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Exceptional Cognitive Ability: The Phenotype

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Abstract

Characterizing the outcomes related to the phenotype of exceptional cognitive abilities has been feasible in recent years due to the availability of large samples of intellectually precocious adolescents identified by modern talent searches that have been followed-up longitudinally over multiple decades. The level and pattern of cognitive abilities, even among participants within the top 1% of general intellectual ability, are related to differential developmental trajectories and important life accomplishments: The likelihood of earning a doctorate, earning exceptional compensation, publishing novels, securing patents, and earning tenure at a top university (and the academic disciplines within which tenure is most likely to occur) all vary as a function of individual differences in cognitive abilities assessed decades earlier. Individual differences that distinguish the able (top 1 in 100) from the exceptionally able (top 1 in 10,000) during early adolescence matter in life, and, given the heritability of general intelligence, they suggest that understanding the genetic and environmental origins of exceptional abilities should be a high priority for behavior genetic research, especially because the results for extreme groups could differ from the rest of the population. In addition to enhancing our understanding of the etiology of general intelligence at the extreme, such inquiry may also reveal fundamental determinants of specific abilities, like mathematical versus verbal reasoning, and the distinctive phenotypes that contrasting ability patterns are most likely to eventuate in at extraordinary levels.

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Notes

  1. Given the number of reports that suggest socioeconomic status (SES) influences cognitive ability measures in unknown ways, readers are referred to articles that have revealed the importance of cognitive abilities in predicting educational, occupational, and medical phenomena while controlling for SES (Gottfredson2004; Lubinski and Humphreys1992; Murray1998; Sackett et al.2009).

  2. This illustrates a common finding. Namely, educational interventions that work increase the mean level of achievement and expand the variance (Ceci and Papierno2005; Gagne2005; Jensen,1991, p. 178; Kenny1975; Robinson et al.1996; Robinson et al.1997). When all students are provided with opportunities to learn at their desired rate, those who begin with more ability typically learn more from such opportunities. This nonlinearity between learning-potential (“ability”) and learning-achievements (“knowledge”) is brought into sharper focus by considering the full range of ability: Students with developmental delays assimilate much less than typically developing students even in the best of conditions, yet this fanning out in achievement is observed throughout the ability spectrum and within these populations as well (Fuchs et al.1999; Fuchs et al.2001). That opportunities for optimal growth expand individual differences in achievement has been periodically discussed for decades (Seashore1922; Pressey1946,1955; Thorndike1911; Thurstone1948; among others), yet it is conspicuously absent in many modern treatments [two excellent exceptions, however, are Ceci and Papierno (2005) and Gagne (2005)]. Ceci and Papierno (2005, p.149) nicely depict this phenomenon by subtitling their treatment: “When the ‘have nots’ gain but the ‘haves’ gain even more.” Stanford University’s distinguished educational psychologist Elliot Eisner (1999, p.660), drew on this principle as a metric for evaluating schools: “The good school, as I have suggested, does not diminish individual differences; it increases them. It raises the mean and increases the variance.”

References

  • Benbow CP (1992) Academic achievement in math and science between ages 13 and 23: are there differences in the top one percent of ability? J Educ Psychol 84:51–61. doi:10.1037/0022-0663.84.1.51

    Article  Google Scholar 

  • Benbow CP, Stanley JC (1996) Inequity in equity: how “equity” can lead to inequity for high-potential students. Psychol Public Policy Law 2:249–292. doi:10.1037/1076-8971.2.2.249

    Article  Google Scholar 

  • Benbow CP, Lubinski D, Shea DL, Eftekhari-Sanjani H (2000) Sex differences in mathematical reasoning ability: their status 20 years later. Psychol Sci 11:474–480. doi:10.1111/1467-9280.00291

    Article PubMed  Google Scholar 

  • Bleske-Rechek A, Lubinski D, Benbow CP (2004) Meeting the educational needs of special populations: advanced placement’s role in developing exceptional human capital. Psychol Sci 15:217–224. doi:10.1111/j.0956-7976.2004.00655.x

    Article PubMed  Google Scholar 

  • Carroll JB (1993) Human cognitive abilities: a survey of factor-analytic studies. Cambridge University Press, Cambridge

    Google Scholar 

  • Ceci SJ, Papierno PB (2005) The rhetoric and reality of gap closing: when the “have nots” gain but the “haves” gain even more. Am Psychol 60:149–160. doi:10.1037/0003-066X.60.2.149

    Article PubMed  Google Scholar 

  • Colangelo N, Assouline SG, Gross MUM (eds) (2004) A nation deceived: how schools hold back America’s brightest students. University of Iowa, Iowa City

    Google Scholar 

  • Corno L, Cronbach LJ et al (eds) (2002) Remaking the concept of aptitude: extending the legacy of Richard E. Snow. Earlbaum, Mahwah

    Google Scholar 

  • Eisner EW (1999) The use and limits of performance assessment. Phi Delta Kappan 80:658–660

    Google Scholar 

  • Ericsson KA et al (eds) (2006) The Cambridge handbook of expertise and expert performance. Cambridge University Press, Cambridge

    Google Scholar 

  • Eysenck HJ (1995) Genius: the natural history of creativity. Cambridge University Press, Cambridge

    Google Scholar 

  • Frey MC, Detterman DK (2004) Scholastic assessment org?: The relationship between the scholastic assessment test and general cognitive ability. Psychol Sci 15:373–378. doi:10.1111/j.0956-7976.2004.00687.x

    Article PubMed  Google Scholar 

  • Fuchs LS, Fuchs D, Karns K, Hamlett CL, Katzaroff M (1999) Mathematics performance assessment in the classroom: effects on teacher planning and student learning. Am Educ Res J 36:609–646

    Google Scholar 

  • Fuchs D, Fuchs LS, Thompson A, Al Otaiba S, Yen L, Yang N, Braun M, O’Connor RE (2001) Is reading important in reading-readiness programs? A randomized field trial with teachers as program implementers. J Educ Psychol 93:251–267. doi:10.1037/0022-0663.93.2.251

    Article  Google Scholar 

  • Gagne F (2005) From noncompetence to exceptional talent: exploring the range of academic achievement within and between grade levels. Gift Child Q 49:139–153. doi:10.1177/001698620504900204

    Article  Google Scholar 

  • Gladwell M (2008) Outliers: the story of success. Little Brown, New York

    Google Scholar 

  • Gohm CL, Humphreys LG, Yao G (1998) Underachievement among spatially gifted students. Am Educ Res J 35:515–531

    Google Scholar 

  • Gottfredson LS (1997) Intelligence and social policy (special issue). Intelligence 24:(#1 whole issue)

  • Gottfredson LS (2003) The challenge and promise of cognitive career assessment. J Career Assess 11:115–135. doi:10.1177/1069072703011002001

    Article  Google Scholar 

  • Gottfredson LS (2004) Intelligence: is it the epidemiologists’ elusive “fundamental cause” of social class inequalities in health. J Pers Soc Psychol 86:174–199. doi:10.1037/0022-3514.86.1.174

    Article PubMed  Google Scholar 

  • Haier RJ (2009) Neuro-intelligence: neuro-metrics and the next phase of brain imaging studies. Intelligence (in press)

  • Jensen AR (1991) Spearman’s g and the problem of educational equality. Oxford Rev Educ 17:169–187

    Article  Google Scholar 

  • Jensen AJ (1996) Giftedness and genius: crucial differences. In: Benbow CP, Lubinski D (eds) Intellectual talent: psychometric and social issues. Johns Hopkins University Press, Baltimore, pp 393–411

    Google Scholar 

  • Jensen AR (1998) The g factor. Praeger, Westport

    Google Scholar 

  • Jung R, Haier RJ (2007) The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav Brain Sci 30:135–154. doi:10.1017/S0140525X07001185

    Article PubMed  Google Scholar 

  • Keating DP, Stanley JC (1972) Extreme measures for the exceptionally gifted in mathematics and science. Educ Res 1:3–7

    Google Scholar 

  • Kenny DA (1975) A quasi-experimental approach to assessing treatment effects in the nonequivalent control group design. Psychol Bull 82:345–362. doi:10.1037/0033-2909.82.3.345

    Article  Google Scholar 

  • Kuncel NR, Hezlett SA (2007) Standardized tests predict graduate student success. Science 315:1080–1081. doi:10.1126/science.1136618

    Article PubMed  Google Scholar 

  • Kuncel NR, Hezlett SA, Ones DS (2001) A comprehensive meta-analysis of the predictive validity of the graduate record examinations: implications for graduate student selection and performance. Psychol Bull 127:162–181. doi:10.1037/0033-2909.127.1.162

    Article PubMed  Google Scholar 

  • Lubinski D (2004) Introduction to the special section on cognitive abilities: 100 years after Spearman’s (1904) “‘General intelligence’, objectively determined and measured. J Pers Soc Psychol 86:96–111. doi:10.1037/0022-3514.86.1.96

    Article PubMed  Google Scholar 

  • Lubinski D, Benbow CP (2006) Study of mathematically precocious youth after 35 years: uncovering antecedents for the development of math-science expertise. Perspect Psychol Sci 1:316–345

    Google Scholar 

  • Lubinski D, Humphreys LG (1992) Some bodily and medical correlates of mathematical giftedness and commensurate levels of socioeconomic status. Intelligence 16:99–115. doi:10.1016/0160-2896(92)90027-O

    Article  Google Scholar 

  • Lubinski D, Humphreys LG (1997) Incorporating general intelligence into epidemiology and the social sciences. Intelligence 24:159–201. doi:10.1016/S0160-2896(97)90016-7

    Article  Google Scholar 

  • Lubinski D, Benbow CP, Shea DL, Eftekhari-Sanjani H, Halvorson MBJ (2001a) Men and women at promise for scientific excellence: similarity not dissimilarity. Psychol Sci 12:309–317

    Article PubMed  Google Scholar 

  • Lubinski D, Webb RM, Morelock MJ, Benbow CP (2001b) Top 1 in 10,000: a 10-year follow-up of the profoundly gifted. J Appl Psychol 86:718–729. doi:10.1037/0021-9010.86.4.718

    Article PubMed  Google Scholar 

  • Lubinski D, Benbow CP, Webb RM, Bleske-Rechek A (2006) Tracking exceptional human capital over two decades. Psychol Sci 17:194–199. doi:10.1111/j.1467-9280.2006.01685.x

    Article PubMed  Google Scholar 

  • Muratori MC, Stanley JC, Gross MUM, Ng L, Tao T, Ng J, Tao B (2006) Insights from SMPY’s greatest former prodigies: Drs. Terence (“Terry”) Tao and Lenhard (“Lenny”) Ng reflect on their talent development. Gift Child Q 50:307–324. doi:10.1177/001698620605000404

    Article  Google Scholar 

  • Murray C (1998) Income inequality, and IQ. American Enterprise Institute, Washington

    Google Scholar 

  • Park G, Lubinski D, Benbow CP (2007) Contrasting intellectual patterns for creativity in the arts and sciences: tracking intellectually precocious youth over 25 years. Psychol Sci 18:948–952. doi:10.1111/j.1467-9280.2007.02007.x

    Article PubMed  Google Scholar 

  • Park G, Lubinski D, Benbow CP (2008) Ability differences among people who have commensurate degrees matter for scientific creativity. Psychol Sci 19:957–961. doi:10.1111/j.1467-9280.2008.02182.x

    Article PubMed  Google Scholar 

  • Plomin R (2003) Behavior genetics in the postgenomic era. American Psychological Association, Washington

    Book  Google Scholar 

  • Plomin R, Kovas Y (2005) Generalist genes and learning disabilities. Psychol Bull 131:592–617. doi:10.1037/0033-2909.131.4.592

    Article PubMed  Google Scholar 

  • Pressey SL (1946) Acceleration: disgrace or challenge? Science 104:215–219. doi:10.1126/science.104.2697.215

    Article PubMed  Google Scholar 

  • Pressey SL (1955) Concerning the nature and nurture of genius. Sci Mon 81:123–129

    Google Scholar 

  • Putallaz MBJ et al (2005) The Duke talent identification program. High Abil Stud 16:41–54. doi:10.1080/13598130500115221

    Article  Google Scholar 

  • Robinson NM, Abbott RD, Berninger VW, Busse J (1996) The structure of abilities in mathematically precocious young children: gender similarities and differences. J Educ Psychol 88:341–352. doi:10.1037/0022-0663.88.2.341

    Article  Google Scholar 

  • Robinson NM, Abbott RD, Berninger VW, Busse J, Mukhopadhyah S (1997) Developmental changes in mathematically precocious young children. Gift Child Q 41:145–158. doi:10.1177/001698629704100404

    Article  Google Scholar 

  • Sackett PR, Kuncel NR, Arneson JJ, Cooper SR, Waters SD (2009) Does socioeconomic status explain the relationship between admissions tests and post-secondary academic performance? Psychol Bull 135:1–22. doi:10.1037/a0013978

    Article PubMed  Google Scholar 

  • Schmidt FL, Hunter JE (1998) The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings. Psychol Bull 124:262–274. doi:10.1037/0033-2909.124.2.262

    Article  Google Scholar 

  • Seashore CE (1922) The gifted student and research. Science 56:641–648. doi:10.1126/science.56.1458.641

    Article PubMed  Google Scholar 

  • Shea DL, Lubinski D, Benbow CP (2001) Importance of assessing spatial ability in intellectually talented young adolescents: a 20-year longitudinal study. J Educ Psychol 93:604–614. doi:10.1037/0022-0663.93.3.604

    Article  Google Scholar 

  • Simonton DK (1994) Greatness: who makes history and why. Guilford Press, NY

    Google Scholar 

  • Snow RE, Lohman DF (1989) Implications of cognitive psychology for educational measurement. In: Linn RL (ed) Educational measurement, 3rd edn. Collier, New York, pp 263–331

    Google Scholar 

  • Snow RE, Corno L, Jackson DIII (1996) Individual differences in affective and conative functions. In: Berliner DC, Calfee RC (eds) Handbook of educational psychology. MacMillan, New York, pp 243–310

    Google Scholar 

  • Spearman C (1927) The abilities of man: their nature and measurement. Macmillan, New York

    Google Scholar 

  • Spearman C, Jones L (1950) Human ability. Macmillan, London

    Google Scholar 

  • Stanley JC (1996) SMPY in the beginning. In: Benbow CP, Lubinski D (eds) Intellectual talent. Johns Hopkins University Press, Baltimore, pp 225–235

    Google Scholar 

  • Stanley JC (2000) Helping students learn only what they don’t already know. Psychol Public Policy Law 6:216–222. doi:10.1037/1076-8971.6.1.216

    Article  Google Scholar 

  • Terman LM (1925) Genetic studies of genius: vol. 1. Stanford University Press, Stanford

    Google Scholar 

  • Terman LM (1954) The discovery and encouragement of exceptional talent. Am Psychol 9:221–230. doi:10.1037/h0060516

    Article  Google Scholar 

  • Thorndike EL (1911) Individuality. Houghton & Miffin, Co, New York

    Google Scholar 

  • Thurstone LL (1948) Psychological implications of factor analysis. Am Psychol 3:402–408. doi:10.1037/h0058069

    Article PubMed  Google Scholar 

  • Wai J, Lubinski D, Benbow CP (2005) Creativity and occupational accomplishments among intellectually precocious youth: an age 13 to age 33 longitudinal study. J Educ Psychol 97:484–492

    Article  Google Scholar 

  • Wai J, Lubinski D, Benbow CP (2009) Spatial ability for STEM domains: aligning over fifty years of cumulative psychological knowledge solidifies its importance. J Educ Psychol 101

  • Webb RM, Lubinski D, Benbow CP (2002) Mathematically facile adolescents with math-science aspirations: new perspectives on their educational and vocational development. J Educ Psychol 94:785–794. doi:10.1037/0022-0663.94.4.785

    Article  Google Scholar 

  • Webb RM, Lubinski D, Benbow CP (2007) Spatial ability: a neglected dimension in talent searches for intellectually precocious youth. J Educ Psychol 99:397–420. doi:10.1037/0022-0663.99.2.397

    Article  Google Scholar 

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Acknowledgments

Support for this article was provided by a Research and Training Grant from the Templeton Foundation and National Institute of Child Health and Development Grant P30 HD 15051 to the Vanderbilt Kennedy Center for Research on Human Development. Earlier versions of this article benefited from comments from Kimberley Ferriman, Gregory Park, and Jonathan Wai.

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Authors and Affiliations

  1. Department of Psychology and Human Development, Vanderbilt University, 0552 GPC, 230 Appleton Place, Nashville, TN, 37203, USA

    David Lubinski

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  1. David Lubinski

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Correspondence toDavid Lubinski.

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Edited by Robert Plomin.

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