland, R. L. -.14Ekman, P. -.16





not difficult to recognize this as a factor having to dowith research on the self.

The fifth factor accounted for 5% of the explainedvariance and is host to people like Dean Pruitt, JohnThibaut, Morton Deutsch, David Messick, John Le-vine, Dick Mooreland, Hal Kelley, Jud Mills, SolomonAsch, and Bob Cialdini. It looks like we have gonefrom the intrapersonal focus associated with socialcognition, attitudes, attribution, and self to a concernwith the interpersonal. I have named this factor Inter-personal Influence, but the presence of people likeBerscheid, Clark, and Mills also gives the factor a hintof relationship research. Table 9 lists the 20 highestloading FMCs on this factor.

The sixth factor also accounted for 5% of the ex-plained variance (see Table 10). This factor appears togo a step up on the scale from intrapersonal and inter-personal to intergroup relations. I think that the labelIntergroup Relations and Stereotypes captures much ofwhat is common to the work of the highest loadingpeople on this dimension. Some of these people areHenri Tajfel, John Turner, Michael Hogg, Kay Deaux,Rupert Brown, Marilynn Brewer, Jenny Crocker,Mahzarin Banaji, Claude Steele, and Dick Mooreland.Table 10 presents the names of all the FMC with load-ings above .30. In the case of this factor only, there areFMCs with negative loadings greater than .2. Theirnames and loadings are in the table, but no interpreta-tion is offered.

It seems unlikely to me that the Factor 7 would haveemerged only 10 years ago. It accounts for only 3% ofthe explained variance, and it appears to reflect thefield's great interest in questions of psychological uni-

Table 8. FMC Factor 4: Self


Scheier, M. F. .92Carver, C. S. .90Mischel, W. .82Wicklund, R. A. .80Bandura, A. .78Wegner, D. M. .72Baumeister, R. F. .69Cantor, N. E. .69Brehm, J. W. .68James, W. .54Brown, J. D. .53Tesser, A. .40Steele, C. M. .39Bem, D. J. .37Swann, W. B., Jr. .36Taylor, S. E. .34Pyszczynski, T. A. .34Ruble, D. N. .32Greenberg, J. .31Pittman, T. S. .30Moreland, R. L. -.08Levine, J. M. -.09

Table 9. FMC Factor 5: Interpersonal Influence


Pruitt, D. G. .88Thibaut, J. W. .88Deutsch, M. .87Messick, D. M. .84Levine, J. M. .78Moreland, R. L. .78Kelley, H. H. .76Mills, J. .54Asch, S. E. .52Cialdini, R. B. .49Festinger, L. .49Lewin, K. .48Ross, L. .47Clark, M. S. .47Kenny, D. A. .45Hogg, M. A. .44Berscheid, E. .40Nisbett, R. E. .39Miller, D. T. .38Turner, J. C. .36Pratto, F. -.11Banaji, M. R. -.16

Note. FMC = frequently mentioned contributor.

versality. The cultural approach focuses on plasticityof cognition and belief; the evolutionary approach fo-cuses on our common biological origins. I am basingmy interpretation of the factor on the first six names onthe list. Thus, Kitayama, Bond, Triandis, and Markusare strongly associated with cultural psychology andEkman and Buss with universals in behavior. However,other themes can be gleaned from this list of contribu-tors. For example, there is a strong emotion thread with

Table 10. FMC Factor 6: Intergroup Relations andStereotypes


Tajfel, H. .84Turner, J. C. .83Hogg, M. A. .79Deaux, K. .79Brown, R. J. .78Brewer, M. B. .61Crocker, J. .53Banaji, M. R. .46Steele, C. M. .41Moreland, R. L. .36Levine, J. M. .36Stangor, C. .35Allport, G. W. .34Bond, M. H. .33Mackie, D. M. .31Messick, D. M. .30Kahneman, D. -.20Brehm, J. W. -.22Tversky, A. -.24Schachter, S. -.32Singer, J. E. -.34


83




TESSER & BAU

names like Ekman, James, Schacter, Singer, andZajonc. All FMCs with loading of .3 or higher arelisted in Table 11.

The final factor accounted for 3% of the commonvariance. Like Factor 5, this appears to be concernedwith interpersonal relationships. The emphasis here,however, seems to be on relationships rather than influ-ence. Thus, the highest loading FMCs are Harry Reis,Peggy Clark, Ellen Berscheid, and Jud Mills. DavidBuss contributes to the relationship literature from anevolutionary perspective and also has a substantial load-ing on this factor. Also, like Factor 7, there is a dose ofemotion research in this factor with Ekman, Schacter,and Singer having noteworthy loadings. Table 12 liststhe FMCs with loadings greater than .30.

Something for Everyone?

Earlier I suggested that a dimensional or factor ap-proach might be more easily interpreted becausesome individuals may not fit well or easily into anygroup and others might feel equally at home in multi-ple areas. To see if this was the case in these factordata, I classified each contributor as having an affin-ity for one factor, no factors, or more than one factor.This was accomplished by simply counting the num-ber of factors on which the individual had loadings of.45 or greater.

As expected, most of the contributors (71%) tend tospecialize in one of the factors we captured. A small mi-nority of FMCs (5%), however, have no loadings ex-ceeding .45 on any factor. Their contributions may be inareas that are not well represented by the factors-suchas developmental social psychology, Diane Ruble's ma-jor area-or their contributions may be seminal in somany areas that they can't be pinned down, likeSchachter and Singer. Finally, there are a group of peo-

Table 11. FMC Factor 7: Culture and Evolution


Kitayama, S. .86Bond, M. H. .84Triandis, H. C. .81Markus, H. R. .78Ekman, P. .54Buss, D. M. .44Lewin, K. .43Davis, K. E. .39James, W. .37Nisbett, R. E. .36Asch, S. E. .36Schachter, S. .33Ross, L. .31Singer, J. E. .31Bruner, J. S. .30Zajonc, R. B. .30Mills, J. -.09Hilton, J. L. -.11

Table 12. FMC Factor 8: Interpersonal Relationships


Reis, H. T. .82Clark, M. S. .75Berscheid, E. .71Mills, J. .63Kenny, D. A. .47Ekman, P. .47Buss, D. M. .43Singer, J. E. .41Schachter, S. .37Swann, W. B., Jr. .31Kelley, H. H. .31Pittman, T. S. .31Snyder, M. .30Ajzen, I. -.18Fishbein, M. -.19


ple (25%) whose work seems well represented by two ofthese factors: For example, Banaji loads on social cogni-tion and on intergroup relations and stereotypes,Kruglanski loads on attitudes and motivated cognition,and Ekman loads on culture and evolution and on inter-personal relationships. None ofthe FMCs have loadingsof greater than .44 on three or more factors.

Research Area and ResearchProminence

The factor loadings are calculated on the basis of theinterpersonal similarities. From a statistical point ofview, they need not bear any relation to research promi-nence as reflected in the number of mentions in thehandbooks. On the other hand, some areas may be"hotter" or more generative than others. To explore thisissue, I correlated factor loadings on each of the personfactors with the mean standardized number of men-tions in the handbooks.

There are a couple of small but, perhaps notable cor-relations between factor scores and number ofmentionsin the handbooks. Persons with higher loadings on Fac-tor 1 (Social Cognition) and on Factor 2 (Attitudes)seem to have been mentioned a bit more frequently (r =.24 and .23,9 respectively). One explanation for thesecorrelations is the prominence of the factors in the field.That is, these factors account for the largest proportionof the shared variance. Also, these areas tend to be asso-ciated with a large number of medium range, specifictheories that may be easily transported to other areas.Perhaps these modest correlations reflect this kind oftheoretical lending and borrowing.

9Significance tests associated with inferential statistics are not

used in this context because we are not focusing on a random samplefrom some population but on the population itself of major contribu-tors to the handbooks.

84





Summary of Similarity

The affinities of the heavy contributors to the disci-pline appear to make sense. The factors are relativelyeasy to interpret, and they seem, to me at least, to do agood job of capturing much of what is common to whatsocial psychologists do. They span the intrapersonaland the interpersonal. They show our classic concernwith attitudes and our love affair with social cognitionand social influence. We see our recent and very popu-lar interest in stereotypes and ingroup-outgroup phe-nomena. There is also a relatively clear factor reflect-ing our needed, broadening focus on the issues ofbiology (evolution) and culture.

Clearly these factors are not totally comprehensive.There is no "aggression" or "altruism" factor. There areother specific domains that might have emerged. Never-theless, the factors that emerged do paint a broad-brushpicture ofwhat social psychology was like in the last de-cade of the 20th century and who was doing what.

Conclusion

To know a scientific discipline is, at least in part, toknow something about the people who are constructingthat discipline. I have attempted to provide you with asnapshot, a picture of the people constructing socialpsychology on the cusp of the 21st century. The per-sons who have been identified will come as no surpriseto active scholars in the area. Not present are manypeople whose work I admire and who I would vote tohave on such a list. I will not mention specific namesbecause I am sure to make some egregious omission.However, there are at least two general categories thatappear underrepresented. As I see the field of scholarsat the moment, I am convinced that this data under-represents the scholarship of women and of personsoutside the United States, particularly Western Europeand Australia.

The factors that describe how we organize ourselvesalso will not be a total surprise to active scholars in the

discipline. Whether this is an accurate description ofthe field at this moment is an open question. The factorstructure has more familiarity than we would expect ifthe discipline was changing and the factor structure re-flected the cutting edges of those changes. The disci-pline is changing, but there is a lag in what is reflectedin the handbooks. However, I am not sure how, pre-cisely, to characterize those changes other than to men-tion the obvious trend in psychology as a whole towarda greater emphasis on neuroscience approaches.

This description is static and has a built-in lag. Ascientific discipline, like a living organism, changescontinuously. Social psychology is no exception. In-deed, there is already a new handbook. Nevertheless, Ifound it interesting to learn more about who was con-structing the discipline in the 1990s and how they wereorganized. I hope you did as well.

References

2000 APA membership register (2000). Washington, DC: AmericanPsychological Association.

APA Research Office. (n.d.). 1997 APA Directory Survey, with newmember updates for 1998. Unpublished manuscript.

Gilbert, D. T., Fiske, S. T., & Lindzey, G. (Eds.). (1998). The hand-book of social psychology (4th ed.). Boston: McGraw-Hill.

Gordon, R., & Vicari, P. J. (1992). Eminence in social psychology: Acomparison of textbook citation, Social Sciences Citation Indexand research productivity ranking. Personality and Social Psy-chology Bulletin, 18, 26-38.

Hewstone, M., & Brewer, M. (Eds.). (2001). Blackwell handbook ofsocial psychology. London: Blackwell.

Higgins, E. T., & Kruglanski, A. W. (Eds.). (1996) Social psychol-ogy: Handbook of basic principles. New York: Guilford.

Membership Directory of the American Psychological Society.(1998). Washington, DC: American Psychological Society.

Reis, H. T., & Stiller, J. (1992). Publication trends in JPSP: Athree-decade review. Personality and Social Psychology Bulle-tin, 18, 465-472.

Tesser, A., & Schwarz, N. (Eds.). (2001). Blackwell handbook ofso-cial psychology. Volume 1: Intraindividual processes. Malden,MA: Blackwell.

Tversky, A. (1977). Features of similarity. Psychological Review, 84,327-352.



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Social Psychology: WhoWe Are andWhatWe Dodtg/TESSER_BAU.pdfpages in the two-volume GFLHandbook5 and 12 or morepagesinthesingle-volumeHKHandbook.These cutoffs are arbitrary, but they