SMPY (Link Bibliography)

SMPY links:


  2. Regression

  3. Hunter


  5. 2021-brown.pdf: ⁠, Matt I. Brown, Jonathan Wai, Christopher F. Chabris (2021-03-08; iq):

    Despite a long-standing expert consensus about the importance of cognitive ability for life outcomes, contrary views continue to proliferate in scholarly and popular literature. This divergence of beliefs presents an obstacle for evidence-based policymaking and decision-making in a variety of settings. One commonly held idea is that greater cognitive ability does not matter or is actually harmful beyond a certain point (sometimes stated as > 100 or 120 IQ points). We empirically tested these notions using data from four longitudinal, representative cohort studies comprising 48,558 participants in the United States and United Kingdom from 1957 to the present. We found that ability measured in youth has a positive association with most occupational, educational, health, and social outcomes later in life. Most effects were characterized by a moderate to strong linear trend or a practically null effect (mean R2 range = 0.002–.256). Nearly all nonlinear effects were practically insignificant in magnitude (mean incremental R2 = 0.001) or were not replicated across cohorts or survey waves. We found no support for any downside to higher ability and no evidence for a threshold beyond which greater scores cease to be beneficial. Thus, greater cognitive ability is generally advantageous—and virtually never detrimental.

  6. #kell-et-al-2017


  8. #university-of-north-texas-julian-c-stanley-archival-materials-19861989





  13. 2003-gross.pdf: “Nowicka, R”⁠, Carmen Robinson

  14. 1951-stanley.pdf

  15. 1972-keating.pdf

  16. 1973-stanley.pdf

  17. 1974-hogan.pdf




  21. 1974-stanley-mathematicaltalentdiscoverydescriptiondevelopment.pdf

  22. 1975-hogan.pdf

  23. 1975-keating.pdf

  24. 1975-solano.pdf


  26. 1976-stanley.pdf: “Youths Who Reason Extremely Well Mathematically: Smpy's Accelerative Approach”⁠, Julian C. Stanley

  27. 1976-george.pdf: “Accelerating Mathematics Instruction for the Mathematically Talented”⁠, William C. George

  28. 1976-solano.pdf: “College Courses and Educational Facilitation of the Gifted”⁠, Cecilia H. Solano, William C. George

  29. 1976-stanley-2.pdf

  30. 1976-stanley-4.pdf

  31. 1976-fox.pdf

  32. 1976-cohn.pdf: “Individualizing Science Curricula for the Gifted”⁠, Sanford J. Cohn


  34. 1976-hogan.pdf

  35. 1976-fox-2.pdf

  36. 1976-fox-3.pdf

  37. 1976-smith.pdf: “My Introduction To Computing”⁠, Daniel W. Smith

  38. 1976-montour.pdf: “Merrill Kenneth Wolf: a Bachelor's Degree At 14”⁠, Kathleen Montour

  39. 1976-keating-intellectualtalentresearchanddevelopment.pdf

  40. 1976-solano-2.pdf: “Teacher and Pupil Stereotypes of Gifted Boys and Girls”⁠, Cecelia H. Solano

  41. 1976-stanley-3.pdf

  42. 1976-stanley-5.pdf

  43. 1977-george.pdf: “Parental Support - Time and Energ”⁠, W. C. George

  44. 1977-stanley.pdf

  45. 1977-stanley-2.pdf: “Books Tell The SMPY Story⁠, J. C. Stanley, S. J. Cohn, W. C. George

  46. 1977-stanley-thegiftedandthecreative.pdf

  47. 1979-davis.pdf

  48. 1977-stanley-3.pdf

  49. 1977-fox.pdf

  50. 1977-getzels.pdf

  51. 1978-stanley-educationalprogramsandintellectualprodigies.pdf: “Educational Programs and Intellectual Prodigies”⁠, Julian C. Stanley, William C. George, Cecilia H. Solano

  52. #montour-1976

  53. 1985-stanley-3.pdf




  57. 1978-albert.pdf

  58. 1978-cohn.pdf: “Cognitive Characteristics of the Top-Scoring Third of the 1976 Talent Search Contestants”⁠, Sanford J. Cohn

  59. 1978-mills.pdf: “Is Sex Role Related To Intellectual Abilities?”⁠, Carol Mills

  60. 1978-stanley-2.pdf

  61. 1978-stanley-3.pdf

  62. 1978-stanley.pdf: “Now We Are Six: The Ever-Expanding SMPY⁠, Julian C. Stanley, William C. George

  63. 1979-cohn-3.pdf: “Searching for Scientifically Talented Youth?”⁠, Sanford J. Cohn

  64. 1979-durden.pdf

  65. 1979-eisenberg.pdf: “Early Entrance to College: The Johns Hopkins Experience; Study of Mathematically Precocious Youth (SMPY), The Johns Hopkins University⁠, Ann R. Eisenberg, William C. George

  66. 1979-george-2.pdf: “The Study of Mathematically Precocious Youth”⁠, W. C. George, J. C. Stanley

  67. 1979-fox.pdf

  68. 1979-fox-2.pdf

  69. 1979-george.pdf: ⁠, William C. George (1979-10-01; iq  /​ ​​ ​smpy):

    Using the empirically based evidence that has resulted from the previous five Talent Searches of the Study of Mathematically Precocious Youth, the article develops the rationale and success behind the talent-search concept as a useful strategy for identifying the intellectually gifted. Its practicality as a model is further demonstrated through the systematic curricular programming that has resulted at school-district levels after students have been identified as talented in a specific aptitude area. The identification issue is discussed as it pertains to efficiency and effectiveness related to cost, predictive validity, and feasibility.

  70. 1979-george-educatingthegifted.pdf

  71. 1979-cohn.pdf

  72. 1979-daurio.pdf

  73. 1979-cohn-2.pdf

  74. 1979-laycock-giftedchildren.pdf

  75. 1979-mills.pdf

  76. 1979-stanley.pdf: “The Future of Education”⁠, Julian C. Stanley, William C. George

  77. 1980-albert.pdf: ⁠, Robert S. Albert (1980-10-01; iq  /​ ​​ ​smpy):

    In an effort to explore some of the possible early-experiential and family variables involved in the achievement of eminence we have developed a model of cognitive and personality development and have undertaken a longitudinal study of two distinct groups of exceptionally gifted boys and their families. In this report, early similarities and differences between two groups of exceptionally gifted boys and their families will be explored. Methodology: This is a longitudinal study of two samples of healthy, exceptionally gifted boys and their families. One group consisted of 26 of the highest scorers in the 1976 Math Talent Search conducted by Julian Stanley (1974, 1977); the second group of 26 boys living in southern California were selected only on the basis of IQ’s of 150 or higher.

    …Factors included for study were parents’ and grand-parents’ educational attainment, parents’ and subjects’ birth-order, subjects’ and parents’ creative potential, and subjects’ cognitive giftedness.

    • Both samples were well-educated and had attained statistically-significantly more formal education than the national norms.
    • The birth-orders of the two samples are what one would expect from the literature of gifted children and they are not statistically-significantly different from one another.
    • A surprisingly remarkable similarity exists between the two samples of cognitively gifted boys, although they were selected a year apart, a continent apart, and on the basis of distinctly different test performances. We expected them to perform better on the figural and the math/​​​​​science subtests of the Wallach-Kogan and BIC measures, respectively, and the high-IQ sample to perform statistically-significantly better on the verbal and the art/​​​​​writing subtests. Instead, the differences between the samples are slight and not statistically-significant. At minimum, these results suggest that the two samples are each made of highly talented, cognitively gifted boys in the ares of art/​​​​​writing and math/​​​​​science as measured by standard instruments. Second, these results further indicate the versatility that accompanies exceptional giftedness…Table 1 shows that the parents of both groups of exceptionally gifted boys are themselves exceptionally creative. Parents of both groups outperformed Duke University subjects. Furthermore, the parents definitely showed more creative potential than their children. It is the parents of the high-IQ boys who have the highest creativity scores of all.

    …We believe the results of the present study and those of Milgram et al. show that cognitive giftedness and creative giftedness are very much related to one another and may be manifestations of the same complex, multi-faceted abilities. Therefore, it should not surprise us that there is a large degree of family cognitive and creative similarity.

  78. #albert-1994

  79. 1980-becker.pdf

  80. 1980-benbow.pdf

  81. 1980-benbow-2.pdf

  82. 1980-fox-womenandthemathematicalmystique.pdf

  83. 1980-fox.pdf

  84. 1980-brody.pdf

  85. 1980-mcclain.pdf: “German for Verbally Gifted Youngsters at Hopkins: The First Year”⁠, William H. McClain, William G. Durden

  86. 1980-mezynski.pdf

  87. 1980-stanley.pdf

  88. 1980-stanley-2.pdf: ⁠, Julian C. Stanley (1980; iq  /​ ​​ ​smpy):

    For 9 years personnel of the Study of Mathematically Precocious Youth (SMPY) at Johns Hopkins have found thousands of youths, chiefly 7th-graders, who reason extremely well mathematically. SMPY strives in various ways to help these students proceed considerably faster and better in mathematics and related subjects than is usually permitted or encouraged. Its work is offered as an example of important problems that, in the judgment of the author, educational psychologists should attack vigorously.

    SMPY’s 4-D model is described, which emphasizes educational acceleration of youths who are highly able and eager to move ahead quickly.

  89. 1981-house.pdf

  90. 1981-fox.pdf

  91. 1981-stanley.pdf

  92. 1981-bartkovich.pdf

  93. 1981-benbow.pdf: “Development of Superior Mathematical Ability During Adolescence”⁠, Lena Camilla Persson Benbow

  94. 1982-benbow.pdf

  95. 1982-benbow-2.pdf: ⁠, Camilla Persson Benbow, Julian C. Stanley (1982-01-01; iq  /​ ​​ ​smpy):

    Between 1972 and 1974 the Study of Mathematically Precocious Youth (SMPY) identified over 2,000 7th and 8th graders who scored as well as a national sample of 11th and 12th grade females on the College Board’s Scholastic Aptitude Test (SAT) Mathematics or Verbal tests. A substantial sex difference in mathematical reasoning ability was found (Benbow & Stanley, 1980b, 1981). The consequences and development of this sex difference over the following 5 years were investigated longitudinally. Over 91 percent (1,996 out of 2,188 SMPY students) participated. This study established that the sex difference persisted over several years and was related to subsequent sex differences in mathematics achievement. The sex difference in mathematics did not reflect differential mathematics course taking. The abilities of males developed more rapidly than those of females. Sex differences favoring males were found in participation in mathematics, performance on the SAT-M, and taking of and performance on mathematics achievement and Advanced Placement Program examinations. SMPY females received better grades in their mathematics courses than SMPY males did. Few significant sex differences were found in attitudes toward mathematics.

  96. 1982-moore.pdf: “The Joys and Challenges in Raising a Gifted Child”⁠, Nancy Delano Moore

  97. 1982-sawyer.pdf: “Duke University's Talent Identification Program”⁠, Robert N. Sawyer, Lynn M. Daggett

  98. 1982-stanley.pdf

  99. 1983-benbow-academicprecocity.pdf

  100. 1983-stanley-5.pdf

  101. 1983-benbow-6.pdf

  102. 1983-michael.pdf

  103. 1983-benbow-7.pdf

  104. 1983-lunny.pdf

  105. 1983-mezynski.pdf

  106. 1983-fox.pdf

  107. 1983-robinson.pdf

  108. 1983-pollins.pdf

  109. 1983-vantasselbaska.pdf

  110. 1983-feldhusen.pdf

  111. 1983-benbow-8.pdf

  112. 1983-benbow-2.pdf

  113. 1983-benbow-3.pdf

  114. 1983-benbow-9.pdf: “Opening Doors for the Gifted: A flexible curriculum will provide valuable learning options for gifted students, according to directors of the Study of Mathematically Precocious Youth at the Johns Hopkins University”⁠, Camilla Persson Benbow, Julian C. Stanley

  115. 1983-benbow-4.pdf

  116. 1983-benbow-5.pdf

  117. 1985-vining.pdf

  118. 1985-gleser.pdf

  119. 1983-stanley-4.pdf

  120. 1983-stanley-6.pdf


  122. 1983-stanley-2.pdf

  123. 1983-stanley-3.pdf

  124. 1983-tursman.pdf: “Fast-Paced Classes: Challenging Gifted Students”⁠, Cindy Tursman

  125. 1984-benbow.pdf

  126. 1984-gowan.pdf

  127. 1984-holmes.pdf

  128. #time-1977

  129. 1984-reynolds-writinginstructionforverballytalentedyouthjhumodel.pdf: “Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”⁠, Reynolds, Ben;Kopelke, Kendra;Durden, William G

  130. 1987-wood.pdf: “Media Review: Books: Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”⁠, Frank H. Wood, Trish Bransky

  131. 1984-reynolds-writinginstructionforverballytalentedyouthjhumodel.pdf#page=13: “Writing Instruction for Verbally Talented Youth: The Johns Hopkins Model”⁠, Reynolds, Ben;Kopelke, Kendra;Durden, William G

  132. 1984-stanley.pdf

  133. 1984-stanley-2.pdf: “The exceptionally talented”⁠, Julian C. Stanley

  134. 1985-durden.pdf

  135. 1985-stanley.pdf

  136. 1985-stanley-2.pdf: “A baker's dozen of years applying all four aspects of the Study of Mathematically Precocious Youth (SMPY)⁠, Julian C. Stanley


  138. 1986-stanley.pdf

  139. 1986-benbow-2.pdf: “Chapter 1: SMPY's Model for Teaching Mathematically Precocious Students⁠, Camilla Persson Benbow

  140. 1986-renzulli-systemsandmodelsforprogramsforgiftedtalented.pdf: “Systems and Models for Developing Programs for the Gifted and Talented”⁠, Joseph S. Renzulli

  141. 1986-benbow.pdf

  142. 1986-brody.pdf

  143. 1986-stanley-2.pdf: “SAT-M scores of highly selected students in Shanghai tested when less than 13 years old⁠, Julian C. Stanley, Jia-fen Huang, Xue-min Zu










  153. 1987-benbow.pdf

  154. 1987-benbow-2.pdf: “Extreme Mathematical Talent: A Hormonally Induced Ability?”⁠, Camilla Persson Benbow, Robert Michael Benbow

  155. 1987-brody.pdf

  156. 1987-fox.pdf

  157. 1987-stanley.pdf

  158. 1987-stanley-2.pdf

  159. #brody-muratori-2014

  160. 1987-stanley-3.pdf

  161. 1987-stanley-4.pdf



  164. 1988-benbow.pdf: “Sex differences in mathematical reasoning ability in intellectually talented preadolescents: Their nature, effects, and possible causes”⁠, Camilla Persson Benbow

  165. 1993-thomas.pdf: “A theory explaining sex differences in high mathematical ability has been around for some time”⁠, Hoben Thomas

  166. 1988-stanley.pdf

  167. 1989-anonymous.pdf

  168. #putallaz-et-al-2005

  169. 1989-stanley.pdf

  170. 1989-stanley-2.pdf

  171. 1989-stanley-3.pdf: “Most Fare Better”⁠, Julian C. Stanley

  172. 1989-lindblad.pdf: “On Being a Misfit”⁠, Jeanette D. Lindblad

  173. 1990-benbow-3.pdf

  174. 1990-benbow-2.pdf

  175. 1985-gagne.pdf

  176. 1990-dark.pdf

  177. 1990-dauber.pdf

  178. 1990-lubinski.pdf

  179. 1990-lupkowski.pdf: “Applying: A Mentor Model: For Young Mathematically Talented Students”⁠, Ann E. Lupkowski, Susan G. Assouline, Julian C. Stanley

  180. 1990-lynch.pdf

  181. 1990-richardson.pdf

  182. 1990-stanley-2.pdf: ⁠, Julian C. Stanley (1990; iq  /​ ​​ ​smpy):

    (1886–1939) pioneered in above age-and grade-level testing of boys and girls in the New York City area whose IQs were extremely high.

    Her deep insights about measuring general and special abilities led to numerous current academic activities on behalf of intellectually highly talented young persons, especially including above-level curricula for them.

  183. 1990-benbow.pdf

  184. 1990-stanley.pdf: “Eight Considerations for Mathematically Talented Youth”⁠, Julian Stanley, Ann E. Lupkowski, Susan G. Assouline

  185. 1991-benbow.pdf

  186. 1991-stanley.pdf

  187. 1991-stanley-2.pdf

  188. 1991-stanley-3.pdf: “Tribute to Halbert B. Robinson (1925-1981)”⁠, Julian C. Stanley

  189. 1991-swiatek.pdf

  190. 1991-swiatek-2.pdf

  191. 1992-brody.pdf

  192. 1994-heller-competenceandresponsibility3rdconference.pdf: “Competence and Responsibility: The Third European Conference of The European Council for High Ability held in Munich (Germany), October 11–14, 1992; Volume 2: Proceedings of the Conference”⁠, Kurt A., Heller und Ernst A., Hany

  193. 1992-benbow.pdf

  194. 1992-benbow-2.pdf

  195. 1992-kirschenbaum.pdf: “An Interview with Julian C. Stanley”⁠, Robert J. Kirschenbaum

  196. 1992-lubinski.pdf

  197. 1992-lubinski-2.pdf

  198. 1992-pyryt.pdf

  199. 1992-stanley.pdf

  200. 1992-stanley-2.pdf

  201. 1993-benbow.pdf: “Psychological profiles of the mathematically talented: some sex differences and evidence supporting their biological basis”⁠, Camilla Persson Benbow, David Lubinski

  202. 1993-benbow-2.pdf: “Consequences of Gender Differences in Mathematical Reasoning Ability and Some Biological Linkages”⁠, C. P. Benbow, D. Lubinski

  203. 1993-bock-theoriginanddevelopmentofhighability.pdf: “The Origins and Development of High Ability”⁠, Gregory R. Bock, Kate Ackrill, R. C. Atkinson, Robert J. Sternberg, Douglas K. Detterman, C. P. Benbow, David Lubinski, Robert Plomin, L. A. Thompson, M. J. A. Howe, J. Sloboda, J. C. Stanley, K. A. Heller, N. Colangelo, S. G. Assouline, B. Kerr, R. Huesman, D. Johnson, Howard Gardner, M. Csikszentmihalyi, I. S. Csikszentmihalyi, W. . Fowler, K. Ogston, G. Roberts-Fiati, A. Swenson, K. A. Ericsson, R. Th. Krampe, S. Heizmann, R. C. Atkinson

  204. 1993-lubinski.pdf

  205. 1993-heller-internationaldhandbookgiftednesstalent.pdf

  206. 1993-mills.pdf

  207. 1993-southern.pdf

  208. 1993-sowell.pdf: ⁠, Evelyn J. Sowell (1993-01-01; iq  /​ ​​ ​smpy):

    This paper summarizes and critiques the empirical research of the 1970s and 1980s on programs for mathematically gifted students. Much research has shown that accelerating the mathematics curriculum provides a very good program for precocious students. Organizational plans that place mathematically gifted students together for mathematics instruction also offer opportunities for these students to perform well. Although technology-based instruction also appears to provide an efficacious way of providing instruction for mathematically gifted elementary students, this method should be examined further with older students and in long-term studies. Research with enriched curricula and non-computer-based instruction provided inconclusive evidence of efficacy for mathematically gifted students.

  209. 1993-swiatek.pdf: ⁠, Mary Ann Swiatek (1993; iq  /​ ​​ ​smpy):

    Over the past decade, several longitudinal studies pertaining to the education of intellectually gifted students were produced through the Study of Mathematically Precocious Youth (SMPY). One area that was emphasized, in keeping with SMPY’s history, is academic acceleration.

    SMPY’s studies, which consider various groups of students, methods of acceleration, and types of outcomes, support acceleration as an educational method. Their results are in keeping with the work of other authors in this area. In this article, the subjects, methods, and outcomes of SMPY’s studies are described and plans for future research are outlined.


  211. 1994-albert.pdf

  212. #albert-1980

  213. 1994-subotnik-beyondterman.pdf: ⁠, Rena F. Subotnik, Karen D. Arnold (1994; iq  /​ ​​ ​smpy):

    Beyond Terman: Contemporary Longitudinal Studies of Giftedness and Talent is an important contribution to the literature in two fields—those of gifted education and educational research. It is important for the former in terms of the insights and understandings it provides about giftedness and its nurture. It is important for the latter for its elucidations of the methodology associated with longitudinal research. The editors point out that “[the] volume presents recent collected works that demonstrate the fit between longitudinal methodology and the central issues of gifted education. Collectively, the studies investigate the early determinants of later academic and career achievement and creativity while employing varied identification practices, perspectives, theoretical orientations, and populations.”

    The studies described vary along many dimensions, including research problem, sample size and character, length of study, data collection procedures and sources, and longitudinal orientation (ie., emergent/​​​​developmental or retrospective). The studies deal with a variety of talent areas, such as academic achievement, science, technical creativity, music, creative and productive thinking, and career development. The samples include gifted and talented children, youths, and adults, both males and females. Although most of the studies deal with identified gifted/​​​​talented individuals, one is a retrospective look at the achievements of graduate students in a university-level leadership education program. Studies originating in Germany and Israel add an international flavor and, more importantly, remind us that there is good research being conducted beyond the borders of the U.S.

    As the premiere longitudinal investigation of a gifted population, the Terman study set a standard of comprehensiveness, large study sample, and societal influence that is difficult to supersede. In spite of the Terman study’s large number of research associates and rich sources of funding support, the data are still being organized for more accurate statistical analysis and examined for more challenging research questions. Further, the Genetic Studies of Genius and its more current follow-ups did not address key questions of concern in today’s social, political, and historical climate, or issues of central importance in the future. The investigations in this book have established a groundwork for answering previously unanswered questions: Are we identifying the “right” people? What are the outcomes associated with various forms of identification and intervention?

    Over the course of his long career, Terman’s perspective on high IQ as a source for potential genius changed to allow personality, interest, special abilities, and opportunity to play a growing role in adult achievement. In filling a vacuum left by Terman, this collection of contemporary studies can guide policy and program development based on the conditions and interventions that contribute to the fulfillment of talent.

  214. 1994-charlton.pdf: ⁠, Jane C. Charlton, Donald M. Marolf, Julian C. Stanley (1994; iq  /​ ​​ ​smpy):

    Too little is known about what happens, when they grow up, to youths who reason extremely well mathematically. Few tell their story to specialists in education of the gifted, either in writing or orally.

    Julian Stanley brought 2 successful former “radical accelerants” to the November 1993 annual meeting of the National Association for Gifted Children in Atlanta and also provided some information about 12 other mathematically precocious youths.

    Jane C. Charlton and Donald M. Marolf, the 2 young adults featured, told the symposium audience about themselves and answered questions. They were amazingly frank, insightful, and humorous about their lives thus far.

    Both are convinced, and are convincing, that rapid progress through school grades all the way to the Ph.D. degree is the nearly optimal way for persons like themselves to enrich their education and prepare for adulthood. All 3 speakers agreed, however, that extremely fast educational advancement might not be the ideal curriculum path for some other equally capable boys and girls.

  215. 1994-ng.pdf

  216. #muratori-et-al-2006

  217. 1994-lubinski.pdf

  218. 1995-lubinski.pdf

  219. 1995-lubinski-2.pdf: ⁠, David Lubinski, Camilla P. Benbow (1995; iq  /​ ​​ ​smpy):

    …How do we develop the talents of gifted children while maintaining equity? Based upon the long and celebrated history of individual differences research (Dawis 1992) from educational and vocational counseling (Brayfield 1950; Dawis & Lofquist 1984; Patterson 1938; Williamson 1939; 1965), we believe that optimal utilization of talent depends upon responding to individual differences in personalities. Specifically, children must be placed in educational environments that are congruent with, and build upon, their most salient abilities and preferences (Benbow & Lubinski 1994; in press; Lubinski & Benbow 1994; Lubinski, Benbow, and Sanders 1993; Stanley 1977). This approach, which is advocated by the Study of Mathematically Precocious Youth (SMPY) (Benbow & Lubinski 1994; in press; Stanley 1977), serves as the focus of this article.

    We argue and present evidence that individuals possess certain attributes that make them differentially suited for excelling, with fulfillment, in contrasting educational and vocational tracks. That is, only a limited set of learning environments is educationally optimal for anyone individual, even a gifted individual. Students, for example, put forth their best effort when they intrinsically enjoy what they are doing, and world-class achievement is most likely to develop when gifted individuals are allowed to pursue what they love at their desired pace. Indeed, learning can be optimized and achievement motivation enhanced if students are presented with tasks that are not only challenging (i.e., slightly above the level already mastered) but also personally meaningful to them (Lofquist & Dawis 1991)…

  220. 1995-sanders.pdf

  221. 1996-achter.pdf

  222. 1997-achter.pdf

  223. 1996-benbow-intellectualtalentpsychometricandsocialissues.pdf

  224. 1996-stanley.pdf

  225. 1996-benbow.pdf

  226. 1996-lubinski.pdf

  227. 1996-stanley-2.pdf

  228. #charlton-et-al-1994

  229. 1996-plotinck.pdf: “My Education”⁠, Alexander Plotinck

  230. 1996-cargain.pdf: “Entering a Women's College Two Years Early”⁠, Michele J. Cargain

  231. 1997-anonymous.pdf

  232. 1997-benbow.pdf

  233. 1997-colangelo-handbookofgiftededucation2ed.pdf




  237. 1997-petrill.pdf

  238. 1997-stanley.pdf

  239. 1998-chorney.pdf: ⁠, M. J. Chorney, K. Chorney, N. Seese, M. J. Owen, J. Daniels, P. McGuffin, L. A. Thompson, D. K. Detterman, C. Benbow, D. Lubinski, T. Eley, Robert Plomin (1998-05-01; iq  /​ ​​ ​smpy):

    (QTLs) associated with general cognitive ability (g) were investigated for several groups of children selected for very high or for average cognitive functioning.

    A DNA marker in the gene for insulin-like growth factor-2 receptor () on Chromosome 6 yielded a statistically-significantly greater frequency of a particular form of the gene (allele) in a high-g group (0.303; average IQ = 136, n = 51) than in a control group (0.156; average IQ = 103, n = 51).

    This association was replicated in an extremely-high-g group (all estimated IQs > 160, n = 52) as compared with an independent control group (average IQ = 101, n = 50), with allelic frequencies of 0.340 and 0.169, respectively. Moreover, a high-mathematics-ability group (n = 62) and a high-verbal-ability group (n = 51) yielded results that were in the same direction but only marginally statistically-significant (p = 0.06 and 0.08, respectively).

    [Warning: despite the replication, these candidate-gene hits were all false positives.]

  240. 2013-rietveld.pdf: ⁠, Cornelius A. Rietveld, Sarah E. Medland, Jaime Derringer, Jian Yang, Tõnu Esko, Nicolas W. Martin, Harm-Jan Westra, Konstantin Shakhbazov, Abdel Abdellaoui, Arpana Agrawal, Eva Albrecht, Behrooz Z. Alizadeh, Najaf Amin, John Barnard, Sebastian E. Baumeister, Kelly S. Benke, Lawrence F. Bielak, Jeffrey A. Boatman, Patricia A. Boyle, Gail Davies, Christiaan de Leeuw, Niina Eklund, Daniel S. Evans, Rudolf Ferhmann, Krista Fischer, Christian Gieger, Håkon K. Gjessing, Sara Hägg, Jennifer R. Harris, Caroline Hayward, Christina Holzapfel, Carla A. Ibrahim-Verbaas, Erik Ingelsson, Bo Jacobsson, Peter K. Joshi, Astanand Jugessur, Marika Kaakinen, Stavroula Kanoni, Juha Karjalainen, Ivana Kolcic, Kati Kristiansson, Zoltán Kutalik, Jari Lahti, Sang H. Lee, Peng Lin, Penelope A. Lind, Yongmei Liu, Kurt Lohman, Marisa Loitfelder, George McMahon, Pedro Marques Vidal, Osorio Meirelles, Lili Milani, Ronny Myhre, Marja-Liisa Nuotio, Christopher J. Oldmeadow, Katja E. Petrovic, Wouter J. Peyrot, Ozren Polašek, Lydia Quaye, Eva Reinmaa, John P. Rice, Thais S. Rizzi, Helena Schmidt, Reinhold Schmidt, Albert V. Smith, Jennifer A. Smith, Toshiko Tanaka, Antonio Terracciano, Matthijs J. H. M. van der Loos, Veronique Vitart, Henry Völzke, Jürgen Wellmann, Lei Yu, Wei Zhao, Jüri Allik, John R. Attia, Stefania Bandinelli, François Bastardot, Jonathan Beauchamp, David A. Bennett, Klaus Berger, Laura J. Bierut, Dorret I. Boomsma, Ute Bültmann, Harry Campbell, Christopher F. Chabris, Lynn Cherkas, Mina K. Chung, Francesco Cucca, Mariza de Andrade, Philip L. De Jager, Jan-Emmanuel De Neve, Ian J. Deary, George V. Dedoussis, Panos Deloukas, Maria Dimitriou, Guðný Eiríksdóttir, Martin F. Elderson, Johan G. Eriksson, David M. Evans, Jessica D. Faul, Luigi Ferrucci, Melissa E. Garcia, Henrik Grönberg, Vilmundur Guðnason, Per Hall, Juliette M. Harris, Tamara B. Harris, Nicholas D. Hastie, Andrew C. Heath, Dena G. Hernandez, Wolfgang Hoffmann, Adriaan Hofman, Rolf Holle, Elizabeth G. Holliday, Jouke-Jan Hottenga, William G. Iacono, Thomas Illig, Marjo-Riitta Järvelin, Mika Kähönen, Jaakko Kaprio, Robert M. Kirkpatrick, Matthew Kowgier, Antti Latvala, Lenore J. Launer, Debbie A. Lawlor, Terho Lehtimäki, Jingmei Li, Paul Lichtenstein, Peter Lichtner, David C. Liewald, Pamela A. Madden, Patrik K. E. Magnusson, Tomi E. Mäkinen, Marco Masala, Matt McGue, Andres Metspalu, Andreas Mielck, Michael B. Miller, Grant W. Montgomery, Sutapa Mukherjee, Dale R. Nyholt, Ben A. Oostra, Lyle J. Palmer, Aarno Palotie, Brenda W. J. H. Penninx, Markus Perola, Patricia A. Peyser, Martin Preisig, Katri Räikkönen, Olli T. Raitakari, Anu Realo, Susan M. Ring, Samuli Ripatti, Fernando Rivadeneira, Igor Rudan, Aldo Rustichini, Veikko Salomaa, Antti-Pekka Sarin, David Schlessinger, Rodney J. Scott, Harold Snieder, Beate St Pourcain, John M. Starr, Jae Hoon Sul, Ida Surakka, Rauli Svento, Alexander Teumer, The LifeLines Cohort Study, Henning Tiemeier, Frank J. A. van Rooij, David R. Van Wagoner, Erkki Vartiainen, Jorma Viikari, Peter Vollenweider, Judith M. Vonk, Gérard Waeber, David R. Weir, H.-Erich Wichmann, Elisabeth Widen, Gonneke Willemsen, James F. Wilson, Alan F. Wright, Dalton Conley, George Davey-Smith, Lude Franke, Patrick J. F. Groenen, Albert Hofman, Magnus Johannesson, Sharon L. R. Kardia, Robert F. Krueger, David Laibson, Nicholas G. Martin, Michelle N. Meyer, Danielle Posthuma, A. Roy Thurik, Nicholas J. Timpson, André G. Uitterlinden, Cornelia M. van Duijn, Peter M. Visscher, Daniel J. Benjamin, David Cesarini, Philipp D. Koellinger (2013-06-21; iq):

    A (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide statistically-significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear from all measured SNPs accounts for ≈2% of the in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our estimates can power analyses in social-science genetics.

    [A landmark study in behavioral genetics and intelligence: the first well-powered GWAS to detect genetic variants for intelligence and education which replicate out of sample and are proven to be causal in a between-sibling study.]

  241. #spain-et-al-2016

  242. ⁠, D. Zabaneh, E. Krapohl, H. A. Gaspar, C. Curtis, S. H. Lee, H. Patel, S. Newhouse, H. M. Wu, M. A. Simpson, M. Putallaz, David Lubinski, Robert Plomin, G. Breen (2017-07-04):

    We used a genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and genome-wide of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide statistical-significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was statistically-significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.


  244. 2002-hill.pdf: “PSCI13124⁠, Frame Management

  245. 2001-cardon.pdf

  246. 1998-pyryt.pdf

  247. 1998-schmidt.pdf

  248. 1999-achter.pdf


  250. 1999-norman.pdf: ⁠, Antony D. Norman, Shula G. Ramsay, Carl R. Martray, Julia L. Roberts (1999; iq  /​ ​​ ​smpy):

    This study compares 2 groups of gifted students, highly (n = 74) and moderately (n = 163) gifted, on a number of scales including self-concept, emotional autonomy, and anxiety.

    Although a measure of academic ability was used to create distinctive ability groups, the results did not support the hypotheses that highly gifted students would be more likely to display lower self-concepts and more adjustment problems than the moderately gifted group.

    These findings are examined in light of past research on differences in highly and moderately gifted students.

  251. 1999-rotigel.pdf

  252. 2000-benbow.pdf

  253. 2000-heller-internationalhandbookofgiftednessandtalent2ed.pdf

  254. 2000-lubinski.pdf

  255. 2001-lubinski-3.pdf

  256. 2000-stanley.pdf

  257. 2001-lubinski.pdf: “1247”

  258. 2001-lubinski-2.pdf

  259. 2001-plomin.pdf: “BG3106_364265”⁠, WorkStation 2

  260. 2001-shea.pdf: “Importance of assessing spatial ability in intellectually talented young adolescents: A 20-year longitudinal study”⁠, Daniel L. Shea, David Lubinski, Camilla P. Benbow

  261. 2002-clark.pdf: “Tending the special spark: Accelerated and enriched curricula for highly talented art students”⁠, Gilbert Clark, Enid Zimmerman

  262. 2002-moore.pdf: “The progress and problems of an incredibly talented sister and brother”⁠, Nancy Delano Moore

  263. 2002-webb.pdf

  264. 2003-anonymous.pdf

  265. 2003-achter.pdf

  266. 2003-kerr.pdf

  267. 2004-bleskerechek.pdf

  268. 2004-lubinski.pdf

  269. 2004-lubinski-2.pdf: “Long-term Effects of Educational Acceleration”⁠, David Lubinski


  271. #wai-2014b

  272. 2005-benbow.pdf: “A Great Man Standing With Terman and Hollingworth: Julian C. Stanley (1918-2005)”⁠, Camilla P. Benbow

  273. 2005-brody-2.pdf


  275. 2005-touron.pdf

  276. 2005-stanley.pdf

  277. 2005-ybarra.pdf

  278. 2005-barnett.pdf

  279. 2005-putallaz.pdf: ⁠, Martha Putallaz, Joy Baldwin, Hollace Selph (2005; iq  /​ ​​ ​smpy):

    The Duke University Talent Identification Program (Duke TIP) holds the distinguished position of being the first ‘transplant’ of the Center for Talented Youth (CTY) regional talent search model developed by Professor Julian Stanley at Johns Hopkins University. Duke TIP was established in 1980, one year after CTY officially began.

    This article describes the history of Duke TIP and the evolution of its talent searches and various formats of its educational programming models as well as the complementary role that research has played at Duke TIP. The success of Duke TIP stands as a truly remarkable tribute to Julian Stanley and to the robustness of the talent search model that he created at Johns Hopkins University.

    Although the specific types of programs and initiatives may have taken different forms at Duke TIP, the underlying philosophy and commitment to identify and further the development of gifted and talented youth remains steadfast.

  280. 2005-olszewskikubilius.pdf

  281. 2005-rigby.pdf

  282. 2005-wallace.pdf

  283. 2005-brody.pdf

  284. 2005-brody-3.pdf

  285. 2005-gilheany.pdf

  286. 2005-touron-2.pdf

  287. 2005-frost.pdf

  288. 2005-touron-3.pdf

  289. 2005-wai.pdf

  290. 2006-benbow.pdf


  292. 2006-lubinski.pdf

  293. 2006-lubinski-2.pdf



  296. 2006-muratori.pdf

  297. 2007-brody.pdf

  298. 2007-halpern.pdf

  299. 2007-lubinski.pdf

  300. 2007-park.pdf

  301. 2007-park-2.pdf


  303. 2008-park.pdf

  304. 2007-swiatek.pdf: “GCQ306318.qxd

  305. 2007-webb.pdf

  306. 2008-leder.pdf: “MERGAVolume1.pdf⁠, yeh

  307. 2009-benbow.pdf: “Extending Sandra Scarr's Ideas about Development to the Longitudinal Study of Intellectually Precocious Youth”⁠, Camilla P. Benbow, David Lubinski

  308. 2009-brody.pdf: “The Johns Hopkins Talent Search Model for Identifying and Developing Exceptional Mathematical and Verbal Abilities”⁠, Linda E. Brody

  309. 2009-ferriman.pdf

  310. 2009-lubinski.pdf: “Cognitive epidemiology: With emphasis on untangling cognitive ability and socioeconomic status”⁠, David Lubinski

  311. 2009-lubinski-2.pdf

  312. 2009-wai.pdf


  314. #wai-et-al-2009

  315. 2009-wai-2.pdf

  316. 2009-steenbergenhu.pdf⁠, markj

  317. 2010-steenbergenhu.pdf

  318. 2010-henshon.pdf: “Talent Sleuth Extraordinaire: An Interview With Camilla P. Benbow”⁠, Suzanna E. Henshon, Camilla P. Benbow

  319. 2010-lubinski.pdf: “Spatial ability and STEM: A sleeping giant for talent identification and development⁠, David Lubinski

  320. 2010-robertson.pdf

  321. #park-et-al-2007

  322. #park-et-al-2008

  323. 2010-wai.pdf


  325. 2011-hunt-ch10-whatuseisintelligence.pdf: “_Human Intelligence_: chapter 10, What Use Is Intelligence?”⁠, Earl Hunt

  326. 2011-touron.pdf: “The Center for Talented Youth Identification Model: A Review of the Literature”⁠, Javier Tourón, Marta Tourón


  328. 2012-benbow.pdf: ⁠, Camilla Persson Benbow (2021-02-01; iq  /​ ​​ ​smpy):

    Calls to strengthen education in science, technology, engineering, and mathematics (STEM) are underscored by employment trends and the importance of STEM innovation for the economy. The Study of Mathematically Precocious Youth (SMPY) has been tracking over 5,000 talented individuals longitudinally for 40 years, throwing light on critical questions in talent identification and development in STEM. SMPY includes individuals identified in 7th/​​​​8th grade as in the top 1% or higher in mathematical or verbal ability, and a comparison group identified as top STEM graduate students.

    SMPY findings cover the educational and occupational attainments of participants, including a large percentage earning a degree or pursuing high powered careers in STEM; gender differences; the extent to which high school experiences, abilities, and interests predict later outcomes; and subsequent creative production. Mathematical reasoning ability as measured by standardized tests is a reliable predictor for later math/​​​​science engagement and achievement in adulthood, and spatial ability adds predictive value. Exposure to appropriate educational opportunities do correlate with career achievement and creative production.

    SMPY researchers have concluded that potential future STEM innovators can be identified early and that educational interventions can increase their chances of success.

  329. 2013-kell-3.pdf: “Spatial Ability: A Neglected Talent in Educational and Occupational Settings”⁠, Harrison J. Kell, David Lubinski

  330. 2013-kell.pdf: ⁠, Harrison J. Kell, David Lubinski, Camilla P. Benbow (2013-03-26; iq  /​ ​​ ​smpy):

    Youth identified before age 13 (n = 320) as having profound mathematical or verbal reasoning abilities (top 1 in 10,000) were tracked for nearly three decades. Their awards and creative accomplishments by age 38, in combination with specific details about their occupational responsibilities, illuminate the magnitude of their contribution and professional stature.

    Many have been entrusted with obligations and resources for making critical decisions about individual and organizational well-being. Their leadership positions in business, health care, law, the professoriate, and STEM (science, technology, engineering, and mathematics) suggest that many are outstanding creators of modern culture, constituting a precious human-capital resource. Identifying truly profound human potential, and forecasting differential development within such populations, requires assessing multiple cognitive abilities and using atypical measurement procedures.

    This study illustrates how ultimate criteria may be aggregated and longitudinally sequenced to validate such measures.

    [Keywords: cognitive abilities, creativity, human capital, intelligence, profoundly gifted, STEM]

  331. 2013-kell-2.pdf

  332. 2013-park.pdf


  334. ⁠, Stephen D. H. Hsu (2014-08-14):

    How do genes affect cognitive ability or other human quantitative traits such as height or disease risk? Progress on this challenging question is likely to be significant in the near future. I begin with a brief review of psychometric measurements of intelligence, introducing the idea of a “general factor” or g score. The main results concern the stability, validity (predictive power), and heritability of adult g. The largest component of genetic variance for both height and intelligence is additive (linear), leading to important simplifications in predictive modeling and statistical estimation. Due mainly to the rapidly decreasing cost of genotyping, it is possible that within the coming decade researchers will identify loci which account for a significant fraction of total g variation. In the case of height analogous efforts are well under way. I describe some unpublished results concerning the genetic architecture of height and cognitive ability, which suggest that roughly 10k moderately rare causal variants of mostly negative effect are responsible for normal population variation. Using results from Compressed Sensing (L1-penalized regression), I estimate the statistical power required to characterize both linear and nonlinear models for quantitative traits. The main unknown parameter s (sparsity) is the number of loci which account for the bulk of the genetic variation. The required sample size is of order 100s, or roughly a million in the case of cognitive ability.


  336. 2013-stumpf.pdf: ⁠, Heinrich Stumpf, Carol J. Mills, Linda E. Brody, Philip G. Baxley (2013-10-10; iq  /​ ​​ ​smpy):

    The importance of spatial ability for success in a variety of domains, particularly in science, technology, engineering, and mathematics (STEM), is widely acknowledged. Yet, students with high spatial ability are rarely identified, as Talent Searches for academically talented students focus on identifying high mathematical and verbal abilities. Consequently, students with high spatial abilities who do not also have high math or verbal abilities may not qualify.

    In an effort to identify students with spatial talent, the Center for Talented Youth developed a Spatial Test Battery to supplement its mathematical and verbal Talent Searches. This article traces the development of the battery; describes its components, important psychometric properties, and continuing development; and encourages its use by researchers and educators interested in developing spatial talent.

    [Keywords: block rotation test, CTY Spatial Test Battery, spatial ability, spatial test, STEM, surface development test, talent search, visual memory test]

  337. 2014-beattie.pdf


  339. 2014-brody.pdf


  341. 2014-lubinski.pdf


  343. 2014-kell.pdf


  345. 2014-johnson.pdf: ⁠, Wendy Johnson, Thomas J. Bouchard Jr. (2014; genetics  /​ ​​ ​heritable  /​ ​​ ​emergenesis):

    [Behavioral genetics discussion of eminence/​​​​genius: intelligence, developmental processes, psychopathology, and creativity scales all contribute to accomplishment but leave much unexplained, in particular, the odd pattern of inheritance where genius runs in families but highly sporadically and not following any standard Mendelian or polygenic inheritance pattern.

    The authors refer to the concept of ‘emergenesis’⁠, where emergenic traits are not additive combinations of subtraits (as is strongly the case for traits like intelligence) but rather are multiplicative combinations, which are epistatic at the genetic level. Because all subtraits must be present to have a chance of producing the overall trait, emergenic traits can be highly genetically influenced yet still rare and sporadically appearing within families. (The Wiley Handbook of Genius 2014, chapter 14)]


  347. 2014-wai.pdf: “Experts are born, then made: Combining prospective and retrospective longitudinal data shows that cognitive ability matters”⁠, Jonathan Wai

  348. 2014-wai-2.pdf

  349. #lubinski-2004b

  350. 2015-brody.pdf

  351. 2016-lubinski.pdf


  353. 2016-makel.pdf: ⁠, Matthew C. Makel, Harrison J. Kell, David Lubinski, Martha Putallaz, Camilla P. Benbow (2016-07-01; iq  /​ ​​ ​smpy):

    The educational, occupational, and creative accomplishments of the profoundly gifted participants (IQs ⩾ 160) in the Study of Mathematically Precocious Youth (SMPY) are astounding, but are they representative of equally able 12-year-olds? Duke University’s Talent Identification Program (TIP) identified 259 young adolescents who were equally gifted. By age 40, their life accomplishments also were extraordinary: Thirty-seven percent had earned doctorates, 7.5% had achieved academic tenure (4.3% at research-intensive universities), and 9% held patents; many were high-level leaders in major organizations. As was the case for the SMPY sample before them, differential ability strengths predicted their contrasting and eventual developmental trajectories—even though essentially all participants possessed both mathematical and verbal reasoning abilities far superior to those of typical Ph.D. recipients. Individuals, even profoundly gifted ones, primarily do what they are best at. Differences in ability patterns, like differences in interests, guide development along different paths, but ability level, coupled with commitment, determines whether and the extent to which noteworthy accomplishments are reached if opportunity presents itself.

    [Keywords: intelligence, creativity, giftedness, replication, blink comparator]

  354. 2004-frey.pdf: ⁠, Meredith C. Frey, Douglas K. Detterman (2004-01-01; iq):

    There is little evidence showing the relationship between the Scholastic Assessment Test (SAT) and g (general intelligence). This research established the relationship between SAT and g, as well as the appropriateness of the SAT as a measure of g, and examined the SAT as a premorbid measure of intelligence. In Study 1, we used the National Longitudinal Survey of Youth 1979. Measures of g were extracted from the Armed Services Vocational Aptitude Battery and correlated with SAT scores of 917 participants. The resulting correlation was .82 (.86 corrected for nonlinearity). Study 2 investigated the correlation between revised and recentered SAT scores and scores on the Raven’s Advanced Progressive Matrices among 104 undergraduates. The resulting correlation was .483 (.72 corrected for restricted range). These studies indicate that the SAT is mainly a test of g. We provide equations for converting SAT scores to estimated IQs; such conversion could be useful for estimating premorbid IQ or conducting individual difference research with college students.

  355. #lubinski-et-al-2001b



  358. ⁠, Harrison Kell, David Lubinski, Camilla Benbow (2017-07-14):

    Over a century of research has demonstrated that intelligence is associated with positive health outcomes (Terman, 1925, Mental and physical traits of a thousand gifted children). Nonetheless, some still doubt whether gifted children grow up to be (on average) healthy, well-adjusted adults (eg., Neihart, 1999). This study compares medical and psychological health outcomes of middle-aged adults from the general population (n = 3,652) to four SMPY cohorts. Cohort 1 (n = 1,159) score in the top 1% of ability and Cohort 2 (n = 491) score in the top 0.5% of ability. Four decades after identification, both cohorts were administered a comprehensive biographical survey, which included many health questions (Lubinski, Benbow, & Kell, 2014). Across 23 items, gifted males evinced more positive outcomes than males of average intelligence on 22 (96%). The mean odds ratio (OR) was 5.32, meaning males of average intelligence were over five times more likely to experience a negative health outcome than those in the top 1%. Gifted females evinced more positive outcomes in 65% of the categories, with a mean odds ratio of 2.52.

    Comparisons of health outcomes within the top 1% are complicated by the higher mean age of Cohort 1 (53) relative to Cohort 2 (48). Only 2 statistically-significant differences emerged between gifted females: Those in the top 1% were more likely than those in the 0.5% to have felt calm and peaceful and less likely to have had emotional or physical problems interfere with their activities recently (average d = 0.12). Results were less consistent for males. Males in the top 1% were statistically-significantly more likely to experience chest pains, hypertension, and arthritis (OR = 2.23), while males in the top 0.5% were more likely to experience asthma, depression, and non-depressive psychiatric problems (OR = 1.2).

    As a replication, 2 additional SMPY samples were administered the same survey. Cohort 3 consists of young adolescents identified as being in the top 0.01% in the early 1980s (anticipated n > 300). Cohort 4 consisted of first-year and second-year students attending top 15 U.S. math/​​​​science graduate programs in 1992 (anticipated n > 400). Health outcomes of these two cohorts will be compared not only to those of the general population, but to those of the top 1% and 0.5% as well. The size, scope, and quality of these data represent an unprecedented opportunity for examining the well-being of intellectually talent adults. Finally, these data also allow for the comparison of health outcomes between three high ability groups explicitly identified in young adolescence and a group of extraordinarily capable individuals identified as extraordinary achievers in early adulthood. Note: Preliminary data from Cohorts 3 and 4 are not ready for analysis, but the survey is well underway. Preliminary findings would be presented at ISIR 2017 for the first time.

  359. #lubinski-et-al-2014

  360. 2017-wai.pdf: “What Innovations Have We Already Lost?: The Importance of Identifying and Developing Spatial Talent”⁠, Jonathan Wai, Harrison J. Kell

  361. 2018-lubinski.pdf: “Individual Differences at the Top: Mapping the Outer Envelope of Intelligence”⁠, David Lubinski

  362. 2019-bernstein.pdf: ⁠, Brian O. Bernstein, David Lubinski, Camilla P. Benbow (2019-01-01; iq  /​ ​​ ​smpy):

    This investigation examined whether math/​​​​scientific and verbal/​​​​humanistic ability and preference constellations, developed on intellectually talented 13-year-olds to predict their educational outcomes at age 23, continue to maintain their longitudinal potency by distinguishing distinct forms of eminence 35 years later. Eminent individuals were defined as those who, by age 50, had accomplished something rare: creative and highly impactful careers (e.g., full professors at research-intensive universities, Fortune 500 executives, distinguished judges and lawyers, leaders in biomedicine, award-winning journalists and writers). Study 1 consisted of 677 intellectually precocious youths, assessed at age 13, whose leadership and creative accomplishments were assessed 35 years later. Study 2 constituted a constructive replication—an analysis of 605 top science, technology, engineering, and math (STEM) graduate students, assessed on the same predictor constructs early in graduate school and assessed again 25 years later. In both samples, the same ability and preference parameter values, which defined math/​​​​scientific versus verbal/​​​​humanistic constellations, discriminated participants who ultimately achieved distinct forms of eminence from their peers pursuing other life endeavors.

  363. 2019-mccabe.pdf: “Who shines most among the brightest?: A 25-year longitudinal study of elite STEM graduate students⁠, Kira O. McCabe, David Lubinski, Camilla P. Benbow

  364. #lubinski-et-al-2001a

  365. ⁠, Harrison J. Kell, Jonathan Wai (2019):

    It has been claimed by prominent authors that there is no relationship between differences in some human traits (eg., cognitive ability, physical ability) and differences in skill among experts. We assert that the failure to detect such associations is often due to an extreme form of range restriction that particularly plagues research focused on expert samples: right-tail range restriction (RTRR). RTRR refers to a lack of representation of data from the far right segment of the normal distribution, inhibiting the observation of statistical associations.

    Using 2 example studies we demonstrate that, when RTRR is not present, relationships between differences in experts’ traits and differences in their degree of skill can be observed. Based on the characteristics of these studies we make recommendations for methodological practices that can be followed to help investigators overcome RTRR and facilitate the continued development of a robust and replicable science of expertise.

    [Keywords: ⁠, expertise, traits, cognitive ability, physical ability, performance, athletics, psychological attributes]

  366. #kell-et-al-2013a

  367. #lubinski-benbow-2006

  368. #makel-et-al-2016

  369. 2020-bernstein.pdf: ⁠, Brian O. Bernstein, David Lubinski, Camilla P. Benbow (2020-07-02; iq  /​ ​​ ​smpy):

    Academic acceleration of intellectually precocious youth is believed to harm overall psychological well-being even though short-term studies do not support this belief. Here we examine the long-term effects. Study 1 involves three cohorts identified before age 13, then longitudinally tracked for over 35 years: Cohort 1 gifted (top 1% in ability, identified 1972–1974, n = 1,020), Cohort 2 highly gifted (top 0.5% in ability, identified 1976–1979, n = 396), and Cohort 3 profoundly gifted (top 0.01% in ability, identified 1980–1983, n = 220). Two forms of educational acceleration were examined: (a) age at high school graduation and (b) quantity of advanced learning opportunities pursued to high school graduation. Participants were evaluated at age 50 on several well-known indicators of psychological well-being. Amount of acceleration did not covary with psychological well-being. Study 2, a constructive replication of Study 1, used a different high-potential sample—elite science, technology, engineering, and mathematics graduate students (n = 478) identified in 1992. Their educational histories were assessed at age 25 and they were followed up at age 50 using the same psychological assessments. Again, the amount of educational acceleration did not covary with psychological well-being. Further, the psychological well-being of participants in both studies was above the average of national probability samples. Concerns about long-term social/​​​​emotional effects of acceleration for high-potential students appear to be unwarranted, as has been demonstrated for short-term effects.

    [Keywords: gifted, acceleration, replication, appropriate developmental placement, psychological well-being]

    Impact Statement: Best practices suggest that acceleration in one of its many forms is educationally efficacious for meeting the advanced learning needs of intellectually precocious youth. Yet, parents, teachers, academic administrators, and psychological theorists worry that this practice engenders negative psychological effects. A three-cohort study of intellectually precocious youth followed for 35 years suggests that there is no cause for concern. These findings were replicated on a sample of elite STEM graduates whose educational histories were assessed at age 25 and tracked for 25 years.

  370. 2020-lubinski-2.pdf: ⁠, David Lubinski, Camilla P. Benbow (2020-07-28; iq  /​ ​​ ​smpy):

    Over the past 50 years, eight robust generalizations about intellectual precocity have emerged, been empirically documented, and replicated through longitudinal research. Within the top 1% of general and specific abilities (mathematical, spatial, and verbal) over one third of the range of individual differences are to be found, and they are meaningful. These individual differences in ability level and in pattern of specific abilities, which are uncovered by the use of above-level assessments, structure consequential quantitative and qualitative differences in educational, occupational, and creative outcomes. There is no threshold effect for abilities in predicting future accomplishments; and the concept of multipotentiality evaporates when assessments cover the full range of all three primary abilities. Beyond abilities, educational/​​​​occupational interests add value in identifying optimal learning environments for precocious youth and, with the addition of conative variables, for modeling subsequent life span development. While overall professional outcomes of exceptionally precocious youth are as exceptional as their abilities, educational interventions of sufficient dosage enhance the probability of them leading exceptionally impactful careers and making creative contributions. Findings have made evident the psychological diversity within intellectually precocious populations, their meaningfulness, and the environmental diversity required to meet their learning needs. Seeing giftedness and interventions on their behalf categorically has held the field back.

    [Keywords: basic interpretive, mixed methods, psychometrics, assessment, creativity, gifted]

    1. Is there an ability threshold, beyond which more ability doesn’t matter? No.

    2. Does the pattern of specific abilities matter? Yes.

      Is there evidence for multipotentiality? No.

    3. Is ability pattern important for students with especially profound intellectual gifts? Yes.

    4. Do educational/​​​​​occupational interests add value to ability assessments of intellectually precocious youth? Yes.

    5. Given the contemporary emphasis placed on the identification and development of human capital in STEM disciplines, are there other important findings from the gifted field germane to this need? Yes.

    6. Can educational interventions enhance learning and ultimate levels of creative expression? Yes.

    7. Beyond ability, interest, and opportunity, are conative attributes important? Yes.

    8. Has the study of intellectual precocity contributed to its parent disciplines in the educational and psychological sciences? Is there a common theme that cuts across the above empirical generalizations, which have been replicated over multiple decades? Yes. And yes.

  371. 2020-henshon.pdf: ⁠, Suzanna E. Henshon (2020-07-30; iq  /​ ​​ ​smpy):

    [Short interview with Linda Brody, current director of Study of Exceptional Talent (SET) at the Johns Hopkins Center for Talented Youth (CTY); she originally started working for SMPY in the 1970s along with Cohn/​​​​Pyryt/​​​​Benbow and for Lynn Fox & Julian Stanley, leaving in 1991 for CTY. She specialized in “twice-exceptional students” (both gifted & disabled). SET is currently studying its alumni.]

  372. 2020-schuur.pdf: ⁠, Jolande Schuur, Marjolijn van Weerdenburg, Lianne Hoogeveen, Evelyn H. Kroesbergen (2020-11-09; iq  /​ ​​ ​smpy):

    Gifted students who experienced grade-based acceleration in primary or secondary education have to meet the challenges of adjusting to university at a younger age than students who did not accelerate. This systematic review critically evaluates the research on social–emotional characteristics and adjustment of these gifted accelerated university students. Based on a review of 22 studies, we may conclude that accelerated students did not differ very much in domains of social–emotional characteristics from their nonaccelerated gifted and nongifted peers. Factors that facilitated adjustment and well-being were cheerfulness, resilience, self-efficacy, a positive self-concept, high prior academic achievement, and supportive family environment. Furthermore, it was found that studies were incomplete in reporting the previous acceleration experiences of the students and that research on students who individually accelerated by 1 or 2 years was scarce. Future research should include individually accelerated students, previous acceleration experiences, gender differences, and comparison groups.

  373. 2020-cardador.pdf: ⁠, M. Teresa Cardador, Rodica Ioana Damian, Justin P. Wiegand (2020-06-08; iq  /​ ​​ ​smpy):

    The persistent gender gap in STEM (Science, Technology, Engineering, and Math) career choice represents a perplexing problem for researchers and policy makers alike. We contribute to the body of research on the gender gap in STEM careers by testing a “surplus model” of vocational interests as a predictor of STEM career choice. The model suggests that, controlling for ability, female adolescents with strong STEM-related interest should be less likely to pursue STEM careers when they also have strong interests in other areas, due to wider career options. We tested the surplus model in a large national longitudinal data set and translated the results into differences in annual wages. Our findings illuminate the predictive validity of a surplus model of interests on STEM career choice across gender, provide insight into the gender gap in STEM, and suggest opportunities for future research.

    [Keywords: vocational interests, surplus model, stem gender gap, stem career choice]

  374. 1957-super-scientificcareersandvocationaldevelopmenttheory.pdf: “Scientific Careers and Vocational Development Theory: A review, a critique and some recommendations”⁠, Donald E. Super, Paul B. Bachrach

  375. 1964-smith-spatialabilityitseducationalsocialsignificance.pdf: “Spatial Ability: Its Educational and Social Significance”⁠, I. Macfarlane Smith

  376. 1985-rootbernstein.pdf: “Visual Thinking: The Art of Imagining Reality”⁠, Robert Scott Root-Bernstein

  377. 1965-walkup.pdf: ⁠, Lewis E. Walkup (1965-08-01; iq):

    Editors’ note: Mr. Walkup, an electrical engineer by training but an applied physicist by experience, has worked 12 yr. in research on explosives and ballistics and 19 yr. in the technology of the graphic arts, especially on the electrostatic photographic process called xerography. In this latter field he has been a major contributor of inventive ideas; he holds 37 U. S. and 60 foreign patents. The present article is a result of his personal study of creativity in his co-workers in a large industrial research institute.

    The fact that attempts to gain insight into the creative process have been so unsuccessful suggests that they have overlooked at least one basic ingredient in the process. This ingredient may lie in the nature or way the individual mind goes about remembering and manipulating data. The hypothesis is advanced that the creative persons appear to have stumbled onto and then developed to a high degree of perfection the ability to visualize—almost hallucinate—in the area in which they are creative. And their visualizations seem to be of a sort that lend themselves to easy manipulation in the thinking process. This is illustrated by reports from many of the great inventors of the past and it is easy to demonstrate that individuals differ enormously in the kind and degree of their ability to think in such manipulable visualizations. If correct, this aspect of creativity suggests many research attacks and many potential changes in education for creative activity.

    …It is interesting to ask a number of persons to solve a simple problem in mental arithmetic, say, to subtract 46 from 100, and then to ask them what went on in their heads as they solved the problem. I have found the following gamut of processes used. Some persons simply grope around with words, perhaps dividing the problem up into subtracting 6 from 10 and 4 from 10, which they do simply by remembering the words associated with these operations and then somehow combining these results to give the final answer. Others mentally write out 100 with 46 beneath it and picture the process of writing down the answer below the two. Finally, some individuals have specialized equipment for just this operation. They visualize two juxtaposed scales from zero to 100, one starting at the right and one at the left. With this mnemonic gadget the required subtraction involves simply finding 46 on one of the scales and reading off 54 on the other!

    …Another interesting example involves the ability to visualize combinations of cubes. Try asking a number of persons to visualize a large cube made up of 27 smaller cubes, that is, three on each edge of the composite cube. Then, ask him to imagine painting the entire outer surface of the large cube. Finally, ask him how many of the smaller cubes he has painted on zero, one, two, or three sides. After he gives the result, ask him to describe the mental process he used in arriving at the answer. A surprising variety of answers come from this simple test. Some persons, even some professionally engaged in science and art, simply are unable to solve this problem mentally because they cannot visualize a cube in any way! Others stumble around with crude visualizations of a cube and end up by guessing at the answer. Some can visualize an opaque cube fairly well but must infer from the one view what is on the other side. The most potent approach seems to be that of the person who can visualize a transparent cube and simply count the smaller cubes whose sides are covered with paint, a process something like counting one’s fingers with his hands held up in front of him.

    In still another provocative problem, persons may be asked co give verbal directions for driving a car from one location to another, and then asked what they visualized mentally as they were giving the directions. Again, a wide variety of mental processes will be disclosed. Surprisingly, many persons report seeing the route as from a low-flying helicopter. The fact that different persons use vastly different visualizations in thinking is suggested by some other informal reports. One person has declared that he dreams only in words, that he does not use any form of visualization in dream states. It has been claimed by some semanticists that the human being thinks only in words. This seems an utterly absurd statement to many of us who spend a large part of our waking hours in visualizing and thinking in pictorial representations. This, of course, does not deny the fact that it is quite possible that semanticists do, in fact, think only in words; it would be logical that “word thinkers” would be drawn to this specialized field.

    …This is well illustrated by the now famous visualization by Kekule, as reported by Beveridge, which led him to the discovery of the benzene ring through a vision of a series of linked atoms biting its tail like a snake. Michael Faraday was one of the first to “see” the electrical and magnetic lines of force that now are standard tools for physicists to visualize otherwise mysterious phenomena in this area. Albert Einstein apparently believed that thought consisted entirely of dealing with mechanical images and not at all of words. The mathematician that he thought exclusively in visual pictures. However, these men did not seem to realize the uniqueness of their ability to visualize in manipulable images. They seemed to assume that all persons had much the same ability. Inventors with whom I have talked report thinking visually about complex mechanisms and organic chemical molecules combining with other molecules. So, it appears that ideas which can be grasped when drawn on paper can be visualized without being put onto paper, perhaps with many shorthand approximations for unimportant parts. Also, the nature of the seeing or sensing is peculiar. It is almost a feeling like the object being visualized. One can feel the pressure of contacting objects, or the erosion of material by friction, or the flow of heat from one point to another, or the swing of the oscillating electrical circuit, or the bending of light as it passes from one medium to another, or the appropriateness of a well-designed structure co hold a maximum load, with every part equally strained in the process, or the eternal bouncing about of the molecules of a gas, or the almost physical transfer of energy from the gasoline, through the motor, transmission, and to the driving wheels of the automobile. It is as though one’s own kinesthetic sensing mechanisms were associated with the physical object and that he thus sensed directly what was going on in the external system. In highly-developed visualizers, this process probably is carried over for other than physical phenomena. Thus, poverty can be seen and felt as a pervading vapor that penetrates a house with its odors and depression, and history might be strung out along an imaginary line extending back as far as one wishes.

    …At least here is a positive lead that is so apparent to the creative persons with whom I am familiar that they never stopped to consider whether or not it is special. When asked if they use life-like visualizations when they are inventing, they are inclined to say, “Why yes. Doesn’t everybody?” [See also: typical mind fallacy]

  378. 1969-arnheim-visualthinking.pdf: “Visual Thinking”⁠, Rudolf Arnheim

  379. 1980-arnheim.pdf: “A Plea for Visual Thinking”⁠, Rudolf Arnheim

  380. 1986-wagner.pdf

  381. Anne-Roe


  383. 1994-gottfried-giftediqfullertonlongitudinalstudy.pdf

  384. 1996-gottfried.pdf

  385. 2004-gottfried.pdf

  386. 2005-gottfried.pdf

  387. 2006-gottfried.pdf

  388. 2009-gottfried.pdf: “Issues in Early Prediction and Identification of Intellectual Giftedness”⁠, Allen W. Gottfried, Adele Eskeles Gottfried, Diana Wright Guerin

  389. 2009-gottfried-2.pdf: “Development of gifted motivation: Longitudinal Research and Applications”⁠, Adele Eskeles Gottfried, Allen W. Gottfried

  390. 2017-mccoach.pdf: “Developing talents: A longitudinal examination of intellectual ability and academic achievement”⁠, D. Betsy McCoach, Huihui Yu, Allen W. Gottfried, Adele Eskeles Gottfried

  391. 1990-heller.pdf

  392. 1990-taylor-expandingawarenessofcreativepotentialsworldwide.pdf

  393. 1991-heller.pdf: “The Nature and Development of Giftedness. A Longitudinal Study”⁠, Kurt A., Heller

  394. 1993-perleth.pdf: ⁠, Christopher Perleth, Wolfgang Sierwald, Kurt A. Heller (1993; iq  /​ ​​ ​munich):

    The Munich Longitudinal Study of Giftedness (carried out from 1985 to 1989), the most comprehensive giftedness study ever conducted in Germany, covers 6 cohorts at 3 points of measurement. In this article, the study’s multidimensional and typographical conception of giftedness is explained.

    After a short overview, results concerning the validation of the multidimensional giftedness model as well as attempts to establish a giftedness typology are presented. While the multidimensional model proved to be useful for predicting achievement behavior, the typological attempts failed. Finally, it is demonstrated that intelligent and creatively gifted students differ strongly in their achievement behavior.

    Consequences for fostering the gifted, especially the creatives, in school are discussed.

  395. 1994-perleth.pdf: “The Munich Longitudinal Study of Giftedness”⁠, Christopher, Perleth und Kurt A., Heller

  396. 2004-heller.pdf: “05.pdf”⁠, Vahrenhorst

  397. 2005-heller.pdf

  398. 2008-heller.pdf⁠, Vahrenhorst


  400. 2013-heller.pdf