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Still Searching for the Zipperump-a-Zoo: A Reflection After 40 Years
Robert J. Sternberg
Cornell University
ABSTRACT—In this article, I describe chronologically my
attempts over a 40-year career to understand the nature
of human intelligence. I explain how later attempts built
on earlier ones, with each attempt revealing the earlier
one to be too limited and narrow in the questions it asked.
In my early work, I envisioned intelligence in terms of
components of information processing. Later, I viewed
these components as contributing to three distinct but
related aspects of intelligence: analytical, creative, and
practical. I came to realize the importance of contextual
factors in determining what constitutes adaptive behavior.
Still later, I viewed wisdom as part of the mix. The search
has been rewarding, except for the fact that I have not
yet completed it and never will.
KEYWORDS—intelligence; analytical skills; creative skills;
practical skills; wisdom-based skills
When my eldest children Seth and Sara were young, I used to
read them a book entitled Professor Wormbog in Search for the
Zipperump-a-Zoo (1). Seth and Sara are now adults with chil-
dren of their own. But the more things change, the more they
stay the same: I now read the book to my 4-year-old triplets.
The book is about Professor Wormbog, who wants to collect one
of each of a panoply of strange animals. There is one animal for
each letter of the alphabet, but the one animal that has eluded
him is the last in the list: the Zipperump-a-Zoo. He searches
high and low, cannot find it, and gives up. He goes to sleep on
his couch. While he sleeps, the reader learns that Wormbog’s
house is full of Zipperump-a-Zoos. They just never appear to
him when he is looking, even though they are right there in front
of him.
I used the story of Professor Wormbog as a figurative basis for
a Broadbent lecture I gave to the British Psychological Society,
which was published in the Society’s journal, The Psychologist
(2). At that point, I had completed half my career and felt it was
a good time to take stock. By now, 15 years later, I probably am
at least three-quarters or so finished with my career, and it is
probably a good time to take another look. My views on intelli-
gence, as well as the field of intelligence, have developed con-
siderably since then. What has not changed is the elusiveness of
the figurative Zipperump-a-Zoo. You and I know that intelli-
gence is right there in front of us, its manifestations as easily
observed as were the manifestations of the Zipperump-a-Zoo in
Professor Wormbog’s home. But we, like he, just cannot quite
see the beast. It is as elusive as ever.
STAGE 0: THE PREHISTORY
I have long believed that IQ is not the whole story of intelli-
gence. Like McClelland (3), Gardner (4), and Ceci (5), among
others, I believe that IQ tests are narrow in what they assess as
intelligence (see also (6)). But if a score on an IQ test is not the
whole story, what is?
As a result of my dismal scores on the group IQ tests that
were all the rage in the 1950s, I became interested in intelli-
gence in elementary school (see Ref. 7). When I was in the sev-
enth grade, in 1963, as part of a science project, I created my
own IQ test: the Sternberg Test of Mental Abilities (STOMA— no doubt you have heard of it!). I thought that what was wrong with IQ tests is that they insufficiently sampled the skills
involved in intelligence. So I put into my test just about every
subtest I could find that was used in existing intelligence tests. I
Robert J. Sternberg, Cornell University.
I thank my mentors—Endel Tulving when I was an undergraduate student at Yale, Gordon Bower when I was a graduate student at Stanford, and the late Wendell Garner when I was a junior faculty member at Yale—for all they taught me that has helped guide me in my research career.
Correspondence concerning this article should be addressed to Robert J. Sternberg, Department of Human Development, College of Human Ecology, Cornell University, B44 MVR, Ithaca, NY 14853; e-mail: [email protected].
© 2015 The Authors
Child Development Perspectives © 2015 The Society for Research in Child Development
DOI: 10.1111/cdep.12113
Volume 9, Number 2, 2015, Pages 106–110
CHILD DEVELOPMENT PERSPECTIVES
did not know statistics, but I knew enough to discover, through
testing, that after a certain point, it did not seem to matter how
many subtests I gave: The results were about the same. I had
rediscovered Spearman’s (8) g. No Zipperump-a-Zoo there!
STAGE 1: THE COMPONENTIAL THEORY OF
INTELLIGENCE
By the time I was in graduate school at Stanford and then an
assistant professor at Yale, I concluded that I finally had figured
out what was wrong with IQ in particular and the whole psycho-
metric approach to intelligence in general. The problem was
focusing on individual differences—person variation—instead of on information processing, as assessed by stimulus variation
(9). So my colleagues and I started giving mental-test problems
in different forms, recording reaction times and error rates, and
mathematically modeling the cognitive processes involved in
solving inductive (e.g., analogies) as well as deductive reasoning
problems (e.g., categorical syllogisms) as well as verbal-compre-
hension problems (where test takers had to figure out the mean-
ings of unknown words). We also gave psychometric ability tests
so we could relate components of information processing to psy-
chometrically determined abilities. Using these techniques, we
ascertained the components of information processing people
used, the strategies into which these components were com-
bined, the mental representations upon which the processes
acted, and the latencies and error rates associated with the com-
ponents (10, 11).
For example, we found that most people solve linear syllo-
gisms (e.g., John is taller than Mary. Mary is taller than Bill.
Who is shortest?) using a combination of linguistic and spatial
strategies, that encoding the terms of the sentences was time-
consuming, and that we could distinguish components of infor-
mation processing that were linguistically based from those that
were spatially based. We also could account for the develop-
ment of component processes in linear syllogisms, analogies,
and other types of problems over different age spans (12–14). I came to believe that components are of three kinds: meta-
components, which plan, monitor, and evaluate problem solving
(e.g., recognizing the existence of a problem, defining the nature
of the problem); performance components, which execute the
problem solving (e.g., encoding items, inferring relations
between items); and knowledge-acquisition components, which
learn how to solve the problems in the first place (e.g., selec-
tively encoding what information is relevant, selectively compar-
ing new information to old information stored in long-term
memory). Some kinds of componential processes (e.g., inference)
continued to develop monotonically, but other kinds of compo-
nential processes (e.g., encoding) did not. Children first became
faster in encoding and then, when they learned that strong
encoding could speed up their reasoning and problem solving,
actually became slower. So we learned that development was
not a matter of continuity versus discontinuity, but a matter of
both (15). I thought I had found the Zipperump-a-Zoo. I was
wrong.
The componential approach was elegant—if I must say so myself—but had three problems. First, in regression equations, the component latency that correlated most strongly with g was
the regression constant. That was clearly not what I had hoped
for, as that was the unanalyzed component. Second, the
approach worked for problems whose information processing
could be decomposed relatively easily, but it was not clear how
it would work for more complex problems, such as the crypt-
arithmetic problems studied by Newell and Simon (16): For
example, given DONALD + GERALD = ROBERT, D = 5, test takers would have to figure out what numerals to put in place of
the remaining letters. Third, I concluded that all I was doing
was reanalyzing IQ test data: Psychometricians analyzed subject
variance; I analyzed stimulus variance. But the underlying
assumption was still that IQ is all there is.
STAGE 2: THE TRIARCHIC THEORY OF
INTELLIGENCE
By the early 1980s, I was convinced that the componential
approach to intelligence was inadequate. Partly through the lit-
erature and partly through my experiences as director of gradu-
ate studies in psychology at Yale, I became convinced that
intelligence comprised more than just the kinds of analytical
skills measured by intelligence tests, including the ones I had
been using. In particular, I believed that intelligence involved
creative and practical skills (17, 18), not just analytical intelli-
gence or what is commonly called general intelligence, or g.
General intelligence is a modestly to moderately good predictor
of many forms of behavior (19), but much unexplained variance
remains in its prediction of various criteria, such as academic
success, job success, and health. When I was tackling the con-
cept of g in the early 1980s, it was a time of some ferment in
the field of intelligence, with Howard Gardner (20) proposing
his theory of multiple intelligences at about the same time. My
colleagues and I did empirical work on practical intelligence
(21) and creative intelligence (22, 23).
I called the theory triarchic because it had three parts: a part
specifying the information-processing components of intelli-
gence; a part specifying what constituted creative and automa-
tized use of those components, depending on one’s level of
experience in given tasks and situations; and a part dealing with
how the components could be used practically by adapting to,
shaping, and selecting environments. However, some scholars
came to see the theory as triarchic because of its distinction
among analytical, creative, and practical aspects of intelligence
—and I eventually adopted that view, too. Unlike in Gardner’s (20) theory, which specified independent intelligences, the three
aspects of intelligence were not viewed as independent. Rather,
components of intelligence were used analytically when applied
to relatively familiar and abstract problems; used creatively
Child Development Perspectives, Volume 9, Number 2, 2015, Pages 106–110
Still Searching for the Zipperump-a-Zoo 107
when applied to relatively novel tasks and situations; and used
practically when applied to everyday situations in which people
needed to adapt to, shape, and select environments.
I thought I had found the Zipperump-a-Zoo at last. I had not.
I was viewing intelligence as some kind of weighted combina-
tion of its analytical, creative, and practical aspects, and that
was wrong.
STAGE 3: THE THEORY OF SUCCESSFUL
INTELLIGENCE
In the triarchic theory, I noted something about human intelli-
gence, but at the time, did not realize its full significance. That
something was that people are intelligent, in large part, by virtue
of recognizing their strengths and weaknesses, and of finding
ways to capitalize on their strengths and compensating for or
correcting their weaknesses. No single weighted combination of
skills characterized a person’s intelligence because people suc-
ceed in large part not just because of their abilities, but also
because of their patterns of capitalization, on one hand, and
compensation and correction, on the other (24). It was as impor-
tant to leverage one’s abilities effectively as to have the abilities
in various degrees in the first place.
We studied validating the theory of successful intelligence,
particularly with regard to whether the theory could improve
instruction. We found that teaching for successful intelligence
improved school achievement (25); however, when we tried to
upscale the work some years later, we were less successful (26).
We lacked the resources to ensure fidelity of treatment, but the
weak findings may have been the result of many possible
causes. We also found that students who were taught at least
some of the time in a way that capitalized on their strengths per-
formed more optimally than students who were not taught in a
way that considered their abilities (27).
This is about where I was when I wrote the first article for The
Psychologist on my search for the Zipperump-a-Zoo (2). But I
knew I had not found the Zipperump-a-Zoo, for at least two rea-
sons. First, I had no well-validated measures of the elements of
the theory of successful intelligence. Second, my experience
suggested that although I acknowledged context effects on intel-
ligence, I was underestimating them.
My first goal was to develop validated measures and show that
they could be useful. A team of collaborators and I constructed
an assessment for an enterprise we called the Rainbow Project
(28). The assessment was administered to roughly 1,000 high
school seniors and college freshmen. The students varied widely
in their geographic region as well as in the level of prestige of
the institution they attended.
By using tests of analytical, creative, and practical skills, we
could about double the prediction of how the SAT or the ACT
alone influenced freshman GPA, and we could reduce substan-
tially ethnic-group differences on our measures in comparison
with the SAT and ACT. We also found separable creative and
practical factors, although the analytical factor we anticipated
instead was characterized by the multiple-choice format. That
is, no matter what we intended to measure, if we measured it by
multiple-choice testing, we ended up with an analytical test. In
a separate study (29), we showed that we could improve predic-
tion of success in a graduate business school over and above the
prediction obtained from the Graduate Management Admission
Test (GMAT). In particular, our test predicted success in a crea-
tive independent project, whereas the GMAT did not. My col-
laborators and I also showed that ethnic-group differences could
be reduced in our augmented versions of various Advanced
Placement (AP) examinations, in particular, in psychology, sta-
tistics, and physics (30, 31).
The Rainbow Project succeeded, at least in a predictive way,
but our funders, the College Board, refused to renew our fund-
ing, claiming that the assessment could not be upscaled. I dis-
agreed. I saw all my research plans going up in smoke. So I
decided to enter administration, which would give me a chance
to use measures like the ones we developed in the undergradu-
ate admissions process. We did so when I was Dean of Arts and
Sciences at Tufts University and Provost at Oklahoma State Uni-
versity. Through a project called Kaleidoscope, we increased
prediction not only of college academic performance but also of
extracurricular and leadership performance, and we continued
to reduce ethnic-group differences (32). These admissions pro-
cedures are still used at Tufts (Kaleidoscope) and Oklahoma
State (Panorama).
Of course, all of these studies were conducted in U.S. main-
stream culture and did not look beyond it. So they could address
some questions about performance of U.S. college-bound stu-
dents, but not about students in other countries. By the turn of
the 20th century, I was looking at cultural and other contextual
factors not only in what it meant to think and perform intelli-
gently, but also on what people meant by intelligence. Although
as psychological scientists, we may discount people’s implicit
theories (folk conceptions) of intelligence, these implicit theories
determine largely both their judgments of the intelligence of oth-
ers and how they raise their children to be intelligent. I had
been studying implicit theories for a while (33, 34), but I had
studied them in the continental United States. I now found that
people’s conceptions of intelligence differed widely across cul-
tures (35). Moreover, what they needed to do to adapt to their
environment varied wildly across cultures (36).
For example, rural Kenyan school children needed to learn
the names of natural herbal medicines to combat frequent para-
sitic illnesses (37), and rural Yup’ik children in Alaska needed
to learn spatial navigation, hunting, and ice-fishing skills (38).
Some of the children who excelled in these indigenous skills did
not fare well on conventional intelligence tests, and some of the
children who did well on standardized tests did not do well on
the indigenous tasks. People in different cultures had very dif-
ferent metaphors of mind (39, 40) and as a result, raised their
children to be smart in terms of their own implicit theories of
Child Development Perspectives, Volume 9, Number 2, 2015, Pages 106–110
108 Robert J. Sternberg
intelligence. When these implicit theories matched those of the
school, the children tended to look smart; but when the implicit
theories were a poor match, the children tended not to look so
smart (41).
I still did not have my Zipperump-a-Zoo and I knew it: I now
realized that even people who were successfully intelligent
could be plenty smart but remarkably foolish (42).
STAGE 4: THE AUGMENTED THEORY OF SUCCESSFUL
INTELLIGENCE
By the early 2000s, I was convinced the theory of successful
intelligence lacked one crucial feature: It did not consider wis-
dom (43, 44). I came to view wisdom as the application of the
analytical, creative, and practical aspects of successful intelli-
gence for a common good, over the long as well as the short
terms, through the infusion of positive values (44). People could
be smart, both in terms of IQ and of successful intelligence, and
yet commit egregious cognitive fallacies in their thinking, in
particular, egocentrism (“It’s all about me”), unrealistic opti-
mism (“It’s my idea so it has to work out”), false omniscience
(“I’m so smart, I know all there is to know”), false omnipotence
(“I’m so smart, I’m all-powerful”), false invulnerability (“I’m so
smart, no one ever will be able to touch me”), and ethical disen-
gagement (“Ethics are important for other people, but I’m too
smart for that.”). Recently, I have become interested in why so
many people’s ethical reasoning goes astray (45). Stanovich (46)
made a related point: People can be smart but highly irrational.
Unfortunately, they do not realize how irrational they are
because they cloak themselves in their not-always-useful IQs.
THAT STILL-HIDDEN ZIPPERUMP-A-ZOO
No, I still have not found the Zipperump-a-Zoo. I know it, and
others are convinced that I am not even close. For one thing,
although I have been studying intelligence as modifiable (47), I
know that intelligence has state-like properties that even a view
of intelligence as modifiable does not capture (48). In universi-
ties today, students take drugs that boost test scores to capitalize
on these state-like properties, raising a new question of what it
means for a test, administered in a brief period of time, to be
fair. Moreover, although I have argued that general intelligence
(g) is part of the whole package of intelligence, many psycholo-
gists and especially psychometricians believe that, when it
comes to intelligence, g is pretty much the whole thing, and they
question much or all of my research (19, 49–51). Personally, I accept a hierarchical model of g, such as Carroll’s (52): I just do
not believe that g, by itself or in a hierarchical arrangement, is
all there is to intelligence.
In the end, you never find the Zipperump-a-Zoo, though it
may lurk in your office, living room, or anywhere else. You pass
the torch to your students in the hope they may find it, and the
best they can do is pass on their torch when the time comes.
The search has been fun, though, and I have had the pleasure to
see plenty of other animals in Professor Wormbog’s menagerie
along the way, even though the Zipperump-a-Zoo has eluded
me, no matter where I have looked. Should you encounter any-
one who believes he or she has found it—and there are plenty of those in the field of intelligence—my advice is: “Caveat emp- tor: Buyer beware!”
REFERENCES
1. Mayer, M. (1976). Professor Wormbog in search for the Zipperup-a- Zoo. New York, NY: Golden Press.
2. Sternberg, R. J. (2000). In search of the Zipperump-a-Zoo: Half a career spent trying to find the right questions to ask about the nature of human intelligence. The Psychologist, 13, 250–255.
3. McClelland, D. C. (1973). Testing for competence rather than for intelligence. American Psychologist, 28, 1–14.
4. Gardner, H. (1983). Frames of mind: The theory of multiple intelli- gences. New York, NY: Basic.
5. Ceci, S. J. (1996). On intelligence. . .more or less. Cambridge, MA: Harvard University Press.
6. Sternberg, R. J. (2015). Multiple intelligences in the new age of thinking. In S. Goldstein, D. Princiotta, & J. Naglieri (Eds.), Hand- book of intelligence: Evolutionary theory, historical perspective, and current concepts (pp. 229–242). New York, NY: Springer.
7. Sternberg, R. J. (2014a). I study what I stink at: Lessons learned from a career in psychology. Annual Review of Psychology, 65, 1–16.
8. Spearman, C. (1927). The abilities of man. New York, NY: Macmillan.
9. Sternberg, R. J. (1980b). Sketch of a componential subtheory of human intelligence. Behavioral and Brain Sciences, 3, 573–584.
10. Sternberg, R. J. (1977). Intelligence, information processing, and analogical reasoning: The componential analysis of human abilities. Hillsdale, NJ: Erlbaum.
11. Sternberg, R. J. (1983). Components of human intelligence. Cogni- tion, 15, 1–48.
12. Sternberg, R. J. (1980a). The development of linear syllogistic rea- soning. Journal of Experimental Child Psychology, 29, 340–356.
13. Sternberg, R. J., & Nigro, G. (1980). Developmental patterns in the solution of verbal analogies. Child Development, 51, 27–38.
14. Sternberg, R. J., & Rifkin, B. (1979). The development of analogical reasoning processes. Journal of Experimental Child Psychology, 27, 195–232.
15. Sternberg, R. J., & Okagaki, L. (1989). Continuity and discontinuity in intellectual development are not a matter of ‘either–or’. Human Development, 32, 158–166.
16. Newell, A., & Simon, H. A. (1972). Human problem solving. Engle- wood Cliffs, NJ: Prentice-Hall.
17. Sternberg, R. J. (1984). Toward a triarchic theory of human intelli- gence. Behavioral and Brain Sciences, 7, 269–287.
18. Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York, NY: Cambridge University Press.
19. Hunt, E. (2010). Human intelligence. New York, NY: Cambridge University Press.
20. Gardner, H. (1983). Frames of mind: The theory of multiple intelli- gences. New York, NY: Basic Books.
21. Sternberg, R. J., Forsythe, G. B., Hedlund, J., Horvath, J., Snook, S., Williams, W. M., Wagner, R. K., & Grigorenko, E. L. (2000).
Child Development Perspectives, Volume 9, Number 2, 2015, Pages 106–110
Still Searching for the Zipperump-a-Zoo 109
Practical intelligence in everyday life. New York, NY: Cambridge University Press.
22. Sternberg, R. J. (1982). Natural, unnatural, and supernatural con- cepts. Cognitive Psychology, 14, 451–488.
23. Sternberg, R. J., & Lubart, T. I. (1995). Defying the crowd: Cultivat- ing creativity in a culture of conformity. New York, NY: Free Press.
24. Sternberg, R. J. (1997). Successful intelligence. New York, NY: Plume.
25. Sternberg, R. J., Torff, B., & Grigorenko, E. L. (1998). Teaching tri- archically improves school achievement. Journal of Educational Psychology, 90, 374–384.
26. Sternberg, R. J., Jarvin, L., Birney, D., Naples, A., Stemler, S., New- man, T., Otterbach, R., Randi, J., & Grigorenko, E. L. (2014). Test- ing the theory of successful intelligence in teaching grade 4 language arts, mathematics, and science. Journal of Educational Psychology, 106, 881–899.
27. Sternberg, R. J., Grigorenko, E. L., Ferrari, M., & Clinkenbeard, P. (1999). A triarchic analysis of an aptitude–treatment interaction. European Journal of Psychological Assessment, 15, 1–11.
28. Sternberg, R. J., & The Rainbow Project Collaborators. (2006). The Rainbow Project: Enhancing the SAT through assessments of ana- lytical, practical and creative skills. Intelligence, 34, 321–350.
29. Hedlund, J., Wilt, J. M., Nebel, K. R., Ashford, S. J., & Sternberg, R. J. (2006). Assessing practical intelligence in business school admissions: A supplement to the Graduate Management Admissions Test. Learning and Individual Differences, 16, 101–127.
30. Stemler, S. E., Grigorenko, E. L., Jarvin, L., & Sternberg, R. J. (2006). Using the theory of successful intelligence as a basis for augmenting AP exams in psychology and statistics. Contemporary Educational Psychology, 31, 344–376.
31. Stemler, S. E., Sternberg, R. J., Grigorenko, E. L., Jarvin, L., & Sharpes, D. K. (2009). Using the theory of successful intelligence as a framework for developing assessments in AP Physics. Contempo- rary Educational Psychology, 34, 195–209.
32. Sternberg, R. J. (2010). College admissions for the 21st century. Cambridge, MA: Harvard University Press.
33. Sternberg, R. J. (1985). Implicit theories of intelligence, creativity, and wisdom. Journal of Personality and Social Psychology, 49, 607–627.
34. Sternberg, R. J., Conway, B. E., Ketron, J. L., & Bernstein, M. (1981). People’s conceptions of intelligence. Journal of Personality and Social Psychology, 41, 37–55.
35. Sternberg, R. J. (2004). Culture and intelligence. American Psychol- ogist, 59, 325–338.
36. Sternberg, R. J., Jarvin, L., & Grigorenko, E. L. (2011). Explorations of the nature of giftedness. New York, NY: Cambridge University Press.
37. Sternberg, R. J., Nokes, K., Geissler, P. W., Prince, R., Okatcha, F., Bundy, D. A., & Grigorenko, E. L. (2001). The relationship between academic and practical intelligence: A case study in Kenya. Intelli- gence, 29, 401–418.
38. Grigorenko, E. L., Meier, E., Lipka, J., Mohatt, G., Yanez, E., & Sternberg, R. J. (2004). Academic and practical intelligence: A case study of the Yup’ik in Alaska. Learning and Individual Differences, 14, 183–207.
39. Sternberg, R. J. (1985b). Human intelligence: The model is the mes- sage. Science, 230, 1111–1118.
40. Sternberg, R. J. (1990). Metaphors of mind: Conceptions of the nature of intelligence. New York, NY: Cambridge University Press.
41. Okagaki, L., & Sternberg, R. J. (1993). Parental beliefs and chil- dren’s school performance. Child Development, 64, 36–56.
42. Sternberg, R. J. (2005). Foolishness. In R. J. Sternberg & J. Jordan (Eds.), Handbook of wisdom: Psychological perspectives (pp. 331– 352). New York, NY: Cambridge University Press.
43. Karelitz, T. M., Jarvin, L., & Sternberg, R. J. (2010). The meaning of wisdom and its development throughout life. In W. Overton (Ed.), Handbook of lifespan human development (pp. 837–881). New York, NY: Wiley.
44. Sternberg, R. J. (2003). Wisdom, intelligence, and creativity synthe- sized. New York, NY: Cambridge University Press.
45. Sternberg, R. J. (2012). A model for ethical reasoning. Review of General Psychology, 16, 319–326.
46. Stanovich, K. E. (2009). What intelligence tests miss: The psychology of rational thought. New Haven, CT: Yale University Press.
47. Sternberg, R. J. (1999). Intelligence as developing expertise. Con- temporary Educational Psychology, 24, 359–375.
48. Sternberg, R. J. (2014b). Intelligence as trait—and state? Journal of Intelligence, 2, 4–5.
49. Jensen, A. R. (1998). The g factor. Westport, CT: Praeger. 50. Ree, M. J., & Earles, J. A. (1992). Intelligence is the best predictor
of job performance. Current Directions in Psychological Science, 1, 86–89.
51. Schmidt, F. L., & Hunter, J. E. (1992). Development of a causal model of processes determining job performance. Current Directions in Psychological Science, 1, 89–92.
52. Carroll, J. B. (1993). Human cognitive abilities: A survey of factor- analytic studies. New York, NY: Cambridge University Press.
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110 Robert J. Sternberg
