Vanderbilt

Sorry for the lack of posts! I've been at Vanderbilt since leaving Fermilab. I was pretty busy giving two talks and meeting with a lot of physics faculty during my visit. As always I am amazed at the variety of things people are working on in a single department. Vanderbilt has a beautiful campus :-)

I've collaborated with two Vanderbilt theorists: Tom Kephart and Bob Scherrer, but this was my first visit to the university.




I had a brief window of time to meet with psychology professors Camilla Benbow and David Lubinski, who co-direct The Study of Mathematically Precocious Youth (SMPY). The data set they've been accumulating is unique and valuable.

SMPY:

The Study of Mathematically Precocious Youth (SMPY) was founded by Julian C. Stanley, on 1 September 1971, at Johns Hopkins University. Camilla P. Benbow and David Lubinski co-direct SMPY at Peabody College of Vanderbilt University. They are planning to complete a 50-year longitudinal study of five cohorts, consisting of over 5,000 intellectually talented individuals, identified over a 25-year period (1972-1997). The aim of this research is to develop a better understanding of the unique needs of intellectually precocious youth and the determinants of the contrasting developmental trajectories they display over the lifespan. The Study of Mathematically Precocious Youth is a bit of a misnomer, however, because verbally precocious youth have been included for longitudinal tracking, and participants are now all adults. Nevertheless, "SMPY" has been chosen to be retained to maintain consistency.

Four of SMPY's five cohorts were identified by talent searches by age 13. These cohorts vary in ability level ranging from the top 3% to the top .01% in quantitative or verbal reasoning ability. A fifth cohort of 714 participants, identified as first- or second-year graduate students attending top U.S. math/science programs in 1992, complements the first four cohorts of talent search participants by, among other things, affording an opportunity to assess the generalizability of the talent search model for identifying scientific potential. A 10-year follow-up of these math/science graduate students is now available (Lubinski et al., 2006). For the first three SMPY cohorts (identified in 1972-1974, 1976-1978, & 1980-1983, respectively), their 20-year follow-ups are available (Benbow et al., 2000; Lubinski et al., 2006). SMPY either has or is planning to follow-up all four cohorts of talent search participants at ages 18, 23, 33, 50 and 65. Cohort 5, the math-science graduate students, will be followed-up at ages 35 (complete) as well as 50 and 65. So far, seven books and over 300 articles have been based on SMPY; many recent articles are on PDF files on Benbow and Lubinski's individual web sites. For further and more detailed information on SMPY's history, the selection criteria for each cohort, and major longitudinal findings, a recent monograph has just appeared (Lubinski & Benbow, 2006).

SMPY at 50: Research Associate position

I'm posting the job ad below for David Lubinski. The Study of Mathematically Precocious Youth (SMPY) is the most systematic long term study of individuals of high cognitive ability since the Terman Study.

SMPY helps to establish a number of important facts about individuals of high ability:

1. We can (at least crudely) differentiate between individuals at the 99th, 99.9th and 99.99th percentiles. Exceptional talent can be identified through testing, even at age 13.

2. Probability of significant accomplishment, such as STEM PhD, patents awarded, tenure at leading research university, exceptional income, etc. continues to rise as ability level increases, even within the top 1%.

3. There are systematic differences in cognitive abilities and profiles in different fields (business, medicine, engineering, physics, etc.)

4. Men and women of exceptional ability differ in life aspirations and preferences.

No one can claim to understand high level human capital, technological innovation, scientific progress, or exceptional achievement without first familiarizing themselves with these results.

Needless to say, I think this Research Associate position will entail important and fascinating work.

Research Associate:

The Study of Mathematically Precocious Youth (SMPY) seeks a full-time post-doctoral Research Associate for study oversight, conducting research, writing articles, laboratory management, and statistical analyses using the vast SMPY data base. SMPY is a four-decade longitudinal study consisting of 5 cohorts and over 5,000 intellectually talented participants. One chief responsibility of this position will be to manage laboratory details associated with launching an age-50 follow-up of two of SMPY’s most exceptional cohorts: a cohort of 500 profoundly gifted participants initially identified by age 13 in the early 1980s, and a second cohort of over 700 top STEM graduate students identified and psychologically profiled in 1992 as first- and second-year graduate students. Candidates with interests in assessing individual differences, talent development, and particularly strong statistical-technical skills are preferred. Send vitae, cover letter stating interests, (pre)reprints, and three letters of recommendation to: Dean Camilla P. Benbow, Department of Psychology & Human Development, 0552 Peabody College, Vanderbilt University, Nashville, TN, 37203. The position will remain open until a qualified applicant is selected. For additional information, please contact either co-director: Camilla P. Benbow, camilla.benbow@vanderbilt.edu, or David Lubinski, david.lubinski@vanderbilt.edu.

http://www.vanderbilt.edu/Peabody/SMPY/. Vanderbilt University is an Equal Opportunity/Affirmative Action Employer.

We are aiming for a June 30th start date but that’s flexible.

Some relevant figures based on SMPY results of Lubinski, Benbow, and collaborators. See links above for more discussion of the data displayed.

Annals of Psychometry: Wordcels and Shape Rotators

Fun with psychometrics! 

Did it all start with High V, Low M, a 2011 post about Stephen J. Gould?

A famous theoretical physicist once complained acerbically to me about someone's paper we were discussing:

It is nothing more than the calculus of words.

Yet there are people who have nothing more than the calculus of words with which to build their models of the world. See Bounded Cognition, and Oppenheimer:

Mathematics is "an immense enlargement of language, an ability to talk about things which in words would be simply inaccessible."

From A Song of Shapes and Words by Roon.

There are many verbally gifted writers and speakers that, when pressed to visualize some math problem in their mind's eye, must helplessly watch their normally high-octane intelligence sputter and fail. They often write or talk at a blistering clip, and can navigate complex mazes of abstractions — and yet, when it comes time to make contact with the real world or accomplish practical tasks, they may be helpless. They'll do great in English class, and terrible in Physics. They can be very fun to listen to due to their terrifying leaps in logic and the exceptional among them will be natural leaders. 

The wordcel moniker describes more than just one’s level of verbal skill: it’s also a socioeconomic classifier that refers to people whose verbal ability borders on self-sabotage (thus the “-cel”). Perhaps they’re driven mad by political rage, postmodernism, and disconnection from reality. It might refer to the priestly figures who work in the culture factories of the New York Times with their incomes and social prestige both precipitously declining only for the unperturbed masses on the internet to tell them in unison: “learn to code”! There’s even an implication that these folks are entirely rent-seekers (wrong, but directionally interesting). 

... 

The shape rotators have been a minor force until very recent history. Though they’ve produced a significant portion of human progress through feats of engineering excellence, they were rarely celebrated until the dawn of the Enlightenment, perhaps 500 years ago. While the long-lasting glory of the Roman aqueducts is renowned to this day, nobody knows the chief engineer behind the project (probably Marcus Vipsanius Agrippa, but who’s counting). Today their stock is climbing to the moon. The world’s richest (self-made) men are almost uniformly engineers, computer scientists, or physicists. Vast portions of society that in a prior age might have been organized by government bureaucrats or private sector shot-callers have been handed over to cybernetic self-organizing systems designed and run by mathematical wizards. We have been witness to the slow, and then rapid transfer of power from the smooth-talking Don Drapers of boardroom acclaim to the multi-armed bandits of Facebook Ads. 

It’s clear that these big tech CEOs are verbally gifted, but by affinity and by practice they are in the rotator camp. Elon continually attributes his success to studying physics in college. Zuck programmed the original iteration of Facebook himself. Larry & Sergei did an entire PhD in linear algebra based information retrieval, a platonic ideal of shape rotation. Of the ten largest companies in the world, several are driven by fundamental technical breakthroughs. Society at large seems to respect and fear the forces of technology more and more as its cultural and financial capital rises.

There is some conflation between Math ability and Spatial ability in this recent talk of Wordcels and Shape Rotators. Math and Spatial ability are positively correlated but are actually separate factors that emerge from PCA in psychometrics. Look carefully at the arrows in the figure below -- if you can't read the figure you might be a wordcel ;-)

Note also that in the SMPY/SVPY data physicists dominated the wordcels even in their own verbal domain. This is also confirmed here.

See post from 2016 reproduced below, especially point #3.

3. There are systematic differences in cognitive abilities and profiles in different fields (business, medicine, engineering, physics, etc.)

This figure displays the math, verbal and spatial scores of gifted children tested at age 12, and their eventual college majors and career choices. This group is cohort 2 of the SMPY/SVPY study: each child scored better than 99.5 percentile on at least one of the M-V sections of the SAT.





Scores are normalized in units of SDs, within this cohort of gifted children. (So above and below average are defined with respect to the gifted population of >99th percentile kids, not relative to the general population.) The vertical axis is V, the horizontal axis is M, and the length of the arrow reflects spatial ability: pointing to the right means above the group average, to the left means below average; note the arrow for business majors should be twice as long as indicated but there was not enough space on the diagram. The spatial score is obviously correlated with the M score. More data here.

SMPY at 50: Research Associate position (2016)

I'm posting the job ad below for David Lubinski. The Study of Mathematically Precocious Youth (SMPY) is the most systematic long term study of individuals of high cognitive ability since the Terman Study.

SMPY helps to establish a number of important facts about individuals of high ability:

1. We can (at least crudely) differentiate between individuals at the 99th, 99.9th and 99.99th percentiles. Exceptional talent can be identified through testing, even at age 13.

2. Probability of significant accomplishment, such as STEM PhD, patents awarded, tenure at leading research university, exceptional income, etc. continues to rise as ability level increases, even within the top 1%.

3. There are systematic differences in cognitive abilities and profiles in different fields (business, medicine, engineering, physics, etc.)

4. Men and women of exceptional ability differ in life aspirations and preferences.

No one can claim to understand high level human capital, technological innovation, scientific progress, or exceptional achievement without first familiarizing themselves with these results.

Needless to say, I think this Research Associate position will entail important and fascinating work.

Research Associate:

The Study of Mathematically Precocious Youth (SMPY) seeks a full-time post-doctoral Research Associate for study oversight, conducting research, writing articles, laboratory management, and statistical analyses using the vast SMPY data base. SMPY is a four-decade longitudinal study consisting of 5 cohorts and over 5,000 intellectually talented participants. One chief responsibility of this position will be to manage laboratory details associated with launching an age-50 follow-up of two of SMPY’s most exceptional cohorts: a cohort of 500 profoundly gifted participants initially identified by age 13 in the early 1980s, and a second cohort of over 700 top STEM graduate students identified and psychologically profiled in 1992 as first- and second-year graduate students. Candidates with interests in assessing individual differences, talent development, and particularly strong statistical-technical skills are preferred. Send vitae, cover letter stating interests, (pre)reprints, and three letters of recommendation to: Dean Camilla P. Benbow, Department of Psychology & Human Development, 0552 Peabody College, Vanderbilt University, Nashville, TN, 37203. The position will remain open until a qualified applicant is selected. For additional information, please contact either co-director: Camilla P. Benbow, camilla.benbow@vanderbilt.edu, or David Lubinski, david.lubinski@vanderbilt.edu.

http://www.vanderbilt.edu/Peabody/SMPY/. Vanderbilt University is an Equal Opportunity/Affirmative Action Employer.

We are aiming for a June 30th start date but that’s flexible.

Some relevant figures based on SMPY results of Lubinski, Benbow, and collaborators. See links above for more discussion of the data displayed.

SMPY in Nature

No evidence of diminishing returns in the far tail of the cognitive ability distribution.

How to raise a genius: lessons from a 45-year study of super-smart children (Nature)

A long-running investigation of exceptional children reveals what it takes to produce the scientists who will lead the twenty-first century.

Tom Clynes 07 September 2016

On a summer day in 1968, professor Julian Stanley met a brilliant but bored 12-year-old named Joseph Bates. The Baltimore student was so far ahead of his classmates in mathematics that his parents had arranged for him to take a computer-science course at Johns Hopkins University, where Stanley taught. Even that wasn't enough. Having leapfrogged ahead of the adults in the class, the child kept himself busy by teaching the FORTRAN programming language to graduate students.

Unsure of what to do with Bates, his computer instructor introduced him to Stanley, a researcher well known for his work in psychometrics — the study of cognitive performance. To discover more about the young prodigy's talent, Stanley gave Bates a battery of tests that included the SAT college-admissions exam, normally taken by university-bound 16- to 18-year-olds in the United States.

Bates's score was well above the threshold for admission to Johns Hopkins, and prompted Stanley to search for a local high school that would let the child take advanced mathematics and science classes. When that plan failed, Stanley convinced a dean at Johns Hopkins to let Bates, then 13, enrol as an undergraduate.

Stanley would affectionately refer to Bates as “student zero” of his Study of Mathematically Precocious Youth (SMPY), which would transform how gifted children are identified and supported by the US education system. As the longest-running current longitudinal survey of intellectually talented children, SMPY has for 45 years tracked the careers and accomplishments of some 5,000 individuals, many of whom have gone on to become high-achieving scientists. The study's ever-growing data set has generated more than 400 papers and several books, and provided key insights into how to spot and develop talent in science, technology, engineering, mathematics (STEM) and beyond.

...

At the start, both the study and the centre were open to young adolescents who scored in the top 1% on university entrance exams. Pioneering mathematicians Terence Tao and Lenhard Ng were one-percenters, as were Facebook's Mark Zuckerberg, Google co-founder Sergey Brin and musician Stefani Germanotta (Lady Gaga), who all passed through the Hopkins centre.

“Whether we like it or not, these people really do control our society,” says Jonathan Wai, a psychologist at the Duke University Talent Identification Program in Durham, North Carolina, which collaborates with the Hopkins centre. Wai combined data from 11 prospective and retrospective longitudinal studies2, including SMPY, to demonstrate the correlation between early cognitive ability and adult achievement. “The kids who test in the top 1% tend to become our eminent scientists and academics, our Fortune 500 CEOs and federal judges, senators and billionaires,” he says.

Such results contradict long-established ideas suggesting that expert performance is built mainly through practice — that anyone can get to the top with enough focused effort of the right kind. SMPY, by contrast, suggests that early cognitive ability has more effect on achievement than either deliberate practice or environmental factors such as socio-economic status.

...

The study's first four cohorts range from the top 3% to the top 0.01% in their SAT scores. The SMPY team added a fifth cohort of the leading mathematics and science graduate students in 1992 to test the generalizability of the talent-search model for identifying scientific potential.

“I don't know of any other study in the world that has given us such a comprehensive look at exactly how and why STEM talent develops,” says Christoph Perleth, a psychologist at the University of Rostock in Germany who studies intelligence and talent development.

...

SMPY 65: Help support the SMPY Longitudinal Study

The Study of Mathematically Precocious Youth (SMPY) needs your help to support the Age-65 phase of their unique longitudinal study. 

For decades, co-directed by David Lubinski and Camilla P. Benbow, SMPY has been a beacon of enlightenment, tracking five cohorts comprising over 5,000 remarkably gifted individuals. In doing so, we have unraveled the secrets to nurturing brilliance. However, we are confronted with a disconcerting reality: the effective methods to identify and cultivate intellectual talent are under siege, threatened by political ideology. 

Our 14-minute documentary and the 3-page feature in Nature underscore the dire need to provide our most gifted youths with the educational opportunities they deserve. They are the architects of solutions and the architects of the future itself. 

Here are some compelling longitudinal findings from SMPY's extensive research:

• Prodigies destined for eminent careers can be identified as early as age 13. 

• There is no plateau of ability; even within the top 1%, variations in mathematical, spatial, and verbal abilities profoundly impact educational, occupational, and creative outcomes. 

• The blend of specific abilities, such as mathematical, spatial, and verbal aptitudes, shapes the nature of one's accomplishments and career trajectory.

More information:

Long

Short

DONATE HERE

Indicate "Please designate this gift to Study of Mathematically Precocious Youth" in the Special Instructions.

Gender trouble in the valley

This NYTimes article looks at the gender disparity in technology career success within the Stanford class of 1994.

NYTimes: In the history of American higher education, it is hard to top the luck and timing of the Stanford class of 1994, whose members arrived on campus barely aware of what an email was, and yet grew up to help teach the rest of the planet to shop, send money, find love and navigate an ever-expanding online universe. ...

I found this reader comment to be realistic -- it is consistent with my own experience both as a parent and as a startup founder.

tiddle nyc

I've been in tech field for some years now. Being a working mother, with two kids (one boy, one girl), this subject hits close to home.

When I first started, there were more women in the ranks than it is now. I never experienced any sexism or discrimination in workplace, nor did I ever feel pushed aside. But I have to say this to my fellow female peers, in order to get ahead, you have to stay in the field. Dropping out or even scaling back will not help, and you can't blame others for not entrusting you with high profile projects because you might not be here next week.

Naturally it helps to have a spouse who share chores and childrearing, rather than having the woman/mother/wife to have-it-all, but really do-it-all which is practically impossible. That's how we stay the course and allow a pathway for younger generations of female to move up the ranks.

Looking at my kids - and we raise them to have the same aspirations, ambitions, and aggressiveness - there is indeed certain nature-vs-nurture difference. Justified or not, my son is almost always over-confident in his ability in all situations whereas my daughter is more circumspect and tentative (even if she's more than capable). It takes a lot more encouragement to prompt my daughter to be aggressive, whereas my son naturally does it on his own. As I look around all those in fields like VC and startups, I see mirrors of how men and women behavior.

This article doesn't surprise me.

See also Gender differences in preferences, choices, and outcomes: SMPY longitudinal study. A longitudinal study of mathematically precocious men and women (SMPY) showed significant gender differences in life and career preferences:

... According to the results, SMPY men are more concerned with money, prestige, success, creating or inventing something with impact, etc. SMPY women prefer time and work flexibility, want to give back to the community, and are less comfortable advocating unpopular ideas. Some of these asymmetries are at the 0.5 SD level or greater. Here are three survey items with a ~ 0.4 SD or more asymmetry:

# Society should invest in my ideas because they are more important than those of other people.

# Discomforting others does not deter me from stating the facts.

# Receiving criticism from others does not inhibit me from expressing my thoughts.

I would guess that Silicon Valley entrepreneurs and leading technologists are typically about +2 SD on each of these items! One can directly estimate M/F ratios from these parameters ...

The anecdote below about serial entrepreneur David Sacks is amusing:

NYTimes: ... Mr. Sacks almost wasn't hired because of doubts that he could work well with others; during his job interview, he put the chief financial officer on notice that his own job would be totally different once Mr. Sacks arrived, Mr. Thiel remembered. But his lack of social grace became an asset, according to Mr. Thiel and other former colleagues. He did not waste time on meetings that seemed pointless, and he bluntly insisted that the engineers whittle an eight-page PayPal registration process down to one.

Everyone knew Mr. Sacks was politically conservative, but in the office, he was less bombastic. He had become a manager, he said in an interview, and did not want to hurt the cohesion of his team. But he and Mr. Thiel now had a setting in which to try out their ideas about diversity and meritocracy. 'In the start-up crucible, performing is all that matters,' Mr. Sacks wrote about that time. He wanted to give all job applicants tests of cognitive ability, according to his colleague Keith Rabois, and when the company searched for a new chief executive, one of the requirements was an I.Q. of 160 -- genius level.

The goal was 'pure meritocracy,' said Amy Klement, one of a small number of women to rise high within the organization. She and other women called Mr. Sacks an effective, relentless, generous boss. But some also wondered how comfortable the men running the company were around them. Lauri Schultheis said that when she interviewed to be PayPal's office manager, and its first female employee -- before even Mr. Sacks arrived -- an engineer asked her, 'Does this mean I have to stop looking at porn? ...

Duke TIP and SMPY

David Lubinski (Vanderbilt) sent me this recent paper, comparing the Duke TIP and SMPY populations.

When Lightning Strikes Twice: Profoundly Gifted, Profoundly Accomplished
DOI: 10.1177/0956797616644735

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.

From the paper:

Over the past 35 years, Duke TIP has assessed more than 2.5 million of the most intellectually talented young adolescents in the United States (Putallaz et al., 2005). It has done so by inviting young adolescents who score in the top 3 to 5% on achievement tests, routinely administered in their schools, to take college entrance exams such as the SAT. For the current study, SAT data on more than 425,000 Duke TIP participants were examined to identify a sample equivalent to Kell, Lubinski, and Benbow’s (2013) in both age and ability level. All participants were enrolled in Duke TIP’s talent search prior to 1995 and had earned scores of least 700 on the SAT-Math or at least 630 on the SAT-Verbal (or both) before reaching age 13— which placed them in the top 0.01% of ability for their age group.

Gender differences in preferences, choices, and outcomes: SMPY longitudinal study

The recent SMPY paper below describes a group of mathematically gifted (top 1% ability) individuals who have been followed for 40 years. This is precisely the pool from which one would hope to draw STEM and technological leadership talent. There are 1037 men and 613 women in the study.

The figures show significant gender differences in life and career preferences, which affect choices and outcomes even after ability is controlled for. (Click for larger versions.) According to the results, SMPY men are more concerned with money, prestige, success, creating or inventing something with impact, etc. SMPY women prefer time and work flexibility, want to give back to the community, and are less comfortable advocating unpopular ideas. Some of these asymmetries are at the 0.5 SD level or greater. Here are three survey items with a ~ 0.4 SD or more asymmetry:

# Society should invest in my ideas because they are more important than those of other people.

# Discomforting others does not deter me from stating the facts.

# Receiving criticism from others does not inhibit me from expressing my thoughts.

I would guess that Silicon Valley entrepreneurs and leading technologists are typically about +2 SD on each of these items! One can directly estimate M/F ratios from these parameters ...

Life Paths and Accomplishments of Mathematically Precocious Males and Females Four Decades Later  (Journal: Psychological Science)

David Lubinski, Camilla P. Benbow, and Harrison J. Kell
Vanderbilt University

Two cohorts of intellectually talented 13-year-olds were identified in the 1970s (1972–1974 and 1976–1978) as being in the top 1% of mathematical reasoning ability (1,037 males, 613 females). About four decades later, data on their careers, accomplishments, psychological well-being, families, and life preferences and priorities were collected. Their accomplishments far exceeded base-rate expectations: Across the two cohorts, 4.1% had earned tenure at a major research university, 2.3% were top executives at “name brand” or Fortune 500 companies, and 2.4% were attorneys at major firms or organizations; participants had published 85 books and 7,572 refereed articles, secured 681 patents, and amassed $358 million in grants. For both males and females, mathematical precocity early in life predicts later creative contributions and leadership in critical occupational roles. On average, males had incomes much greater than their spouses’, whereas females had incomes slightly lower than their spouses’. Salient sex differences that paralleled the differential career outcomes of the male and female participants were found in lifestyle preferences and priorities and in time allocation.

See also these poll results from the Harvard Crimson.

Crimson: ... The gender gap was also apparent in career choice. Men were far more likely to hope to eventually work in finance and entrepreneurship than women, while women were much more likely to aspire to careers in nonprofits and public service, health, and media or publishing. [ Note: these are super high achieving HARVARD kids in the survey, not state-U types ... no one has more "privilege" than they do, so I think it's fair to conclude that they might be expressing their relatively unconstrained actual preferences here. ]

Meanwhile, down on the Farm

Note Added in response to 2020 Twitter mob attack which attempts to misrepresent my views: This blog post discusses the firing of James Damore by Google. It was a sensation at the time in Silicon Valley and made national news. This post is primarily about the scientific content of Damore's memo. Initial media reports describing his memo were very misleading and few people made the effort to read what Damore actually wrote before attacking him. I happened to notice that the Stanford Medical School magazine had (by coincidence) just featured an article on some of the issues discussed by Damore. Whether (below) the Stanford neuroscientist Nirao Shah or the former President of the American Psychological Association Diane Halpern are correct or not about the science, it seems unfair to call Damore a crank if he is simply referencing (in good faith) results in the published scientific literature. The same kinds of results are presented in the article below, written for the alumni of Stanford Medical School.

In the second part of the post below I describe some recent survey results on individual preferences among mathematically gifted men and women who are part of a ~50 year longitudinal study -- they have been studied since childhood. I note specifically that differences in preferences between men and women are not necessarily biological in origin (we simply don't know): they could be the result of sexism in child rearing, schooling, postdoc training, etc.

However, the point is that the survey results are likely descriptive of how actual adult men and women think and feel, and may have implications for labor markets. This is NOT a discussion about ability differences between men and women (all the individuals in the study are mathematically gifted), but rather about preferences concerning life fulfillment, lifestyle, work-life balance, etc. And again, no causation is assumed -- the situation may be entirely due to sexism in society, with zero biological basis.

The Spring 2017 issue of the Stanford Medical School magazine has a special theme: Sex, Gender, and Medicine. I recommend the article excerpted below to journalists covering the Google Manifesto / James Damore firing. After reading it, they can decide for themselves whether his memo is based on established neuroscience or bro-pseudoscience.

Perhaps top Google executives will want to head down the road to Stanford for a refresher course in reality.

Stanford Neuroscience Professor Nirao Shah and Diane Halpern, past president of the American Psychological Association, would both make excellent expert witnesses in the Trial of the Century.

Two minds: The cognitive differences between men and women

... Nirao Shah decided in 1998 to study sex-based differences in the brain ... “I wanted to find and explore neural circuits that regulate specific behaviors,” says Shah, then a newly minted Caltech PhD who was beginning a postdoctoral fellowship at Columbia. So, he zeroed in on sex-associated behavioral differences in mating, parenting and aggression.

“These behaviors are essential for survival and propagation,” says Shah, MD, PhD, now a Stanford professor of psychiatry and behavioral sciences and of neurobiology. “They’re innate rather than learned — at least in animals — so the circuitry involved ought to be developmentally hard-wired into the brain. These circuits should differ depending on which sex you’re looking at.”

His plan was to learn what he could about the activity of genes tied to behaviors that differ between the sexes, then use that knowledge to help identify the neuronal circuits — clusters of nerve cells in close communication with one another — underlying those behaviors.

At the time, this was not a universally popular idea. The neuroscience community had largely considered any observed sex-associated differences in cognition and behavior in humans to be due to the effects of cultural influences. Animal researchers, for their part, seldom even bothered to use female rodents in their experiments, figuring that the cyclical variations in their reproductive hormones would introduce confounding variability into the search for fundamental neurological insights.

But over the past 15 years or so, there’s been a sea change as new technologies have generated a growing pile of evidence that there are inherent differences in how men’s and women’s brains are wired and how they work.

... There was too much data pointing to the biological basis of sex-based cognitive differences to ignore, Halpern says. For one thing, the animal-research findings resonated with sex-based differences ascribed to people. These findings continue to accrue. In a study of 34 rhesus monkeys, for example, males strongly preferred toys with wheels over plush toys, whereas females found plush toys likable. It would be tough to argue that the monkeys’ parents bought them sex-typed toys or that simian society encourages its male offspring to play more with trucks. A much more recent study established that boys and girls 9 to 17 months old — an age when children show few if any signs of recognizing either their own or other children’s sex — nonetheless show marked differences in their preference for stereotypically male versus stereotypically female toys.

Halpern and others have cataloged plenty of human behavioral differences. “These findings have all been replicated,” she says.

... “You see sex differences in spatial-visualization ability in 2- and 3-month-old infants,” Halpern says. Infant girls respond more readily to faces and begin talking earlier. Boys react earlier in infancy to experimentally induced perceptual discrepancies in their visual environment. In adulthood, women remain more oriented to faces, men to things.

All these measured differences are averages derived from pooling widely varying individual results. While statistically significant, the differences tend not to be gigantic. They are most noticeable at the extremes of a bell curve, rather than in the middle, where most people cluster. ...

See also Gender differences in preferences, choices, and outcomes: SMPY longitudinal study. These preference asymmetries are not necessarily determined by biology. They could be entirely due to societal influences. But nevertheless, they characterize the pool of human capital from which Google is trying to hire.

The recent SMPY paper below describes a group of mathematically gifted (top 1% ability) individuals who have been followed for 40 years. This is precisely the pool from which one would hope to draw STEM and technological leadership talent. There are 1037 men and 613 women in the study.

The figures show significant gender differences in life and career preferences, which affect choices and outcomes even after ability is controlled for. (Click for larger versions.) According to the results, SMPY men are more concerned with money, prestige, success, creating or inventing something with impact, etc. SMPY women prefer time and work flexibility, want to give back to the community, and are less comfortable advocating unpopular ideas. Some of these asymmetries are at the 0.5 SD level or greater. Here are three survey items with a ~ 0.4 SD or more asymmetry:

# Society should invest in my ideas because they are more important than those of other people.

# Discomforting others does not deter me from stating the facts.

# Receiving criticism from others does not inhibit me from expressing my thoughts.

I would guess that Silicon Valley entrepreneurs and leading technologists are typically about +2 SD on each of these items! One can directly estimate M/F ratios from these parameters ...

For example, if a typical male SV entrepreneur / tech leader is roughly +2SD on these traits whereas a female is +2.5SD, the population fraction would be 3:1 or 4:1 larger for males. This doesn't mean that the females who are > +2.5SD (in the female population) are ill-suited to the role (they may be as good as the men), just that there are fewer of them in the general population. I was shocked to see that even top Google leadership didn't understand this point that Damore tried to make in his memo.

A 6ft3 Asian-American guard (Jeremy Lin) might be just as good as other guards in the NBA, but the fraction of Asian-American males who are 6ft3 is smaller than for other groups, like African-Americans. Even if there were no discrimination against Asian players, you'd expect to see fewer (relative to base population) in the NBA due to the average height difference.

Life impacts of personality and intelligence

Here are two nice figures I came across recently.

The first, based on SMPY data, displays odds ratios for various accomplishments (doctorate degree, STEM publication, patent, high income, tenure) as a function of SAT-M score at age 13. The quartiles correspond roughly to 1 in 200 ability (Q1) to 1 in 10k ability (Q4). This data soundly refutes the "IQ above 120 doesn't matter" Malcolm Gladwell nonsense. See earlier post Horsepower matters; Psychometrics works.

In (imprecise) words: "Profoundly gifted children are 10+ times more likely than merely gifted children to, e.g., earn a patent or gain tenure at a top research university. They are at least several times more likely to earn exceptionally high incomes." (Note "merely gifted" is somewhat below the Q1 SMPY cut -- most school systems use top few percent vs top 0.5 percent.)

The second figure shows regression coefficients of income (at various ages) vs IQ and personality traits (standardized, so returns for each SD of trait). This was originally discussed in Earnings effects of personality, education and IQ for the gifted; see also this paper (Miriam Gensowski, Copenhagen). Note the IQ returns may be underestimated for average individuals since the data source is Terman and there is significant restriction of range (everyone tested at better than 1 in 200 or so on the Stanford-Binet). Nevertheless there are still positive returns to above average IQ within the Terman group (analogous to SMPY results above).

It pays to be Smart, Disciplined/Focused, Extraverted, and Mean! 8-(

Earnings effects of personality, education and IQ for the gifted

Thanks to a reader for pointing me to this recent paper by Heckman and collaborators, which makes use of data from the Terman study of gifted individuals (minimum IQ of 135 on the Stanford-Binet).

Of the personality factors, Conscientiousness and Extraversion had the largest (positive) effect on lifetime earnings: the most conscientious or extraverted individuals earned, on average, about 50% more than the least (see figures below). See here for more on Big 5 personality factors and a link to a personality test.

The Effects of Education, Personality, and IQ on Earnings of High-Ability Men

This paper estimates the internal rate of return (IRR) to education for men and women of the Terman sample, a 70-year long prospective cohort study of high-ability individuals. The Terman data is unique in that it not only provides full working-life earnings histories of the participants, but it also includes detailed profiles of each subject, including IQ and measures of latent personality traits. Having information on latent personality traits is significant as it allows us to measure the importance of personality on educational attainment and lifetime earnings.

Our analysis addresses two problems of the literature on returns to education: First, we establish causality of the treatment effect of education on earnings by implementing generalized matching on a full set of observable individual characteristics and unobserved personality traits. Second, since we observe lifetime earnings data, our estimates of the IRR are direct and do not depend on the assumptions that are usually made in order to justify the interpretation of regression coefficients as rates of return.

For the males, the returns to education beyond high school are sizeable. For example, the IRR for obtaining a bachelor's degree over a high school diploma is 11.1%, and for a doctoral degree over a bachelor's degree it is 6.7%. These results are unique because they highlight the returns to high-ability and high-education individuals, who are not well-represented in regular data sets.

Our results highlight the importance of personality and intelligence on our outcome variables. We find that personality traits similar to the Big Five personality traits are significant factors that help determine educational attainment and lifetime earnings. Even holding the level of education constant, measures of personality traits have significant effects on earnings. Similarly, IQ is rewarded in the labor market, independently of education. Most of the effect of personality and IQ on life-time earnings arise late in life, during the prime working years. Therefore, estimates from samples with shorter durations underestimate the treatment effects.

Here are a couple of interesting excerpts from the paper:

... Our third contribution is to show how the effect of personality on earnings varies through-out the men’s working lives. We find that without access to long follow-up data, the estimated effect would be understated. Note that even though the Terman sample has a restricted range of IQ, there is substantial variation in personality. In fact, the Terman men do not differ from the general population in terms of personality.

... note that even when controlling for rich background variables, IQ maintains a statistically significant effect on lifetime earnings. Even though the effect is slightly diminished from the un-controlled association of the first column, it is still sizable. Malcolm Gladwell claims rather generally in his book Outliers that for the Terman men, IQ did not matter once family background and other observable personal characteristics were taken into account. While we do not want to argue that IQ has a larger role for the difference between 50 and 100, for example, than for the difference between 150 and 200, we do want to point out that even at the high end of the ability distribution, IQ has meaningful consequences. [The syntax of this last sentence is strange. Presumably the impact of IQ variation from 50 to 100 (from severely handicapped to average) is larger than for 150 to 200, even though their results show a significant effect even in the very high range.]

Below are some nice figures (click for larger versions). Note the personality factor distribution among Termites was similar to that of the overall population, whereas the IQ range was restricted due to selection. Typical lifetime earnings for this group of exceptionally able men ranged from $2 to $3 million in 2008 dollars.




Compare the bottom right IQ graph with SMPY results which show the impact of ability (SAT-M measured before age 13) on publication and patent rates. Ability in the SMPY graph varies between 99th and 99.99th percentile in quartiles Q1-Q4. The variation in IQ between the bottom and top deciles of the Terman study covers a similar range. The Terman super-smarties (i.e., +4 SD) only earned slightly more (say, 15-20% over a lifetime) than the ordinary smarties (i.e., +2.5 SD), but the probability of earning a patent (SMPY) went up by about 4x over the corresponding ability range.

One hundred years of research on intellectual precocity

David Lubinski sent me this comprehensive review of 100 years of research on intellectual precocity. Someone has already posted an un-gated copy online at the link below. Many of the stunning SMPY graphs summarizing their longitudinal (30+ year) study of a population of gifted individuals (including one group measured at the 1 in 10,000 ability level at age 13) appear in the paper. More SMPY.

From Terman to Today: A Century of Findings on Intellectual Precocity

David Lubinski
Vanderbilt University

One hundred years of research (1916–2016) on intellectually precocious youth is reviewed, painting a portrait of an extraordinary source of human capital and the kinds of learning opportunities needed to facilitate exceptional accomplishments, life satisfaction, and positive growth. The focus is on those studies conducted on individuals within the top 1% in general or specific (mathematical, spatial, or verbal reasoning) abilities. Early insights into the giftedness phenomenon actually foretold what would be scientifically demonstrated 100 years later. Thus, evidence-based conceptualizations quickly moved from viewing intellectually precocious individuals as weak and emotionally liable to highly effective and resilient individuals. Like all groups, intellectually precocious students and adults have strengths and relative weaknesses; they also reveal vast differences in their passion for different pursuits and their drive to achieve. Because they do not possess multipotentiality, we must take a multidimensional view of their individuality. When done, it predicts well long-term educational, occupational, and creative outcomes.

Nature News: Chinese project probes the genetics of genius

This article is mostly correct -- see my comments below in [[ brackets ]]. As usual the Chinese connection is emphasized in the title, even though Plomin (Kings College London) is the more experienced researcher in this area, and most of our DNA samples come from US citizens.

To clarify, my main motivation for understanding the genetics of cognition derives from the observation that the human brain, the most complex object we know of in the universe, is produced from a genetic code of only gigabits in length. How, exactly, this works is one of the greatest scientific mysteries. Genomic selection and other "spin-offs" from this research are of secondary interest.

Nature News: The US adolescents who signed up for the Study of Mathematically Precocious Youth (SMPY) in the 1970s were the smartest of the smart, with mathematical and verbal-reasoning skills within the top 1% of the population. Now, researchers at BGI (formerly the Beijing Genomics Institute) in Shenzhen, China, the largest gene-sequencing facility in the world, are searching for the quirks of DNA that may contribute to such gifts. Plunging into an area that is littered with failures and riven with controversy, the researchers are scouring the genomes of 1,600 of these high-fliers in an ambitious project to find the first common genetic variants associated with human intelligence.

[[ SMPY qualifiers scored at the 1 in 10k level on the math portion of the SAT. Due to the positive correlation between M and V they almost all have V scores in the top half of one percent. ]]

The project, which was launched in August 2012 and is slated to begin data analysis in the next few months, has spawned wild accusations of eugenics plots, as well as more measured objections by social scientists who view such research as a distraction from pressing societal issues. Some geneticists, however, take issue with the study for a different reason. They say that it is highly unlikely to find anything of interest — because the sample size is too small and intelligence is too complex.

Earlier large studies with the same goal have failed. But scientists from BGI’s Cognitive Genomics group hope that their super-smart sample will give them an edge, because it should be enriched with bits of DNA that confer effects on intelligence. “An exceptional person gets you an order of magnitude more statistical power than if you took random people from the population — I’d say we have a fighting chance,” says Stephen Hsu, a theoretical physicist from Michigan State University in East Lansing, who acts as a scientific adviser to BGI and is one of the project’s leaders.

“If they think they’re likely to get much useful data out of this study, they’re almost certainly wrong,” says Daniel MacArthur, a geneticist at Massachusetts General Hospital in Boston. He is not against intelligence studies in principle, despite the visceral reactions they provoke in some people. “Studying intelligence is useful for understanding cognitive function, or diseases” that affect it, he says. But he questions whether the study will work.

[[ Not exactly sure what Dan means by "useful data" here. It's true that we don't anticipate getting more than a few genome-wide significant hits from a GWAS analysis. We may get zero! ]]

... Both Plomin and Hsu are passionate enough to take a shot, although their goals differ. Hsu is focused on the genetic basis of extreme intelligence. “My primary interest is why Einstein or Hawking is different from a normal person,” he says. Plomin is sequencing high-performers as a way of homing in on genes that affect intelligence in the broader population. If enough of these are discovered, he thinks that it may be possible to predict someone’s intelligence from an early age, and to offer help to children who are at risk of learning disabilities.

[[ This may give the false impression that it's a different genetic mechanism that gives rise to "extreme" intelligence as opposed to normal variation. ]]

Publicity around the project has spawned some extreme reactions. An article published in March entitled ‘China is Engineering Genius Babies’ in the US arts and culture magazine VICE branded the study “a state-endorsed genetic-engineering project” that will allow parents to predict the IQs of embryos and selectively breed ever-smarter children. (“That’s nuts,” says Hsu.) “Intelligence does push a lot of buttons. It’s like waving a red flag to a bull,” says Plomin. He argues that there is nothing wrong with using genetic information as the basis of educational interventions. “I’m interested in predicting learning problems early rather than waiting until kids get to school and then fail,” he says. ...

Human capital mongering: M-V-S profiles

The figure below displays the math, verbal and spatial scores of gifted children tested at age 12, and their eventual college majors and career choices. This group is cohort 2 of the SMPY/SVPY study: each child scored better than 99.5 percentile on at least one of the M-V sections of the SAT.





Scores are normalized in units of SDs. The vertical axis is V, the horizontal axis is M, and the length of the arrow reflects spatial ability: pointing to the right means above the group average, to the left means below average; note the arrow for business majors should be twice as long as indicated but there was not enough space on the diagram. The spatial score is obviously correlated with the M score.

Upper right = high V, high M (e.g., physical science)
Upper left = high V, lower M (e.g., humanities, social science)
Lower left = lower V, lower M (e.g., business, law)
Lower right = lower V, high M (e.g., math, engineering, CS)

Because of the selection criteria I wouldn't be surprised if the SDs are large in this population. Many of the SMPY qualifiers could have relatively average V scores and vice versa for SVPY. So the variation between the highest and lowest scores in each ability could be larger than in the general population.

New Yorker: Practice Doesn't Make Perfect (Zach Hambrick, MSU Psychology)

MSU Psychology Professor Zach Hambrick is featured in this New Yorker article about Nature vs Nurture. How far the pendulum has swung since the naive days of Malcolm Gladwell's Outliers and its credulous embrace of Anders Ericsson's nurturist claims. David Lubinski and SMPY also make an appearance.

New Yorker: Practice Doesn't Make Perfect

... So how much did practice actually explain? In a 2014 meta-analysis that looked specifically at the relationship between deliberate practice and performance in music, games like chess, sports, education, and other professions, Hambrick and his team found a relationship that was even more complex than they had expected. For some things, like games, practice explained about a quarter of variance in expertise. For music and sports, the explanatory power accounted for about a fifth. But for education and professions like computer science, military-aircraft piloting, and sales, the effect ranged from small to tiny. For all of these professions, you obviously need to practice, but natural abilities matter more.

What’s more, the explanatory power of practice fell even further when Hambrick took exact level of expertise into account. In sports—one of the areas in which deliberate practice seems to make the most difference—it turned out that the more advanced the athlete, the less of a role practice plays. Training an average athlete for a set number of hours yields far more results than training an élite athlete, which, in turn, yields greater results than training a super-élite athlete. Put differently, someone like me is going to improve a great deal with even a few hundred hours of training. But within an Olympic team tiny differences in performance are unlikely to be the result of training: these athletes train together, with the same coach, day in and day out. Those milliseconds come from somewhere else. Some may be due to the fact that genetic differences can account for some of the response to training. ...

So where else, exactly, do performance differences come from? While Hambrick’s work has been focussed more explicitly on practice and genetics, David Lubinski, a professor of psychology at Vanderbilt University, has been approaching the question from a slightly different angle: through what’s called the Study of Mathematically Precocious Youth (smpy), a longitudinal study of the lives of students who, by the age of thirteen, had scored in the top one per cent of mathematical-reasoning ability and were then selected to take part in an enriched educational environment. (The study, co-directed for many years by Lubinski and his wife, Vanderbilt’s education-school dean, Camilla Benbow, was described in detail in a recent article in Nature.) It’s a crucial supplement to work like Hambrick’s; the data you get from close observation of the same sample and the same individuals over time can answer questions other approaches can’t. “What kinds of practice are more effective? What approaches more effective for some people than others?” Hambrick asks. “We need all the pieces to the puzzle to maximize people’s potential. Lubinski’s work on mathematically precocious youth is an essential piece.”

Chief Executives: brainpower, personality, and height

This paper uses Swedish conscript data to examine characteristics of CEOs of large and medium sized companies. Also discussed on Marginal Revolution. Thanks to Carl Shulman for the link.

It looks like large company CEOs are roughly +1, +1.5 and +0.5 SD on cognitive ability, non-cognitive ability (see below) and height, respectively. Apparently Swedish medical doctors are also only about +1 SD in cognitive ability (see article).

Horizontal axes are on a stanine (STAndard NINE) scale. On this scale a normal distribution is divided into nine intervals, each of which has a width of 0.5 standard deviations excluding the first and last.

Match Made at Birth? What Traits of a Million Swedes Tell Us about CEOs

Abstract: This paper analyzes the role three personal traits — cognitive and non-cognitive ability, and height — play in the market for CEOs. We merge data on the traits of more than one million Swedish males, measured at age 18 in a mandatory military enlistment test, with comprehensive data on their income, education, profession, and service as a CEO of any Swedish company. We find that the traits of large-company CEOs are at par or higher than those of other high-caliber professions. For example, large-company CEOs have about the same cognitive ability, and about one-half of a standard deviation higher non-cognitive ability and height than medical doctors. Their traits compare even more favorably with those of lawyers. The traits contribute to pay in two ways. First, higher-caliber CEOs are assigned to larger companies, which tend to pay more. Second, the traits contribute to pay over and above that driven by firm size. We estimate that 27-58% of the effect of traits on pay comes from CEO’s assignment to larger companies. Our results are consistent with models where the labor market allocates higher-caliber CEOs to more productive positions.

... The cognitive-ability test consists of four subtests designed to measure inductive reasoning (Instruction test), verbal comprehension (Synonym test), spatial ability (Metal folding test), and technical comprehension (Technical comprehension test).

[Non-cognitive ability:] Psychologists use test results and family characteristics in combination with one-on-one semi-structured interviews to assess conscripts’ psychological fitness for the military. Psychologists evaluate each conscript’s social maturity, intensity, psychological energy, and emotional stability and assign a final aptitude score following the stanine scale. Conscripts obtain a higher score in the interview when they demonstrate that they have the willingness to assume responsibility, are independent, have an outgoing character, demonstrate persistence and emotional stability, and display initiative. Importantly, a strong desire for doing military service is not considered a positive attribute for military aptitude (and may even lead to a negative assessment), which means that the aptitude score can be considered a more general measure of non-cognitive ability.

See related post Creators and Rulers:

I went to Harvard Business School, a self-styled pantheon for the business elite.

The average person was:
- top decile intellect (though probably not higher)
- top decile emotional intelligence (broadly construed - socially aware, self-aware, persuasion skills, etc.)
- highly conscientious / motivated

Few were truly brilliant intellectually. Few were academically distinguished (plenty of good ivy league degrees, but very few brilliant mathematical minds, etc.).

A good number will be at Davos in 20 years time.

Performance beyond a certain level in the vast majority of fields (and business is certainly one of them) is principally a function of having no cognitive and personal qualities which fall below a (high, but not insanely high) hygene threshold -- and then multiplied by determination, of course.

Conscientiousness, in fact, is the best single stable predictor of job success for complex jobs (well established in personality psychometrics).

Very high intelligence actually negatively correlates with career success (Kotter), probably because smart people enjoy solving problems, rather than making money selling things -- which outside of quant trading, show business and sport is really the only way of being really successful.

There are some extremely intelligent people in business (by which I mean high IQ, not just wise or experienced), but you tend to find them in the corners of the business landscape with the richest intellectual pastures: some areas of law, venture capital, some cutting edge technology fields.

See also Human capital mongering: M-V-S profiles. Note deviation scores (SDs) here are relative to the average among the gifted kids in the sample, not relative to the general population. The people in this sample are probably above average in the general population on each of M-V-S.

The figure below displays the math, verbal and spatial scores of gifted children tested at age 12, and their eventual college majors and career choices. This group is cohort 2 of the SMPY/SVPY study: each child scored better than 99.5 percentile on at least one of the M-V sections of the SAT.





Scores are normalized in units of SDs. The vertical axis is V, the horizontal axis is M, and the length of the arrow reflects spatial ability: pointing to the right means above the group average, to the left means below average; note the arrow for business majors should be twice as long as indicated but there was not enough space on the diagram. The spatial score is obviously correlated with the M score.

Upper right = high V, high M (e.g., physical science)
Upper left = high V, lower M (e.g., humanities, social science)
Lower left = lower V, lower M (e.g., business, law)
Lower right = lower V, high M (e.g., math, engineering, CS)

Roe's scientists: original published papers

Gwern has provided scans of the original papers published by Anne Roe on studies of 64 eminent scientists. These papers include details concerning the selection of these individuals and the psychometric testing performed on them. Roe's scientists -- selected in their 40's and 50's for outstanding research contributions -- scored much higher on a set of high ceiling psychometric tests than the general population of scientists or PhDs.

Roe's work, combined with SMPY and Duke TIP longitudinal studies, and the earlier Terman studies, supports the claim that measured cognitive ability in the far tail significantly increases the likelihood of important contributions to science and technology.

See Annals of psychometry: IQs of eminent scientists.

1. Roe 1949, "Psychological Examinations of Eminent Biologists": http://www.gwern.net/docs/iq/1949-roe-biologists.pdf

2. Roe 1951, "A Psychological Study of Eminent Biologists": http://www.gwern.net/docs/iq/1951-roe-biologists.pdf

3. Roe 1951, "A Study of Imagery in Research Scientists": http://www.gwern.net/docs/iq/1951-roe-imagery.pdf

4. Roe 1951, "Psychological Tests of Research Scientists": http://www.gwern.net/docs/iq/1951-roe-scientists.pdf

5. Roe 1953, "A Psychological Study of Eminent Psychologists and Anthropologists, and a comparison with Biological and Physical Scientists": http://www.gwern.net/docs/iq/1953-roe-psychologists.pdf

6. Roe 1953, _The Making of a Scientist_: https://www.dropbox.com/s/i7raf2aup5pdpgy/1953-roe-makingscientist.pdf

7. Roe 1951, "A psychological study of physical scientists" (physicists/chemists) now available: https://www.dropbox.com/s/qh34xcxl0pzc9lr/1951-roe-physicalscientists.pdf

The individuals in the study are listed below.

Physicists will recognize names such as Luis Alvarez, Julian Schwinger, Wendell Furry, J.H. Van Vleck and others. Also in the group were Carleton Coon, B.F. Skinner, Linus Pauling and Sewall Wright.

Allport, Gordon W.(Gordon Willard), 1897-1967
Alvarez 1911-1988, Luis Walter
Anderson, Edgar, 1897-1969
Babcock, Horace W., 1912-2003
Beach, Frank A., (Frank Ambrose), 1911-1988
Beadle, George Wells, 1903-1989
Beams, Jesse W., (Jesse Wakefield), 1898-1977
Bearden, J.A. (Joyce Alvin), 1903-1987
Bonner, James Frederick, 1910-1996
Bruner, Jerome S. (Jerome Seymour), 1915-
Cleland, Ralph E., (Ralph Erskine), 1892-1971
Coon, Carleton S., (Carleton Stevens), 1904-1981
Corner, George Washington, 1889-1981
Doisy, Edward Adelbert, 1893-1986
Epling, Carl, 1894-1968
Ewing, W. Maurice, (William Maurice), 1906-1974
Furry, W.H. (Wendell Hinkle) , 1907-1984
Guilford, J. P. , (Joy Paul), 1897-1987
Hallowell, A. Irving , (Alfred Irving), 1892-1974
Hansen, William Webster, 1909-1949
Harlow, Harry Freerick, 1905-1981
Hilgard, Ernest R., (Ernest Ropiequet), 1904-2001
Joseph Edward, Mayer, 1904-1983
Kirkwood, John Gamble, 1907-1959
Kluckhohn, Clyde, 1905-1960
Knudsen, Vern Oliver, 1893-1974
Lashley, Karl Spencer, 1890-1958
Lindsey, Donald B.
Linton, Ralph, 1893-1953
Mayer, Joseph Edward, 1904-1983
McMillan, Edwin M. (Edwin Mattison), 1907-1991
Morse, Philip M., (Philip McCord), 1903-1985
Mueller, J. Howard, (John Howard), 1891-1954
Muller, H. J., (Hermann Joseph), 1890-1967
Mulliken, Robert Sanderson, 1896-1986
Muskat , M. (Morris) , 1906-1998
Northrop, John Howard, 1891-1987
Pauling, Linus, 1901-1994
Rhoades, Marcus M., (Marcus Morton), 1903-1991
Ritcher, Curt Paul, 1894-1994
Robbins, William Jacob, 1890-1978
Robertson, H. P., (Howard Percy), 1903-1961
Rogers, Carl R., (Carl Ransom), 1902-1987
Romer, Alfred Sherwood, 1894-1973
Schwinger, Julian Seymour, 1918-1994
Sears, Robert R., (Robert Richardson)
Shapiro, Harry L., (Harry Lionel), 1902-1990
Skinner, B. F. (Burrhus Fredric), 1904-1990
Smith, Homer William, 1895-1962
Sonneborn, T.M., (Tracy Morton), 1905-1981
Stanley, Wendell M., (Wendell Meredith), 1904-
Stebbins, G. Ledyard, (George Ledyard), 1906-2000
Stevens, S. S., (Stanley Smith), 1906-1973
Stewart, Homer Joseph, 1915-2007
Stratton, Julius Adams, 1901-1994
Strong, William Duncan, 1899-1962.
Sturtevant, A.H. (Alfred Henry), 1891-1970
Tuve, Merle Antony, 1901-1982
Van Vleck, J. H., (John Hasbrouck), 1899-1980
Willey, Gordon R., (Gordon Randolph), 1913-2002
Wright, Sewall, 1889-1988

More on psychometrics

I've had some email discussions elaborating on the psychometrics slides I posted earlier. The slides themselves don't convey a lot of the important points I made in the talks so I thought I'd share this message on the blog.

Hi Guys,

I'm very interested in exactly the question Henry is getting at.

I think our simple two factor model

Grades = ability + work ethic = IQ + W

is not too crazy. Note that once you fix the ability level (=SAT score) the remaining variance in GPA has about the same SD regardless of value of SAT score (vertical red lines in the big figure in the slides). That suggests that we can think of IQ and W as largely uncorrelated random variables -- so there are smart lazy people, hard working dumb people, etc. I can't really prove the residual variance after IQ is controlled for is due to work ethic, but my experience in the classroom suggests that it is. (Note work ethic here isn't necessary general work ethic as a personality factor, but how hard the kid worked in the specific course. However, in our data we average over many courses taken by many kids, so perhaps it does get at variation of personality factor(s) in the overall population.) Beyond work ethic, some people are just more "effective" -- they can get themselves organized, are disciplined, can adapt to new challenges, are emotionally robust -- and this is also absorbed in the W factor above.

Now, in some fields there seems to be a minimum cognitive threshold. I've known physics students who worked incredibly hard and just couldn't master the material. That is reflected in our data on pure math and physics majors at UO. For all majors there is a significant positive correlation between SAT and upper GPA (in the range .3-.5).

Whether IQ has a large impact on life outcomes depends on how you ask the question. I do believe that certain professions are almost off-limits for people below a certain IQ threshold. But for most jobs (even engineer or doctor), this threshold is surprisingly low IF the person has a strong work ethic. In other words a +1 SD IQ person can probably still be a doctor or engineer if they have +(2-3) SD work ethic. However, such people, if they are honest with themselves, understand that they have some cognitive disadvantages relative to their peers. I've chosen a profession in which, every so often, I am the dumbest guy in the room -- in fact I put myself in this situation by going to workshops and wanting to talk to the smartest guys I can find :-) For someone of *average* work ethic I think you can easily find jobs for which the IQ threshold is +2 SD or higher. The typical kid admitted to grad school in my middle-tier physics department is probably > +2 SD IQ and at least +1.5 SD in work ethic -- ditto for a top tier law or med school. That's probably also the case these days for any "academic admit" at a top Ivy.

For typical jobs I think the correlation between success/income and IQ isn't very high. Other factors come into play, like work ethic, interpersonal skills, affect, charisma, luck, etc. This may even be true in many "elite" professions once you are talking about a population where everyone is above the minimum IQ threshold -- if returns to IQ above threshold are not that large then the other factors dominate and determine level of success. What is interesting about the Roe and SMPY studies is that they suggest that in science the returns to IQ above the +2 SD threshold (for getting a PhD) are pretty high. ***

Henry is right that for ideological reasons many researchers are happy to present the data so as to minimize the utility of IQ or testing in making life predictions. They might even go so far as to claim that since we use g-loaded tests in admissions, the conclusion that some professions require high IQ is actually circular. The social scientist who walked out of my Sci Foo talk actually made that claim.

Finally, when it comes to *individual* success I think most analysts significantly underestimate the role of pure blind luck (i.e., what remains when all other reasonable, roughly measurable variables have been accounted for; of course this averages out of any large population study). Or perhaps I am just reassuring myself about my limited success in life :-)


Steve

PS In the actual talks I gave I made most of these points. The slides are kind of bare bones...


*** You would have difficulty finding a hard scientist who would disagree with the statement it is a big advantage in my field to be super smart. However, thanks to political correctness, social science indoctrination, or unfamiliarity with psychometrics, it IS common for scientists to deny that being super smart has anything to do with scores on IQ tests. I myself question the validity of IQ tests beyond +(3-4) SD -- I'm more impressed by success on the IMO, Putnam, or in other high level competitions. (Although I realize that training has a big impact on performance in these competitions I do think real talent is a necessary condition for success.)

Success, Ability, and all that

I came across this nice discussion at LessWrong which is similar to my old post Success vs Ability. The illustration below shows why even a strong predictor of outcome is seldom able to pick out the very top performer: e.g., taller people are on average better at basketball, but the best player in the world is not the tallest; smarter people are on average better at making money, but the richest person in the world is not the smartest, etc.

This seems like a trivial point (as are most things, when explained clearly), however, it still eludes the vast majority. For example, in the Atlantic article I linked to in the earlier post Creative Minds, the neuroscientist professor who studies creative genius misunderstands the implications of the Terman study. She repeats the common claim that Terman's study fails to support the importance of high cognitive ability to "genius"-level achievement: none of the Termites won a Nobel prize, whereas Shockley and Alvarez, who narrowly missed the (verbally loaded) Stanford-Binet cut for the study, each won for work in experimental physics. But luck, drive, creativity, and other factors, all at least somewhat independent of intelligence, influence success in science. Combine this with the fact that there are exponentially more people a bit below the Terman cut than above it, and Terman's results do little more than confirm that cognitive ability is positively but not perfectly correlated with creative output.

In the SMPY study probability of having published a literary work or earned a patent was increasing with ability even within the top 1%. The "IQ over 120 doesn't matter" meme falls apart if one measures individual likelihood of success, as opposed to the total number of individuals at, e.g., IQ 120 vs IQ 145, who have achieved some milestone.

It is plausible that, e.g., among top execs or scientists or engineers there are roughly equal numbers of IQ 120 and IQ 145 individuals (the actual numbers could vary depending on how the groups are defined). But the base population of the former group is 100 times that of the latter! (IQ 120 is about top 10% and IQ 145 is roughly top 0.1% in the population.) This means, e.g., that the probability that an IQ 145 person becomes a top scientist could be ~100x higher than for an IQ 120 person.

This topic came up last night in Hong Kong, at dinner with two hedge funders (Caltech/MIT guys with PhDs) who have had long careers in finance. Both observed that 20 years ago it was nearly impossible to predict which of their colleagues and peers would go on to make vast fortunes, as opposed to becoming merely rich.