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J. Intell., Volume 2, Issue 3 (September 2014) – 5 articles , Pages 56-121

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159 KiB  
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Are Humans the Most Intelligent Species?
by Robert P. Erickson
J. Intell. 2014, 2(3), 119-121; https://doi.org/10.3390/jintelligence2030119 - 22 Sep 2014
Cited by 4 | Viewed by 14674
Abstract
Hunt and Jaeggi [1] nicely summarize the point that within the academic field of intelligence, we do not have a commonly understandable definition of what intelligence is. Still the term is used extensively and with consensus to the effect that humans are the [...] Read more.
Hunt and Jaeggi [1] nicely summarize the point that within the academic field of intelligence, we do not have a commonly understandable definition of what intelligence is. Still the term is used extensively and with consensus to the effect that humans are the most intelligent species. An example is given of this problem, and a definition and solution are suggested. Full article
(This article belongs to the Special Issue Intelligence, Where to Look, Where to Go?)
387 KiB  
Article
The Flynn Effect in Families: Studies of Register Data on Norwegian Military Conscripts and Their Families
by Jon Martin Sundet
J. Intell. 2014, 2(3), 106-118; https://doi.org/10.3390/jintelligence2030106 - 18 Sep 2014
Cited by 12 | Viewed by 14835
Abstract
In the present paper published data and new analyses are presented and discussed in order to demonstrate the power of family data (siblings and parents to military conscripts with IQ data) in the study of the Flynn effect (FE). In particular, it is [...] Read more.
In the present paper published data and new analyses are presented and discussed in order to demonstrate the power of family data (siblings and parents to military conscripts with IQ data) in the study of the Flynn effect (FE). In particular, it is shown how studies of the mean intelligence changes in sibships of different sizes and changing proportions of sibship sizes can enhance our understanding how these factors may influence FE. Some new analyses of correlations between intelligence and sibship sizes illustrate how family data can be used to investigate changes in the correlation pattern across generations. It is shown that comparison of the secular trends in the general population and in sibling pairs can be a powerful method in the exploration of the relative influence of between-families and within-families factors in the FE. Surprising connections between the birth order effect on intelligence and the FE are demonstrated. Full article
(This article belongs to the Special Issue Methodological Advances in Understanding the Flynn Effect)
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960 KiB  
Article
Can GE-Covariance Originating in Phenotype to Environment Transmission Account for the Flynn Effect?
by Janneke M. De Kort, Conor V. Dolan, Kees-Jan Kan, Catharina E. M. Van Beijsterveldt, Meike Bartels and Dorret I. Boomsma
J. Intell. 2014, 2(3), 82-105; https://doi.org/10.3390/jintelligence2030082 - 01 Sep 2014
Cited by 10 | Viewed by 7449
Abstract
The Dickens and Flynn model of the Flynn effect (generational increases in mean IQ) assigns an important role to genotype-environment covariance (GE-cov). We quantify GE-cov in a longitudinal simplex model by modeling it as phenotype to environment (Ph->E) transmission in twin data. The [...] Read more.
The Dickens and Flynn model of the Flynn effect (generational increases in mean IQ) assigns an important role to genotype-environment covariance (GE-cov). We quantify GE-cov in a longitudinal simplex model by modeling it as phenotype to environment (Ph->E) transmission in twin data. The model fits as well as the standard genetic simplex model, which assumes uncorrelated genetic and environmental influences. We use the results to explore numerically the possible role of GE-cov in amplifying increases in environmental means. Given the estimated Ph->E transmission parameters, GE-cov resulted in an amplification (in std units) of a factor 1.57 (full scale IQ) to 1.7 (performance IQ). The results lend credence to the role of GE-cov in the Flynn effect. Full article
(This article belongs to the Special Issue Methodological Advances in Understanding the Flynn Effect)
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294 KiB  
Article
Predicting Intellectual Ability and Scholastic Outcomes with a Single Item: From Early Childhood to Adulthood
by Curtis S. Dunkel and Nora A. Murphy
J. Intell. 2014, 2(3), 68-81; https://doi.org/10.3390/jintelligence2030068 - 31 Jul 2014
Cited by 2 | Viewed by 7339
Abstract
Previous research shows that perceived intelligence judgments significantly correlate with measured intelligence scores. The present study investigated the developmental trajectory of the association between perceived intelligence and measured intelligence. Using the Block and Block longitudinal dataset, we examined the relationship between a single [...] Read more.
Previous research shows that perceived intelligence judgments significantly correlate with measured intelligence scores. The present study investigated the developmental trajectory of the association between perceived intelligence and measured intelligence. Using the Block and Block longitudinal dataset, we examined the relationship between a single rating of “high intellectual ability” made in early childhood by targets’ preschool teachers with future intellectual ability and scholastic outcome measures, including IQ scores, grade-point average, SAT scores, and educational attainment. Even when controlling for variables including attractiveness, parental education levels, the General Factor of Personality, and socioeconomic status, correlations between early childhood intelligence perceptions and later intellectual measures were significant, large, and robust. Results are discussed in terms of potential mechanisms and cues in early childhood that may reveal future intellectual abilities. Full article
819 KiB  
Article
The Sternberg Triarchic Abilities Test (Level-H) is a Measure of g
by Weng-Tink Chooi, Holly E. Long and Lee A. Thompson
J. Intell. 2014, 2(3), 56-67; https://doi.org/10.3390/jintelligence2030056 - 09 Jul 2014
Cited by 7 | Viewed by 37188
Abstract
Although the consensus in the field of human intelligence holds that a unitary factor (g) accounts for the majority of the variance among individuals, there are still some who argue that intelligence is composed of separate abilities and individual differences across [...] Read more.
Although the consensus in the field of human intelligence holds that a unitary factor (g) accounts for the majority of the variance among individuals, there are still some who argue that intelligence is composed of separate abilities and individual differences across abilities in combination are what constitutes intelligence. In keeping with the latter theoretical support, the Sternberg Triarchic Abilities Test (STAT) is an intelligence test that is designed to measure three distinct types of intelligence: analytical, practical, and creative. Several analyses were conducted to establish whether or not the triarchic model is empirically supported, or if a unitary construct is the best explanation of individual differences on this test. Exploratory and confirmatory factor analyses indicate that a g model is the best explanation for the data. Full article
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