Wednesday, 30 September 2015

Does culture cultivate, or do you need a good plough?

 

The search for culture-free or culture-fair tests has proved endless, because “culture” can be used so broadly as to encompass virtually anything a human does. People live in society, and societies transmit the habits of previous generations. There was a time in the debates after Jensen’s 1969 paper when psychologists believed that they could estimate the cultural loading of a test by inspecting the items. Indeed, my very first published paper attacked Jensen for arguing that the Wechsler subtest of Block Design was relatively culture-free, such that black-white differences on that test were probably genetic, whereas I felt it depended on access to constructional toys.

How does one determine the cultural loading of an intelligence test item? A Dutch team have plunged into these waters (strictly speaking they are below sea level, but no matter) and have rated subtests thus: Cultural load was operationalized as the average proportion of items that were adjusted in each subtest of the WAIS-III when the scale was adapted for use in 13 countries (Georgas et al., 2003).  To my eye that is certainly a language adjustment, though I wonder whether it allows for the different availabilities of artefacts in the home (not that I can think of an easy way to measure that).

Kees-Jan Kan, Jelte M. Wicherts, Conor V. Dolan, and Han L. J. van der Maas. On the Nature and Nurture of Intelligence and Specific Cognitive Abilities: The More Heritable, the More Culture Dependent. Psychological Science 24(12) 2420–2428

http://wicherts.socsci.uva.nl/kan_PS_2013.pdf

 

 

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On this measure, Vocabulary is the most culture dependent subtest. On first glance that makes sense: the easiest way to learn a language is to be immersed in the particular culture that speaks it. However, that merely covers translating words from one language to another. Even within a culture, even the most ethno-centric citizens do not learn all the available words: intelligence is required for that.

From an early post on Vocabulary: Some people have the simplistic notion that vocabulary must be determined by mere exposure to spoken language. That is necessary, but far from sufficient, as even children work out. They notice patterns, informal rules, and the contexts in which communication takes place.  “The acquisition of meaning is based on the eduction of meaning from the contexts in which the words are encountered”. (So, even if the word “eduction” in the quotation from page 146 of Jensen’s “Bias in mental Testing” is unfamiliar, you will not be surprised to deduce that it means “To assume or work out from given facts; deduce”).The meaning of a word is acquired in some contexts which permits at least some partial inference as to its meaning. By hearing or reading the word in different contexts, through a process of generalization, discrimination and eduction one can guess at the essence of the meaning of the word, so as to use it (experimentally) oneself the next time a similar context presents itself. Words move from being unfamiliar to familiar, from familiar but not really understood to being familiar and partly understood (at which stage the explanations given about the meaning of the word are threadbare and inaccurate), and from there to being explained by use of synonyms (though those can range from partial to full understanding as shown by the power of the explanations and definitions).

http://drjamesthompson.blogspot.co.uk/2013/06/vocabulary-humanitys-greatest.html

The Methods section is explicit about how things were calculated, one step at a time: a model approach to be commended.

 

WAIS subtest heritabilities

The culturally loaded tests have higher heritabilities.

The authors conclude:

Each subtest’s proportion of variance in IQ shared with general intelligence was a function of cultural load: The more culture loaded, the higher this proportion. In addition, in adult samples, culture-loaded tests tended to have greater heritability coefficients than did culture-reduced tests, and there was a relationship between subtest’s proportion of variance shared with general intelligence and heritability. In child samples, these relationships were in the same direction, but correlations were small and insignificant.

They sound a cautionary note about the data, but their substantive point is:

A correlation between, for instance, g loading and heritability coefficient is in line with the hypothesis that the g factor is the most heritable factor (Jensen, 1998), but a test of the significance of this correlation does not provide the means to test whether the g factor is indeed the most heritable factor1 (Dolan & Hamaker, 2001). The method merely serves to evaluate competing theories of intelligence (Rushton & Jensen, 2009): A significant correlation denotes that a phenomenon exists that is in need of theoretical explanation. Theories that account for the correlation are stronger (with respect to this correlation) than are theories that do not account for it or are silent about it. The same line of reasoning holds for the correlations of cultural load with g loadings and heritability coefficients.

Having given their conclusions, the team then go against normal sequence and start a discussion.

Our result showing that culture-loaded knowledge tests (crystallized tests) are more strongly related to general intelligence than are culture-reduced cognitive processing tests (fluid tests) fits better with the idea that g loadings reflect societal demands (Dickens, 2008) than that they reflect cognitive demands (Jensen, 1987). Furthermore, in adult samples, our finding that the heritability coefficients of culture-loaded tests tend to be larger than those of culture-reduced tests calls for an explanation, given that this result does not follow from the subtest-complexity and investment hypotheses of g theory and fluid-crystallized theory.

After discussing some options they plump for genotype-environment covariance.

Because the acquisition of knowledge depends on cognitive processing, individuals who develop relatively high levels of cognitive-processing abilities tend to achieve relatively high levels of knowledge. High achievers are more likely to end up in cognitively demanding environments that encourage and facilitate the further development of a wide range of knowledge and skills. The contents and organization of these environments largely reflect societal demands. These societal demands thus influence the degree of dynamical interaction among cognitive processes and knowledge and, hence, their intercorrelations. In this way, the societal demands determine IQ-subtest loadings on the general factor of intelligence and, eventually, the degree to which broad-sense heritability coefficients of IQ subtests include the effects of (growing) genotype-environment covariance. In view of theoretical parsimony, we conclude that the assumption of a true causal g can be incorporated but that this is not required.

This paper presents interesting, counter-intuitive findings, which deserve replication on other samples and other psychometric tests. As to their favoured genotype-environment effect, I don’t see how bright people can obtain high levels of knowledge without being bright in the first place. They don’t develop intelligence, they have that ability in varying degree and use it to develop their knowledge to varying degrees. I am still working this out, but I think that ability is prior, and therefore more likely to be causal.

See what you think.

Monday, 28 September 2015

Blood Moon: Recalling Eratosthenes

 

Although the Observatory at Greenwich still be-straddles the globe as the origin of longitude, and thus of Time itself, London long ago ceased to be a good vantage point for examining the heavens. Anthracite coal conquered the world, but it besmirched London’s skies, and then the Clean Air Act coincided with ever-stronger electric street lighting, so light replaced soot as the celestial pollutant, fading distant stars. Of more moment, British skies are always covered with clouds, so astronomy is well-nigh impossible. And yet, and yet, last night the London sky was sparkling clear, so the whole supermoon lunar eclipse was visible for the seven stages from first to final contact.

At this numinous and transient moment I sleepily tried to explain to myself what was happening. The earth was travelling round the sun, but not at a speed sufficient to account for what I was observing. The earth was rotating on its axis, but rotation does not cause shadow. The moon was apparently fixed in the sky, yet it was slowly falling into a shadow caused by the nearest heavenly body, the Earth, and the atmosphere of that home planet was causing selective filtering of light-waves, taking out the shorter ones, and leaving the red.

If Eratosthenes, the third-ever Chief Librarian of the great library at Alexandria, had been standing beside me at my London window, he would have been the perfect teacher, had he not, as would have been more likely, been using the event to avoid chit-chat and make his own observations and calculations.

http://drjamesthompson.blogspot.co.uk/2014/11/the-puzzle-comes-before-solution.html

Astronomical events were the first and greatest of puzzles faced by our ancestors, the stuff of creation myths, superstitions, rituals and eventually sceptical surmise: the dawn of science. Astronomy required a leap of understanding: that the all too solid earth on which we stand might also be just one hurtling dot among the many visible (and invisible) one in the skies. Tycho Brache, the last of the naked-eye astronomers, was chronicling the regressive paths of the planets, but could not fully agree with Copernicus’ interpretation of those wandering planets in terms of the Earth’s own orbit round the sun.  The Copernican shift of perspective was a leap of Piagetian proportions, in which an observant maturing child eventually understands that what they see, and what a doll placed in an assembled mini-landscape sees, are not one an the same thing. The ego-centric perspective of early childhood is attenuated by a growing appreciation of the perspectives of other minds. It is similar in intellectual status to a growing child noticing that kindergarten children are becoming smaller, but eventually realizing that is only because he has grown bigger, not because new generations have shrunk.

How well do contemporary citizens understand astronomy? I should add, understand it without looking it up and repeating it, only to fall into ignorance again? If the Flynn Effect is real, then it will be far easier for average persons to understand eclipses, night and day, summer and winter. I do not have up to date data on pass rates, but here is an interesting finding from a random survey of British adults in 1992, which is 122 years after the 1870 Education Act and 472 years after the publication of Copernicus’ De revolutionibus orbium coelestium in 1543.

John Durant, Geoffrey Evans and Geoffrey Thomas. (1992) Public understanding of science in Britain: the role of medicine in the popular representation of science. Public Understand. Sci. 1 161-182.

 

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So, 30% of British adults thought that the observed passage of the sun in the sky meant that our star obligingly whizzed round us. 16% imagined it did so once a day, as per visual observation of the same apparent phenomenon. More recent findings gratefully received.

If I concentrate on matters involving events observable to our ancestors, and avoid calendrical calculations, science education websites show that popular misconceptions still include the following: that the phases of the moon are caused by the moon going into and out of the earth’s shadow; that the moon has a side which is in perpetual darkness; that the moon does not rotate; that the phases of the moon are completed in exactly the number of days it takes to completes its orbit of the earth; that the moon is somehow larger on the horizon than when it is high in the sky; that the four seasons are the result of the changing distance from the sun; and that heavier objects fall faster than lighter objects.

I know that we no longer live on the land, and therefore are more distant from nature, and from the peregrinations of the sun and moon. I know that ignorance about astronomy is very largely a matter of education, but it is likely also that some education has been given but was not retained, because egocentric observation is deemed sufficient by many people. I know that I can make errors, and that many people make errors in simple Newtonian physics (imagining that if you drop an object when running it will describe an arc backwards to the ground, not forwards to the ground).  I know all this, but if we were really getting brighter over the last two centuries we would be able to work out much of this for ourselves, as Eratosthenes worked out the circumference of the world when he heard a casual remark about a well to the south of Alexandria where on one particular day of the year the sun shone down to the very bottom of the well.

Just for amusement, here are some Northern hemisphere university graduates explaining the astronomical causes of seasonal variations.

https://www.youtube.com/watch?v=p0wk4qG2mIg

Here are some popular misconceptions tracked down and explained.

http://www.scc.losrios.edu/pag/observatory/44-common-misconceptions-astronomy/

http://www.astronomy.org/astronomy/misconceptions.html

So, these were some thoughts whilst watching the super-moon lunar eclipse last night, among the blazing street lights of urban London. If by some magical process Eratosthenes had stood next to me I am sure that I would have best served him only by listening to him attentively.

Sunday, 27 September 2015

600,000

On 19 June the blog reached 500,000 and just a moment ago, 102 days later, it achieved 600,000. I am aware that most citizens will continue with their post-Sunday lunch nap, but I judge that my select group of readers will at least raise one eyebrow before returning to their even more serious reading. The total is far higher than I conceived possible when I began the blog two years and 10 months ago, when I felt lucky if I got 20 readers a day. The current daily page-view rate is roughly a thousand.

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The snapshot of the past month shows a pronounced ISIR conference peak, and the most popular posts in that period are all about the conference.

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The all-time greats remain the familiar old posts, with a few additions in the lower ranks:

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Where do readers come from?

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Readers are almost 6 times more likely to be in the US than the UK. The peak age for readers is 18-35 range, going down gradually to age 65+. So, the message is getting through to those who have most of their working life ahead of them, and might make decisions based on intelligence results. Readers are interested in science, news and politics. In terms of how they get to the blog, last month 4080 visitors came directly (loyal established readers?)  3912 through social media (loyal plus new readers?)  2822 through “organic search” (searchers for knowledge?) and  2634 through referral (new readers willing to admit they are searching for knowledge?).

There is a tendency for the longer essays to get correspondingly longer reading times, suggesting readers stick with the content. The item on whether Asians were bright but lacking in curiosity made people read for 6 minutes, whilst shorter conference announcements got half that duration of attention, all consistent with visitors being real readers.

Twitter is my hyper-active front-runner for the slower meditative page-turners of my blog. Precis is good for the mind. I have a few more followers (now at 1,262) which is welcome. Of course, I want the right sort of followers: those who contribute to knowledge, even when they just ask questions. I tweet sparingly (on average 3 or 4 a day) and virtually always only about blog posts or published work. I get 107 retweets per 100 tweets, and almost always respond to tweets with further answers.

 

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Request: Could I ask university teachers and researchers to select one of their students, and get them to critique one of my posts, or to take up one of the suggestions for further research? It would be good to have more psychology student readers (not that I know how many of my readers are in that category) and I think that will come if psychology teachers get their students to have a look at the blog.

If you have any suggestions for getting more blog readers please let me know.

The Donate button is down on the bottom right. Just one gentle press does the trick. $35 buys readership of a pay-walled paper (this is just a price guideline) $20 buys a printer ink cartridge, $15 any number of coloured pencils. What more do I need, other than to keep up my enthusiasm, secure in the knowledge my readers are changing the world?

Thursday, 24 September 2015

Types of psychology lecture

 

It was said of Presidential Addresses at the British Psychological Society Annual Conference that they fell into three types:

Whither Now?

Patients I have Cured

5-hydroxy-triptamine

These three encapsulated the philosophical, clinical and physiological traditions in the society.

With that in mind, I have looked back at the very recent International Society for Intelligence Research conference in Albuquerque to see if I can detect a classificatory structure, tripartite or otherwise. Here, without too much poetic licence, is a possible troika of themes:

Technical: use of statistics and modelling techniques, understanding the limitations and characteristics of particular intelligence measures, arguing about the hierarchical structure of intelligence

Correlational: Real-life associations with IQ, and examples of the predictive power of intelligence.

Genetic: the genetic underpinnings of intelligence and related behaviours.

The technical theme is very specialised. It makes crucial points about intelligence measures and how results can be modelled and analysed. Tracking down whether tests show “measurement invariance” is essential if you want dependable findings. Understanding all this is crucial for researchers. Speaking personally, I find some of the discussions about the structure of group factors less interesting.

The correlational theme is enormous in scope, and accounts for the bulk of published results. Intelligence runs through psychology like carbon through biology. All of human life is there. Intelligence is the most replicated result in psychology, and with the largest sample sizes, sometimes in the millions. There is much still to learn, and the results keep coming in.

The genetic theme is transformational. This is the leading edge of intelligence research. The tempo seems to be about one major publication every 2 or 3 months. Sample sizes are usually above 100,000 and sometimes 300,000. These papers usually find links between the genome and human behaviour which are statistically significant but moderate in effect size, and very probably caused by very many genes of small effect, and which also have effects on other things. I get forewarning of a few of these publications, and will comment further when papers in the review pipeline get published. Tracking down the genetics of intelligence is happening now, with impacts which most people don’t yet appreciate.

The classificatory scheme is a mere sketch, and very open to counter-claims. It might be better to follow the path outlined by Borges in classifying animals in “Celestial Emporium of Benevolent Knowledge” : Those that belong to the Emperor; Embalmed ones; Those that are trained; Suckling pigs; Mermaids; Fabulous ones; Stray dogs; Those that are included in this classification; Those that tremble as if they were mad; Innumerable ones; Those drawn with a very fine camel hair brush; Those that have just broken the flower vase;  Those that resemble flies from a distance.

Perhaps all lectures should be judged by the criterion “Have they just broken the flower vase?”

 

Sunday, 20 September 2015

#ISIR15 ends, celestial carriages await

 

So, thus ends a stellar conference.

One of the delights of a conference is to sit next to like-minded and knowledgeable confederates who feed me comments, evaluations and questions which need to be asked. The audience should have the last word. So, here is a selection of what such persons said to me about the talks.

James Lee’s talk went very well. At the beginning I thought it was an over-sell, but boy, the flow of his argument is terrifically clear.

I heard a lot of audience reaction after Steve Pinker's talk.  Comments like 'inspired, entertained, definitely going to try harder to write more clearly'.  There was quite a podium-rush after his talk - felt for his safety! Really good to have the hall ringing with laughter at the end of a long day.

PhD student Sephira Ryman gave a standout talk.  She asked: since men and women have similar mean intelligence, yet women have smaller brain sizes, are there other features that differ?  She found that gray matter volume is important for men, but white matter network connectivity was more important for women. Evidence from her sample of 244 persons that men and women may arrive at their intelligence by slightly different means.

Paul Sackett and Nathan Kuncel utterly destroyed the idea that SAT tests do not predict college performance. Their "ginormous" dataset comprised over a million students. A droll and data rich talk, they left myths about the non-utility of standardised tests lying like road-kill on the highway of evidence.

PhD student Helen Davis gave a fascinating talk that contrasted the spatial abilities and mobility patterns of two traditionally-living (forager-horticulturalist) peoples: the Maya and the Tsimane.  The lifestyle and ecology differ between the societies and this is reflected in their spatial abilities and movement patterns. The typically found sex difference in spatial ability (men outperform women) was only found in the Maya where men travel greater distances to find food for their children.

Alice Dreger. Simply barnstorming. Brilliant, and packed with rich content.  We must keep in contact with her.

Tim Bates' talks are consistently a highlight of any meeting he speaks at.  His careful replications, showing null results of famous memes that tear through the classroom like flu, are a pleasure to hear.

IN CONCLUSION – See you in St Petersburg, 15-17 July 2016

http://www.isironline.org/category/conferences/

Russian and UK school kids

 

CROSS-CULTURAL INVESTIGATION INTO TEACHER/CLASSROOM EFFECTS ON ACADEMIC PROGRESS IN RELATION TO MOTIVATIONAL FACTORS*

Elaine White1,2 , Margherita Malanchini1,2 , Dina Zueva2 , Olga Bogdanova2 , Yulia Kovas1,2

1 Goldsmiths, University of London, UK, e.white@gold.ac.uk.

2 Tomsk State University, Russia.

Research suggests that within any country, almost the whole spectrum of individual variation in academic achievement is observed in any school or classroom, with only a small portion of within-population variance attributable to differences across teachers, classes and school (e.g. Asbury et al., 2008).

It may be that shared effects of class/teacher are weaker or stronger as a function of such factors as teacher training, curricula, educational norms, and cultural stereotypes (e.g. Kovas et al., 2013). As longitudinal research into teacher/classroom effects are limited to date and neglect the contribution of non-cognitive factors, this study investigates teacher/classroom effects on academic achievement, across several points of the academic year in two countries.

This longitudinal study follows 622 11-12 year old Russian and UK secondary school students at several waves across one academic year. As students have subject-specific teachers for the first time in their education, comparisons can be made between their classrooms for two subjects, maths and geography. The students from 3 urban schools completed a range of tests and self-report questionnaires during their maths lesson. Data were collected to assess cognitive and non-cognitive factors in relation to academic progress. The students’ school achievement data were also obtained.

We explore differences: across the two countries; within and between classes; across the two school subjects; and motivational factors. Preliminary results (from the first 3 waves) suggest stability of the measures, maths ability and maths self-efficacy, over time. A reciprocal relationship was shown between maths ability and maths self-efficacy across time 1 and time 2. This suggests that higher performance increases self-efficacy and higher self-efficacy increases performance. This reciprocal relationship remains when controlling for IQ and the relationship strengthens between ability at time 1 and self-efficacy at time 2. A negative relationship, which appears between ability at time 2 and self-efficacy at time 3, is likely to be the result of performance feedback.

This research investigates potential differences between Russian and UK education systems comparing classroom environments of mathematics in contrast to geography. Although taught and utilised differently, both academic subjects contain similar attributes. Both Russian and UK secondary school students have specific subject teachers for the first time in their education. UK students have the same teacher for all subjects during primary school and changes yearly, whereas Russian students have the same teacher throughout the four years of their primary education. The study therefore provides an ideal comparison of cognitive and non-cognitive factors across subject and classroom environments. Identifying factors moderating classroom effects is important for educational policy and provision.

Remember the 7 tribes of intellect

 

Take a dozen eggs. Better still, take several dozen eggs and compare them to another several dozen eggs. Eggs are eggs, and an omelette make.

However, from the individual differences perspective, humans differ. Brighter kids learn faster, about 5 times faster than their slower classmates. Take a whole school district and you will find a few children who learn 7 times faster, hence

http://drjamesthompson.blogspot.co.uk/2013/12/the-7-tribes-of-intellect.html

Here’s a deal: we will improve our experimental designs if they will measure, even very briefly, the ability and personality of their experimental subjects.Even a simple brief vocabulary test, plus a digit span test or speeded coding task would provide useful information, and if parents could be persuaded to do the same we would have a handle on a major source of unexamined variance in experimental designs.

As Sara says: There is a world outside of experimental designs

USING INTELLIGENCE TO PREDICT RESPONSE-TO-INTERVENTION: AN APPLICATION OF INTEGRATIVE DATA ANALYSIS IN PROJECT KIDS

Sara A. Hart Florida State University, hart@psy.fsu.edu.

https://psy.fsu.edu/faculty/hart.dp.html

There has been a growing body of work, which suggests that the individual traits that a child brings into an intervention project have an interactive effect on literacy learning. Even within intervention studies shown to be impactful at the mean level, there are individual differences in how children responded to the intervention.

I contend that there are numerous (typically unmeasured) sources of these individual differences, and for this talk I will present data examining the role of both crystallized and fluid intelligence in predicting individual differences in response-to-intervention, with data pooled across multiple projects allowing for generalization beyond any given intervention protocol. Integrative Data Analysis (IDA; Curran & Hussong, 2009) was used to create a pooled source of Project KIDS raw data of 545 kindergarten and first grade children (age M = 5.6yrs) who had previously participated in one of three literacy-based randomized control trial interventions in the treatment group.

IDA allows for raw data from each project to be combined and heterogeneity, such as age and project, controlled for. Reading was measured as pre- and post-intervention scores on the Woodcock Johnson Tests of Achievement Letter-Word Identification (LWID) subtest, crystallized intelligence was measured using a pre-test mean raw score across the KBIT-2 Verbal Knowledge and Riddles subtests, and fluid intelligence was measured using a pre-test raw score from the KBIT-2 Matrices subtest.

As a first step of IDA, a moderated nonlinear factor analysis was used to create scale scores which are project invariant for the constructs of interest. I then used Proc Mixed to calculate covariance adjusted scores to model change from pre-test to post-test for LWID, operationalizing “response-to-intervention”. Quantile regression was then used to model both crystallized and fluid intelligence predicting response to-intervention.

The models indicated that both crystallized and fluid intelligence were statistically significant predictors across the distribution of response-to-intervention, although for both, the effect was statistically greater for the students who made the greatest gains due to the intervention.

These results indicate that brighter children do even better in an intervention that is impactful for most students. Although certainly not surprising for the audience of ISIR, child traits such as intelligence are not often included in determining response-to-intervention in education studies, and I argue that it is important moderator that should be considered. Beyond these specific findings, I will discuss how we will use these pooled data to exploring many other sources of moderation of response-to-intervention, including other cognitive traits, behavioral traits, the environment and family history. This work will expand the understanding of how and why some children are more successful when receiving gold standard educational interventions.

Older fathers still have bright children

 

This is an interesting paper, but I note it refers to European populations. It may not hold true of societies in which many children are the product of older men accumulating many younger wives.

 

PATERNAL AGE AS AN INDICATOR OF NEW MUTATIONS: CHILDREN OF OLDER FATHERS HAVE LOWER EVOLUTIONARY FITNESS, BUT NOT LOWER INTELLIGENCE

Ruben C. Arslan 1 , Kai P. Willführ 2 , Emma M. Frans 3 , Mikko Myrskyla 4 , Catarina Almqvist 3 & Lars Penke

1 Georg August University Göttingen, Germany, ruben.arslan@gmail.com.

2 MPI for Demographic Research, Rostock, Germany.

3 Karolinska Institut, Stockholm, Sweden.

4 MPI for Demographic Research, Rostock, Germany.

Ruben Arslan

https://www.psych.uni-goettingen.de/en/biopers/team/arslan

 

Paternal age at offspring conception seems to be the main driver of single nucleotide de novo mutations (Kong et al.., 2012). Different theories posit that intelligence is linked to mutation load as a fitness indicator or simply owing to its genetic complexity. Based on evolutionary genetic theory we predicted negative paternal age effects on offspring fitness and intelligence in the normal range. To investigate effects on fitness, we used church records from three pre-industrial Western populations and governmental data from 20th century Sweden. We used a sibling control design and accounted for confounds including maternal age, birth order and parental loss. Main analyses had an aggregate N > 1.3 million.

To investigate effects on intelligence, we compared siblings in the German Socio-Economic Panel (N = 1479). Furthermore we were the first to directly adjust for measured parental intelligence, the most obvious confound, in data from the Minnesota Twin Family Study (N = 1898 twin pairs). We found clear support for mutational paternal age effects on offspring survival, mating and reproductive success. Weaker effects were found in 20th century Sweden, possibly indicating a diminished strength of purifying selection. However, we found no mutational paternal age effect on offspring intelligence, which was corroborated further by a Swedish study of half a million men (D’Onofrio et al.., 2014).

Although paternal age effects seem to be an appropriate way to characterize the effect of de novo mutations on fitness, no effect was found on intelligence in the normal range. Genomic research supports this result. The inferred genetic architecture of intelligence does not seem to make it fragile and vulnerable to increases in paternal age-driven mutation or to decreases in purifying selection.

Creativity and fluid intelligence

 

Finally, Brazilians take the stage, in the form of Paulistano Ricardo Primi, who gives a creative take on creativity, looking at the difficult-to-measure genre of figural drawing. Brazil needs to figure more in international intelligence research, particularly on the large matter of genetic differences, since Brazil’s history is very different from that of the US, and the contrast can provide a test of cultural explanations for black/white intelligence differences. That bigger project will have to wait, but here is what they have done on their drawing task, also using Bootstrap to test model fit.

 

CREATIVITY AND FLUID INTELLIGENCE: MIXTURE GROWTH MODELING OF INTRA INDIVIDUAL PATTERNS OF PERFORMANCE DURING A DIVERGENT THINKING TASK OF FIGURAL DRAWING

Ricardo Primi 1 , Nelson Hauck-Filho 1 , Tatiana de Cássia Nakano 2

1 Universidade São Francisco, rprimi@mac.com.

2 PUC-Campinas.

https://www.researchgate.net/profile/Ricardo_Primi

 

This study examines the association of fluid intelligence and creativity. In divergent thinking tests it is common to observe that later responses tend to be more creative than earlier ones – this is called serial order effect. Recent view of the role of executive function on divergent production predicts that high fluid intelligence subjects will have creative responses already in the beginning of divergent thinking tasks. This indicates a central role of executive functions –inhibiting common less creative responses and management interference on idea production.

Most studies observing these relationships are done in verbal tasks. This research tests if this relationship can be found on divergent productions of figural drawings. Participants in the present study were 585 children and high school students with ages from 7 to 17 (mean = 11.11 years, SD = 2.02; 52.5% female). All participants provided demographic information on a self-report questionnaire, and undertook a cognitive assessment battery (verbal, abstract, logic and numeric reasoning) supplemented by a creativity task, whose data we analyzed in the present study.

This creativity task consisted of 10 stimuli, which participants were required to complete using paper and pencil. Independent raters subsequently coded each resulting drawing in a scale from 1 to 5 to reflect the extent to which it approached a set of criteria defining creative responses. Data analysis was conducted using Mplus 7.11. Factor growth mixture modelling were performed in order to detect groups of potentially differing patterns of performance (ratings) from the first to the last stimulus of the task.

Bayesian Information Criterion (BIC) and the Bootstrap Likelihood Ratio Test (BLRT) suggested that a three-class solution was a better fit to the data (entropy = .77) when compared to alternative 1-, 2-, and 4-class solutions. Latent classes revealed a large group (83.36%) of individuals with initially modest scores and descending performances along the 10 stimuli, as well as two small groups of individuals with high initial scores—one (12.52%) with a descending performance, and the other (4.12%) with a stable high performance across the whole task.

Last two groups have significantly higher scores in Gf. This study shows that executive processes of top down voluntary control are important components for production of creative responses. This demonstrates a higher role of intelligence on creative idea production. It shows a high role of fluid intelligence in idea production.

Sex differences in chattering and counting

 

People come in two types: those that chatter and those that count.

Women are more likely to chatter, men to count. Women incline to non-STEM subjects, men to STEM; as a consequence they go on to have different jobs and careers.

For both sexes, chatterers turn to humanities, counters to STEM.

This may be evidence of a sex difference.

Tom and his team’s excellent work makes it plain that there are some natural inclinations and ability profiles (tilts), not only between sexes, but within sexes and between those with different cognitive abilities. I don’t see this as something which needs remediation and some special campaign (and doubt that Tom thinks so). By all means offer maths classes and writing classes to those that want them. Indeed, offer them to those that don’t want them, so that the Two Cultures don’t divide permanently.

http://sciencepolicy.colorado.edu/students/envs_5110/snow_1959.pdf

 

 

http://colfa.utsa.edu/psychology/faculty/thomas_coyle

 

SEX DIFFERENCES IN ABILITY TILT

Thomas R. Coyle, Miranda C. Richmond and Anissa C. Snyder, University of Texas at San Antonio, thomas.coyle@utsa.edu.

Although g is the best predictor of life outcomes (academic achievement), non-g factors may also predict such outcomes. One non-g factor with predictive validity is ability tilt, the difference in math and verbal scores on tests (SAT). There are two types of tilt: math tilt (math>verbal) and verbal tilt (verbal>math). Whereas prior studies have examined tilt in the profoundly gifted (1 in 10,000 in ability), the current study examines sex differences in tilt in nongifted subjects. Nongifted subjects show fatter ability profiles (less tilt), which may lower the predictive validity of tilt.

Unlike prior studies of nongifted subjects, the current study is the first to examine sex differences in tilt for outcomes after college (occupations, but also college majors and specific abilities).

Subjects (866 males and 1084 females) were drawn from the National Longitudinal Survey of Youth, a representative sample in the U.S. Tilt was based on math minus verbal scores on the SAT, ACT, and PSAT (in high school). College majors were STEM majors (science, technology, engineering, math) and humanities majors (English, history, languages). Occupations (around age 30) were STEM jobs (chemist, biologist, engineer) and verbally-loaded jobs (media, law, counseling). Specifc abilities (math, verbal) were based on the Armed Services Vocational Aptitude Battery (ASVAB).

Sex differences in levels (or frequency) of tilt were examined with ANOVAs (chi-squares), and tilt relations with specific abilities were examined with structural equation modelling. Significant effects are reported at p<.05. Tilt was unrelated to g (based on the ASVAB) for males and females (r < .10), confirming its non-g status.

Math tilt (math>verbal) on all tests (SAT, ACT, PSAT) was more common for males, whereas verbal tilt (verbal>math) was more common for females. In addition, STEM majors and jobs were more common for males, whereas humanities majors and verbally-loaded jobs were more common for females. For both sexes, STEM majors and jobs were associated with math tilt, and humanities majors and verbal jobs were associated with verbal tilt (r ~ .35). Also for both sexes, math tilt predicted math ability (on the ASVAB), and verbal tilt predicted verbal ability (betas ~ .30), confirming the construct validity of tilt.

The results were confirmed for all tests (SAT, ACT, PSAT). Tis study is the first to examine sex differences in tilt for nongifted subjects. Tilt was unrelated to g, confirming its non-g status, but still differentiated males and females. Males tended to show math tilt, which predicted STEM outcomes, whereas females tended to show verbal tilt, which predicted verbal outcomes. The absence of sex differences in tilt relations (with jobs and majors) suggests that males and females with math tilt prefer STEM whereas those with verbal tilt prefer humanities.

An important question for public policy is why fewer females show math tilt (which may reduce STEM participation). Future research will examine tilt at earlier ages (elementary school) and also examine other abilities (spatial ability) that may contribute to sex differences in tilt and STEM.