nhaliday + large-factor   39

The Hanson-Yudkowsky AI-Foom Debate - Machine Intelligence Research Institute
How Deviant Recent AI Progress Lumpiness?: http://www.overcomingbias.com/2018/03/how-deviant-recent-ai-progress-lumpiness.html
I seem to disagree with most people working on artificial intelligence (AI) risk. While with them I expect rapid change once AI is powerful enough to replace most all human workers, I expect this change to be spread across the world, not concentrated in one main localized AI system. The efforts of AI risk folks to design AI systems whose values won’t drift might stop global AI value drift if there is just one main AI system. But doing so in a world of many AI systems at similar abilities levels requires strong global governance of AI systems, which is a tall order anytime soon. Their continued focus on preventing single system drift suggests that they expect a single main AI system.

The main reason that I understand to expect relatively local AI progress is if AI progress is unusually lumpy, i.e., arriving in unusually fewer larger packages rather than in the usual many smaller packages. If one AI team finds a big lump, it might jump way ahead of the other teams.

However, we have a vast literature on the lumpiness of research and innovation more generally, which clearly says that usually most of the value in innovation is found in many small innovations. We have also so far seen this in computer science (CS) and AI. Even if there have been historical examples where much value was found in particular big innovations, such as nuclear weapons or the origin of humans.

Apparently many people associated with AI risk, including the star machine learning (ML) researchers that they often idolize, find it intuitively plausible that AI and ML progress is exceptionally lumpy. Such researchers often say, “My project is ‘huge’, and will soon do it all!” A decade ago my ex-co-blogger Eliezer Yudkowsky and I argued here on this blog about our differing estimates of AI progress lumpiness. He recently offered Alpha Go Zero as evidence of AI lumpiness:


In this post, let me give another example (beyond two big lumps in a row) of what could change my mind. I offer a clear observable indicator, for which data should have available now: deviant citation lumpiness in recent ML research. One standard measure of research impact is citations; bigger lumpier developments gain more citations that smaller ones. And it turns out that the lumpiness of citations is remarkably constant across research fields! See this March 3 paper in Science:

I Still Don’t Get Foom: http://www.overcomingbias.com/2014/07/30855.html
All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain.

If we count by economic value, humans now do most of the mental tasks worth doing. Evolution has given us a brain chock-full of useful well-honed modules. And the fact that most mental tasks require the use of many modules is enough to explain why some of us are smarter than others. (There’d be a common “g” factor in task performance even with independent module variation.) Our modules aren’t that different from those of other primates, but because ours are different enough to allow lots of cultural transmission of innovation, we’ve out-competed other primates handily.

We’ve had computers for over seventy years, and have slowly build up libraries of software modules for them. Like brains, computers do mental tasks by combining modules. An important mental task is software innovation: improving these modules, adding new ones, and finding new ways to combine them. Ideas for new modules are sometimes inspired by the modules we see in our brains. When an innovation team finds an improvement, they usually sell access to it, which gives them resources for new projects, and lets others take advantage of their innovation.


In Bostrom’s graph above the line for an initially small project and system has a much higher slope, which means that it becomes in a short time vastly better at software innovation. Better than the entire rest of the world put together. And my key question is: how could it plausibly do that? Since the rest of the world is already trying the best it can to usefully innovate, and to abstract to promote such innovation, what exactly gives one small project such a huge advantage to let it innovate so much faster?


In fact, most software innovation seems to be driven by hardware advances, instead of innovator creativity. Apparently, good ideas are available but must usually wait until hardware is cheap enough to support them.

Yes, sometimes architectural choices have wider impacts. But I was an artificial intelligence researcher for nine years, ending twenty years ago, and I never saw an architecture choice make a huge difference, relative to other reasonable architecture choices. For most big systems, overall architecture matters a lot less than getting lots of detail right. Researchers have long wandered the space of architectures, mostly rediscovering variations on what others found before.

Some hope that a small project could be much better at innovation because it specializes in that topic, and much better understands new theoretical insights into the basic nature of innovation or intelligence. But I don’t think those are actually topics where one can usefully specialize much, or where we’ll find much useful new theory. To be much better at learning, the project would instead have to be much better at hundreds of specific kinds of learning. Which is very hard to do in a small project.

What does Bostrom say? Alas, not much. He distinguishes several advantages of digital over human minds, but all software shares those advantages. Bostrom also distinguishes five paths: better software, brain emulation (i.e., ems), biological enhancement of humans, brain-computer interfaces, and better human organizations. He doesn’t think interfaces would work, and sees organizations and better biology as only playing supporting roles.


Similarly, while you might imagine someday standing in awe in front of a super intelligence that embodies all the power of a new age, superintelligence just isn’t the sort of thing that one project could invent. As “intelligence” is just the name we give to being better at many mental tasks by using many good mental modules, there’s no one place to improve it. So I can’t see a plausible way one project could increase its intelligence vastly faster than could the rest of the world.

Takeoff speeds: https://sideways-view.com/2018/02/24/takeoff-speeds/
Futurists have argued for years about whether the development of AGI will look more like a breakthrough within a small group (“fast takeoff”), or a continuous acceleration distributed across the broader economy or a large firm (“slow takeoff”).

I currently think a slow takeoff is significantly more likely. This post explains some of my reasoning and why I think it matters. Mostly the post lists arguments I often hear for a fast takeoff and explains why I don’t find them compelling.

(Note: this is not a post about whether an intelligence explosion will occur. That seems very likely to me. Quantitatively I expect it to go along these lines. So e.g. while I disagree with many of the claims and assumptions in Intelligence Explosion Microeconomics, I don’t disagree with the central thesis or with most of the arguments.)
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april 2018 by nhaliday
1 Genetics and Crime
The broader construct of antisocial behavior – which includes criminal offending, as well as aggression – also shows substantial genetic influence. In a meta-analysis combining effect sizes in 51 twin and adoption studies, Rhee and Waldman (2002) reported a heritability estimate of 41 per cent, with the remaining 59 per cent of variance being due to environmental factors. Interestingly, when comparing results for various definitions of antisocial behavior, only criminal offending appeared to be influenced by both additive genetic effects and non-additive genetic effects – possibly due to genetic dominance and epistatic interactions between genes – based on a pattern of results whereby, on average, identical (monozygotic) twin correlations are more than twice the value of fraternal (dizygotic) twin correlations, and also that biological parent–offspring correlations are less than fraternal twin correlations. Such non-additive genetic effects could arise if one or more high risk alleles act in a recessive fashion, or if certain alleles at one locus affect gene expression at other loci (epistasis).

One intriguing aspect of the literature on genetics and crime is that the strong and consistent genetic influence seen for property offending does not hold true for violent criminal convictions. None of the major adoption studies in Scandinavia or the United States found any elevated risk for violent convictions as a function of either biological or adoptive parent criminal offending, although one early twin study did find greater identical (monozygotic) than fraternal (dizygotic) concordance for violent convictions (see Cloninger and Gottesman, 1987). This pattern of twin, but not parent-offspring, similarity for violent criminal behavior suggests the possibility of non-additive genetic effects due to dominance or epistasis, which would result in increased resemblance for siblings (and twins), but not for parents and offspring. Thus, there may be genetic risk for violent crimes such as murder and rape, which may stem from rare recessive genes, or specific combinations of alleles that do not appear in studies of vertical transmission across generations.

A Swedish national twin study of criminal behavior and its violent, white-collar and property subtypes: https://www.cambridge.org/core/journals/psychological-medicine/article/a-swedish-national-twin-study-of-criminal-behavior-and-its-violent-white-collar-and-property-subtypes/0D9A88185ED0FD5525A5EBD5D2EBA117
For all criminal convictions, heritability was estimated at around 45% in both sexes, with the shared environment accounting for 18% of the variance in liability in females and 27% in males. The correlation of these risk factors across sexes was estimated at +0.63. In men, the magnitudes of genetic and environmental influence were similar in the three criminal conviction subtypes. However, for violent and white-collar convictions, nearly half and one-third of the genetic effects were respectively unique to that criminal subtype. About half of the familial environmental effects were unique to property convictions.

Heritability, Assortative Mating and Gender Differences in Violent Crime: Results from a Total Population Sample Using Twin, Adoption, and Sibling Models: https://link.springer.com/article/10.1007/s10519-011-9483-0
Using 36k twins, violent crime was moderately heritable (~ 55%) w/ 13% shared environment influence. Using 1.5 mil siblings, heritability was higher for males, & family environment higher for females. Moderate assortative mating for violent crime (r = .4).

The impact of neighbourhood deprivation on adolescent violent criminality and substance misuse: A longitudinal, quasi-experimental study of the total Swedish population: https://academic.oup.com/ije/article/42/4/1057/656274/The-impact-of-neighbourhood-deprivation-on
In the crude model, an increase of 1 SD in neighbourhood deprivation was associated with a 57% increase in the odds of being convicted of a violent crime (95% CI 52%–63%). The effect was greatly attenuated when adjustment was made for a number of observed confounders (OR 1.09, 95% CI 1.06–1.11). When we additionally adjusted for unobserved familial confounders, the effect was no longer present (OR 0.96, 95% CI 0.84–1.10). Similar results were observed for substance misuse. The results were not due to poor variability either between neighbourhoods or within families.

Childhood family income, adolescent violent criminality and substance misuse: quasi-experimental total population study: http://bjp.rcpsych.org/content/early/2014/08/14/bjp.bp.113.136200
What did surprise him was that when he looked at families which had started poor and got richer, the younger children—those born into relative affluence—were just as likely to misbehave when they were teenagers as their elder siblings had been. Family income was not, per se, the determining factor.

Indicators of domestic/intimate partner violence are structured by genetic and nonshared environmental influences: https://www.researchgate.net/publication/233737219_Indicators_of_domesticintimate_partner_violence_are_structured_by_genetic_and_nonshared_environmental_influences
Three indicators of IPV were measured and genetic factors accounted for 24% of the variance in hitting one's partner, 54% of the variance in injuring one's partner, and 51% of the variance in forcing sexual activity on one's partner. The shared environment explained none of the variance across all three indicators and the nonshared environment explained the remainder of the variance.
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october 2017 by nhaliday
key fact: cognitive ability is not growing in importance, but non-cognitive ability is

The labor market increasingly rewards social skills. Between 1980 and 2012, jobs requiring high levels of social interaction grew by nearly 12 percentage points as a share of the U.S. labor force. Math-intensive but less social jobs—including many STEM occupations—shrank by 3.3 percentage points over the same period. Employment and wage growth was particularly strong for jobs requiring high levels of both math skill and social skill. To understand these patterns, I develop a model of team production where workers “trade tasks” to exploit their comparative advantage. In the model, social skills reduce coordination costs, allowing workers to specialize and work together more efficiently. The model generates predictions about sorting and the relative returns to skill across occupations, which I investigate using data from the NLSY79 and the NLSY97. Using a comparable set of skill measures and covariates across survey waves, I find that the labor market return to social skills was much greater in the 2000s than in the mid 1980s and 1990s. JEL Codes: I20, I24, J01, J23, J24, J31

The Increasing Complementarity between Cognitive and Social Skills: http://econ.ucsb.edu/~weinberg/MathSocialWeinberger.pdf

The Changing Roles of Education and Ability in Wage Determination: http://business.uow.edu.au/content/groups/public/@web/@commerce/@research/documents/doc/uow130116.pdf

Intelligence and socioeconomic success: A meta-analytic review of longitudinal research: http://www.emilkirkegaard.dk/en/wp-content/uploads/Intelligence-and-socioeconomic-success-A-meta-analytic-review-of-longitudinal-research.pdf
Moderator analyses showed that the relationship between intelligence and success is dependent on the age of the sample but there is little evidence of any historical trend in the relationship.

that feelio when america has crossed an inflection point and EQ is obviously more important for success in todays society than IQ
I think this is how to understand a lot of "corporate commitment to diversity" stuff.Not the only reason ofc, but reason it's so impregnable
compare: https://pinboard.in/u:nhaliday/b:e9ac3d38e7a1
and: https://pinboard.in/u:nhaliday/b:a38f5756170d

g-reliant skills seem most susceptible to automation: https://fredrikdeboer.com/2017/06/14/g-reliant-skills-seem-most-susceptible-to-automation/

THE ERROR TERM: https://spottedtoad.wordpress.com/2018/02/19/the-error-term/
Imagine an objective function- something you want to maximize or minimize- with both a deterministic and a random component.


Part of y is rules-based and rational, part is random and outside rational control. Obviously, the ascent of civilization has, to the extent it has taken place, been based on focusing energies on those parts of the world that are responsive to rational interpretation and control.

But an interesting thing happens once automated processes are able to take over the mapping of patterns onto rules. The portion of the world that is responsive to algorithmic interpretation is also the rational, rules-based portion, almost tautologically. But in terms of our actual objective functions- the real portions of the world that we are trying to affect or influence- subtracting out the portion susceptible to algorithms does not eliminate the variation or make it unimportant. It simply makes it much more purely random rather than only partially so.

The interesting thing, to me, is that economic returns accumulate to the random portion of variation just as to the deterministic portion. In fact, if everybody has access to the same algorithms, the returns may well be largely to the random portion. The efficient market hypothesis in action, more or less.


But more generally, as more and more of the society comes under algorithmic control, as various forms of automated intelligence become ubiquitous, the remaining portion, and the portion for which individual workers are rewarded, might well become more irrational, more random, less satisfying, less intelligent.

Golden age for team players: https://news.harvard.edu/gazette/story/2017/10/social-skills-increasingly-valuable-to-employers-harvard-economist-finds/
Strong social skills increasingly valuable to employers, study finds

Number of available jobs by skill set (over time)

Changes in hourly wages by skill set (over time)

A resolution for the new year: Remember that intelligence is a predictor of social intelligence!
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august 2017 by nhaliday
Genes, Evolution and Intelligence
I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties—intelligence—is best explained by the near infinitesimal model of quantitative genetics.
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august 2017 by nhaliday
Sex differences in latent cognitive abilities ages 6 to 59: Evidence from the Woodcock–Johnson III tests of cognitive abilities

The higher-order, latent g factor showed inconsistent differences for children, small, non-significant differences favoring females for adolescents, and fairly consistent statistically significant differences favoring females in adulthood. Findings are inconsistent with developmental theory that suggests males should show an advantage on g in adulthood. Supplemental analyses suggested that methodological choices, including the use of latent variables versus composites and methods for dealing with missing data, can affect research findings.
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may 2017 by nhaliday
Identifying the Determinants of Attitudes towards Immigrants: A Structural Cross-Country Analysis
not much of a difference by gender (seems female->more supportive in northern countries, less supportive in southern countries), biggest thing is urbanity+educational attainment

Vote share for WEuro populist parties higher in regions: rural, ⇈foreigners, ⇈unemployment, AND ⇈education except in cities (surprising)
the urban educated hate the nationalist parties but the nonurban educated are prone to support them. Not all educated are alike

The success of radical right-wing parties in Western European regions – new challenging findings: http://www.tandfonline.com/doi/abs/10.1080/14782804.2016.1198691

Can Television Reduce Xenophobia? The Case of East Germany: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2932276
To examine this question, we exploit the fact that individuals in some areas of East Germany – due to their geographic location – could not receive West German television until 1989. We conjecture that individuals who received West German television were exposed more frequently to foreigners and thus have developed less xenophobia than people who were not exposed to those programs. Our results show that regions that could receive West German television were less likely to vote for right-wing parties during the national elections from 1998 to 2013. Only recently, the same regions were also more likely to vote for left-wing parties. Moreover, while counties that hosted more foreigners in 1989 were also more likely to vote for right-wing parties in most elections, we find counties that recently hosted more foreign visitors showed less xenophobia, which is in line with intergroup contact theory.

With an Open Mind: Openness to Experience Moderates the Effect of Interethnic Encounters on Support for Immigration: https://academic.oup.com/esr/article-abstract/33/5/721/4102111/With-an-Open-Mind-Openness-to-Experience-Moderates

Refugees Unwelcome? Changes in the Public Acceptance of Immigrants and Refugees in Germany in the Course of Europe’s ‘Immigration Crisis’: https://academic.oup.com/esr/article-abstract/doi/10.1093/esr/jcx071/4557564/Refugees-Unwelcome-Changes-in-the-Public
Derived from discussions making up the German immigration discourse during this time, we expect reduced acceptance especially of those immigrants who were explicitly connected to the salient events, like Muslims and the offenders of NYE. Most strikingly, we find that refugees were generally highly accepted and even more so in the second wave, whereas the acceptance of immigrants from Arab or African countries further decreased. Moreover, _female respondents’ initial preference for male immigrants_ disappeared. Contrary to our expectations, we find no changes in the acceptance of Muslims.
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may 2017 by nhaliday
PsycARTICLES - Is education associated with improvements in general cognitive ability, or in specific skills?
Results indicated that the association of education with improved cognitive test scores is not mediated by g, but consists of direct effects on specific cognitive skills. These results suggest a decoupling of educational gains from increases in general intellectual capacity.

look at Model C for the coefficients

How much does education improve intelligence? A meta-analysis: https://psyarxiv.com/kymhp
Intelligence test scores and educational duration are positively correlated. This correlation can be interpreted in two ways: students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.

three study designs: control for prior IQ, exogenous policy change, and school age cutoff regression discontinuity

It’s surprising that there isn’t much of a fadeout (p11) – half of the effect size is still there by age 70 (?!). That wasn’t what I expected. Maybe they’re being pulled upwards by smaller outlier studies – most of the bigger ones tend towards the lower end.

These gains are hollow, as they acknowledge in the discussion. Examples:
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march 2017 by nhaliday
Links 6/15: URLing Toward Freedom | Slate Star Codex
Why do some schools produce a disproportionate share of math competition winners? May not just be student characteristics.

My post The Control Group Is Out Of Control, as well as some of the Less Wrong posts that inspired it, has gotten cited in a recent preprint article, A Skeptical Eye On Psi, on what psi can teach us about the replication crisis. One of the authors is someone I previously yelled at, so I like to think all of that yelling is having a positive effect.

A study from Sweden (it’s always Sweden) does really good work examining the effect of education on IQ. It takes an increase in mandatory Swedish schooling length which was rolled out randomly at different times in different districts, and finds that the districts where people got more schooling have higher IQ; in particular, an extra year of education increases permanent IQ by 0.75 points. I was previously ambivalent about this, but this is a really strong study and I guess I have to endorse it now (though it’s hard to say how g-loaded it is or how linear it is). Also of note; the extra schooling permanently harmed emotional control ability by 0.5 points on a scale identical to IQ (mean 100, SD 15). This is of course the opposite of past studies suggest that education does not improve IQ but does help non-cognitive factors. But this study was an extra year tacked on to the end of education, whereas earlier ones have been measuring extra education tacked on to the beginning, or just making the whole educational process more efficient. Still weird, but again, this is a good experiment (EDIT: This might not be on g)
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march 2017 by nhaliday
Why g Matters: The Complexity of Everyday Life
- that classic carpet example among other things
- note that many manufacturing/trade jobs are fairly high up on the ladder
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march 2017 by nhaliday
Social Epistasis Amplifies the Fitness Costs of Deleterious Mutations, Engendering Rapid Fitness Decline Among Modernized Populations | SpringerLink
- Michael A. Woodley

We argue that in social species, interorganismal gene-gene interactions, which in previous literatures have been termed social epistasis, allow genomes carrying deleterious mutations to reduce via group-level pleiotropy the fitness of others, including noncarriers. This fitness reduction occurs by way of degradation of group-level processes that optimize the reproductive ecology of a population for intergroup competition through, among other mechanisms, suppression of free-riding.


Fitness indicators theory (Houle 2000; Miller 2000) predicts that the behavioral and physiological condition of prospective partners strongly influences female mate choice in particular, as these constitute honest indicators of underlying genetic quality. Furthermore, as deleterious mutations are pleiotropic (i.e., they can influence the development of multiple traits simultaneously), they are a source of genetic correlation among diverse behavioral and physiological domains, yielding a latent general fitness factor( f ). This optimizes the efficiency of sexual selection, as selection for quality with respect to one domain will increase the probability of selection for quality “across the board” (Houle 2000; Miller 2000). If purifying selection is primarily cryptic—working by virtue of those lower in f simply being less successful in competition for mates and therefore producing fewer offspring relative to those higher in the factor—then considerably less reproductive failure is needed to solve the mutation load paradox (19% instead of 88% based on simulations in Leseque et al. 2012).


Theoretical work involving humans suggests a loss of intrinsic fitness of around 1% per generation in the populations of modernized countries (Lynch 2016; Muller 1950). Thus, these might yet be undergoing mutational meltdown, albeit very gradually (i.e., over the course of centuries)


An interesting observation is that the fitness of the populations of modernized nations does appear to be rapidly decreasing—although not in a manner consonant with the direct action of deleterious mutations on the fitness of individuals (as per the mutation load paradox).


Increased education has furthermore encouraged individuals to trade fertility against opportunities to enhance their social status and earning power, with the largest fitness losses occurring among those with high status who potentially carry fewer deleterious mutations (i.e., by virtue of possessing higher levels of traits that exhibit some sensitivity to mutation load, such as general intelligence; Spain et al. 2015; Woodley of Menie et al. 2016a). Hitherto not considered is the possibility that the demographic transition represents a potential change in the fitness characteristics of the group-level extended phenotype of modernized populations, indicating that there might exist pathways through which deleterious mutations that accumulate due to ecological mildness could pathologically alter fertility tradeoffs in ways that might account for the maladaptive aspects of the fertility transition (e.g., subreplacement fertility; Basten, Lutz and Scherbov, 2013).


Cooperation, though offering significant fitness benefits to individual organisms and groups, involves some costs for cooperators in order to realize mutual gains for all parties. Free riders are individuals that benefit from cooperation without suffering any of the costs needed to sustain it. Hence, free riders enjoy a fitness advantage relative to cooperators via the former’s parasitism on the latter.


The balance of selection can alternate between the different levels depending on the sorts of selective challenges that a population encounters. For example, group selection may operate on human populations during times of intergroup conflict (i.e., warfare), whereas during times of peace, selection may tend to favor the fitness of individuals instead (Woodley and Figueredo 2013; Wilson 2002). A major factor that seems to permit group-level selection to be viable under certain ecological regimes is the existence of free-rider controls, i.e., features of the group’s social ecology that curb the reproductive fitness of the carriers of “selfish” genetic variants (MacDonald 1994; Wilson 2002).


High-status individuals participate in the generation and vertical cultural transmission of free-rider controls—these take the form of religious and ideological systems which make a virtue out of behaviors that overtly benefit the group, and a vice out of those that only favor individual-level fitness, via the promotion of ethnocentrism, martyrdom, and displays of commitment (MacDonald 1994, 2009, 2010; Wilson 2002). Humans are furthermore equipped with specialized mental adaptations for coordinating as part of a group, such as effortful control—the ability to override implicit behavioral drives via the use of explicit processing systems, which allow them to regulate their behavior based on what is optimal for the group (MacDonald 2008). The interaction between individuals of different degrees of status, i.e., those that generate and maintain cultural norms and those who are merely subject to them, therefore constitutes a form of social epistasis, as the complex patterns of interactions among genomes that characterize human culture have the effect of regulating both individual- and group-level (via the curbing of free-riding) fitness (MacDonald 2009, 2010).

Mutations that push the behavior of high-status individuals away from the promotion of group-selected norms may promote a breakdown of or otherwise alter these social epistatic interactions, causing dysregulation of the group’s reproductive ecology. Behavioral changes are furthermore a highly likely consequence of mutation accumulation, as “behavior” (construed broadly) is a large potential target for new mutations (Miller 2000; Lynch 2016) 1 owing to the fact that approximately 84% of all genes in the human genome are involved in some aspect of brain development and/or maintenance (Hawrylycz et al. 2012).

Consistent with the theorized role of group-level (cultural) regulatory processes in the maintenance of fitness optima, positive correlations exist between religiosity (a major freerider control; MacDonald 1994; Wilson 2002) and fertility, both at the individual differences and cross-cultural levels (Meisenberg 2011). Religiosity has declined in modernized nations—a process that has gone hand-in-hand with the rise of a values system called postmaterialism (Inglehart 1977), which is characterized by the proliferation of individualistic, secular, and antihierarchical values (Welzel 2013). The holding of these values is negatively associated with fertility, both at the individual level (when measured as political liberalism; Goldstone et al. 2011) and across time and cultures (Inglehart and Appel 1989). The rise of postmaterialist values is also associated with increasingly delayed onset of reproduction (Klien 1990) which directly increases the (population) mutation load.

Pathological Altruism

Some of the values embodied in postmaterialism have been linked to the pathological altruism phenomenon, i.e., forms of altruism that damage the intended recipients or givers of largesse (Oakley et al. 2012; Oakley 2013). Virtues associated with altruism such as kindness, fidelity, magnanimity, and heroism, along with quasi-moral traits associated with personality and mental health, may be under sexual selection and might therefore be sensitive, through the f factor, to the deleterious effects of accumulating mutations (Miller 2007).


Another form of pathologically altruistic behavior that Oakley (2013) documents is self-righteousness, which may be increasing, consistent with secular trend data indicating elevated levels of self-regarding behavior among Western populations (sometimes called the narcissism epidemic; Twenge and Campbell 2009). This sort of behavior constitutes a key component of the clever silly phenomenon in which the embrace of counterfactual beliefs is used to leverage social status via virtue signaling (e.g., the conflation of moral equality among individuals, sexes, and populations with biological equality) (Dutton and van der Linden 2015; Charlton 2009; Woodley 2010). There may be a greater number of influential persons inclined to disseminate such beliefs, in that the prevalence of phenotypes disposed toward egoistic behaviors may have increased in Western populations (per Twenge and coworkers’ research), and because egoists, specifically Machiavellians and narcissists, appear advantaged in the acquisition of elite societal stations (Spurk et al. 2015).

[Do Bad Guys Get Ahead or Fall Behind? Relationships of the Dark Triad of Personality With Objective and Subjective Career Success: http://sci-hub.tw/http://journals.sagepub.com/doi/abs/10.1177/1948550615609735

After controlling for other relevant variables (i.e., gender, age, job tenure, organization size, education, and work hours), narcissism was positively related to salary, Machiavellianism was positively related to leadership position and career satisfaction, and psychopathy was negatively related to all analyzed outcomes.]


By altering cultural norms, elite egoists may encourage the efflorescence of selfish behaviors against which some older and once highly influential cultural systems acted. For example, Christianity in various forms strongly promoted personal sacrifice for the good of groups and proscribed egoistic behaviors (Rubin 2015), but has declined significantly in terms of cultural power following modernization (Inglehart 1977). Thus, it is possible that a feedback loop exists wherein deleterious mutation accumulation raises population levels of egoism, either directly or indirectly, via the breakdown of developmental constraints on personality canalization; the resultantly greater number of egoists are then able to exploit relevant personality traits to attain positions of sociocultural influence; and through these … [more]
study  speculation  models  biodet  bio  sapiens  evolution  genetic-load  paternal-age  the-monster  slippery-slope  society  social-structure  free-riding  coordination  EGT  dynamical  🌞  fertility  dysgenics  eh  self-control  obesity  altruism  mutation  multi  twitter  social  commentary  perturbation  gnon  new-religion  science-anxiety  population-genetics  biophysical-econ  hmm  discipline  autism  scitariat  clown-world  epidemiology  malaise  sociology  demographic-transition  blowhards  model-organism  nonlinearity  civilization  expression-survival  universalism-particularism  order-disorder  trends  deep-materialism  values  ideology  domestication  cohesion  christopher-lasch  scale  patho-altruism  social-capital  behavioral-gen  madisonian  chart  nihil  aristos  piracy  theos  cultural-dynamics  roots  zeitgeist  rot  the-bones  counter-revolution  pdf  modernity  microfoundations  video  presentation  religion  christianity  health  longevity  ethnocentrism  genetic-correlation  👽  instinct 
march 2017 by nhaliday
Principal Component Analysis explained visually
The PCA transformation ensures that the horizontal axis PC1 has the most variation, the vertical axis PC2 the second-most, and a third axis PC3 the least.

I think this is equivalent to variational characterization of singular values?
data-science  explanation  visual-understanding  visualization  techtariat  stats  methodology  exploratory  large-factor  better-explained  let-me-see  matrix-factorization 
january 2017 by nhaliday
The g beyond Spearman's g: Flynn's paradoxes resolved using four exploratory meta-analyses
- coauthored by Flynn
- no g-loading in either direction averaged across 4 diseases
- calls into question value of g-loading as indicator of Flynn effect being "hollow"
study  spearhead  psychology  cog-psych  iq  intelligence  psychometrics  trends  meta-analysis  large-factor  disease  neuro  optimism  psych-architecture  flynn  big-peeps 
january 2017 by nhaliday
Information Processing: Chimp intelligence is heritable
The more g-loaded, the more heritable, evolvable, and phenotypically variable: Homology with humans in chimpanzee cognitive abilities: http://www.sciencedirect.com/science/article/pii/S0160289615000495

Relaxed genetic control of cortical organization in human brains compared with chimpanzees: http://www.pnas.org/content/112/48/14799.abstract
We show that the morphology of the human cerebral cortex is substantially less genetically heritable than in chimpanzees and therefore is more responsive to molding by environmental influences. This anatomical property of increased plasticity, which is likely related to the human pattern of development, may underlie our species’ capacity for cultural evolution.

The heritability of chimpanzee and human brain asymmetry: http://rspb.royalsocietypublishing.org/content/283/1845/20161319
humans more lateralized and have lower heritability for degree of asymmetry

A Review of Cognitive Abilities in Dogs, 1911 Through 2016: More Individual Differences, Please!: http://www.lse.ac.uk/CPNSS/people/Staff/rosalind-arden/arden-psychological-science-2016.pdf

A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee: http://rspb.royalsocietypublishing.org/content/royprsb/284/1864/20171323.full.pdf
Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee (Bombus terrestris) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density.
hsu  scitariat  study  summary  nature  intelligence  iq  eden  model-organism  biodet  behavioral-gen  multi  neuro  bio  evolution  sapiens  variance-components  comparison  🌞  org:nat  flexibility  brain-scan  psychometrics  large-factor  pdf  psychology  cog-psych  cocktail  survey  psych-architecture  neuro-nitgrit  correlation  visuo 
december 2016 by nhaliday
Psychological comments: Does Age make us sage or sag?
Khan on Twitter: "figure on right from @tuckerdrob lab is depressing (the knowledge plateau). do i read in vain??? https://t.co/DZzBD8onEv": https://twitter.com/razibkhan/status/809439911627493377
- reasoning rises then declines after age ~20
- knowledge plateaus by age 35-40
- different interpretation provided by study authors w/ another graph (renewal)
- study (can't find the exact graph anywhere): http://www.iapsych.com/wj3ewok/LinkedDocuments/McArdle2002.pdf

School’s out: https://westhunt.wordpress.com/2016/12/29/schools-out/
I saw a note by Razib Khan, in which he mentioned that psychometric research suggests that people plateau in their knowledge base as adults. I could believe it. But I’m not sure it’s true in my case. One might estimate total adult knowledge in terms of BS equivalents…

Age-related IQ decline is reduced markedly after adjustment for the Flynn effect: https://www.ncbi.nlm.nih.gov/m/pubmed/20349385/
Twenty-year-olds outperform 70-year-olds by as much as 2.3 standard deviations (35 IQ points) on subtests of the Wechsler Adult Intelligence Scale (WAIS). We show that most of the difference can be attributed to an intergenerational rise in IQ known as the Flynn effect.


For these verbal subtests, the Flynn effect masked a modest increase in ability as individuals grow older.

Predictors of ageing-related decline across multiple cognitive functions: http://www.sciencedirect.com/science/article/pii/S0160289616302707
Cognitive ageing is likely a process with few large-effect predictors

A strong link between speed of visual discrimination and cognitive ageing: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4123160/
Results showed a moderate correlation (r = 0.460) between inspection time performance and intelligence, and a strong correlation between change in inspection time and change in intelligence from 70 to 76 (r = 0.779). These results support the processing speed theory of cognitive ageing. They go beyond cross-sectional correlation to show that cognitive change is accompanied by changes in basic visual information processing as we age.
albion  psychology  cog-psych  psychometrics  aging  iq  objektbuch  long-term  longitudinal  study  summary  variance-components  scitariat  multi  gnxp  learning  metabuch  twitter  social  discussion  pic  data  planning  tradeoffs  flux-stasis  volo-avolo  west-hunter  studying  knowledge  age-generation  flexibility  rigidity  plots  manifolds  universalism-particularism  being-becoming  essence-existence  intelligence  stock-flow  large-factor  psych-architecture  visuo  correlation  time  speed  short-circuit  roots  flynn  trends  dysgenics  language  explanans  direction  chart 
december 2016 by nhaliday
Relationships among processing speed, working memory, and fluid intelligence in children. - PubMed - NCBI
We conclude from our review of the literature that the development of processing speed, working memory, and fluid intelligence, all follow a similar time course, suggesting that all three abilities develop in concert. Furthermore, the strength of the correlation between speed and intelligence does not appear to change with age, and most of the effect of the age-related increase in speed on intelligence appears to be mediated through the effect of speed on working memory. Finally, most of the effect of the age-related improvement in working memory on intelligence is itself attributable to the effect of the increase in speed on working memory, providing evidence of a cognitive developmental cascade.
study  iq  intelligence  cog-psych  psychology  psychometrics  large-factor  aging  psych-architecture 
september 2016 by nhaliday
Information Processing: High V, Low M
Commenter Gwen on the blog Infoproc hints at a possible neurological basis for this phenomenon, stating that “one bit of speculation I have: the neuroimaging studies seem to consistently point towards efficiency of global connectivity rather than efficiency or other traits of individual regions; you could interpret this as a general factor across a wide battery of tasks because they are all hindered to a greater or lesser degree by simply difficulties in coordination while performing the task; so perhaps what causes Spearman is global connectivity becoming around as efficient as possible and no longer a bottleneck for most tasks, and instead individual brain regions start dominating additional performance improvements. So up to a certain level of global communication efficiency, there is a general intelligence factor but then specific abilities like spatial vs verbal come apart and cease to have common bottlenecks and brain tilts manifest themselves much more clearly.” [10] This certainly seem plausible enough. Let’s hope that those far smarter than ourselves will slowly get to the bottom of these matters over the coming decades.


My main prediction here then is that based on HBD, I don’t expect China or East Asia to rival the Anglosphere in the life sciences and medicine or other verbally loaded scientific fields. Perhaps China can mirror Japan in developing pockets of strengths in various areas of the life sciences. Given its significantly larger population, this might indeed translate into non-trivial high-end output in the fields of biology and biomedicine. The core strengths of East Asian countries though, as science in the region matures, will lie primarily in quantitative areas such as physics or chemistry, and this is where I predict the region will shine in the coming years. China’s recent forays into quantum cryptography provide one such example. [40]


In fact, as anyone who’s been paying attention has noticed, modern day tech is essentially a California and East Asian affair, with the former focused on software and the latter more so on hardware. American companies dominate in the realm of internet infrastructure and platforms, while East Asia is predominant in consumer electronics hardware, although as noted, China does have its own versions of general purpose tech giants in companies like Baidu, Alibaba, and Tencent. By contrast, Europe today has relatively few well known tech companies apart from some successful apps such as Spotify or Skype and entities such as Nokia or Ericsson. [24] It used to have more established technology companies back in the day, but the onslaught of competition from the US and East Asia put a huge dent in Europe’s technology industry.


Although many will point to institutional factors such as China or the United States enjoying large, unfragmented markets to explain the decline of European tech, I actually want to offer a more HBD oriented explanation not only for why Europe seems to lag in technology and engineering relative to America and East Asia, but also for why tech in the United States is skewed towards software, while tech in East Asia is skewed towards hardware. I believe that the various phenomenon described above can all be explained by one common underlying mechanism, namely the math/verbal split. Simply put, if you’re really good at math, you gravitate towards hardware. If your skills are more verbally inclined, you gravitate towards software. In general, your chances of working in engineering and technology are greatly bolstered by being spatially and quantitatively adept.


If my assertions here are correct, I predict that over the coming decades, we’ll increasingly see different groups of people specialize in areas where they’re most proficient at. This means that East Asians and East Asian societies will be characterized by a skew towards quantitative STEM fields such as physics, chemistry, and engineering and towards hardware and high-tech manufacturing, while Western societies will be characterized by a skew towards the biological sciences and medicine, social sciences, humanities, and software and services. [41] Likewise, India also appears to be a country whose strengths lie more in software and services as opposed to hardware and manufacturing. My fundamental thesis is that all of this is ultimately a reflection of underlying HBD, in particular the math/verbal split. I believe this is the crucial insight lacking in the analyses others offer.


Sailer In TakiMag: What Does the Deep History of China and India Tell Us About Their Futures?: http://takimag.com/article/a_pair_of_giants_steve_sailer/print#axzz5BHqRM5nD
In an age of postmodern postnationalism that worships diversity, China is old-fashioned. It’s homogeneous, nationalist, and modernist. China seems to have utilitarian 1950s values.

For example, Chinese higher education isn’t yet competitive on the world stage, but China appears to be doing a decent job of educating the masses in the basics. High Chinese scores on the international PISA test for 15-year-olds shouldn’t be taken at face value, but it’s likely that China is approaching first-world norms in providing equality of opportunity through adequate schooling.

Due to censorship and language barriers, Chinese individuals aren’t well represented in English-language cyberspace. Yet in real life, the Chinese build things, such as bridges that don’t fall down, and they make stuff, employing tens of millions of proletarians in their factories.

The Chinese seem, on average, to be good with their hands, which is something that often makes American intellectuals vaguely uncomfortable. But at least the Chinese proles are over there merely manufacturing things cheaply, so American thinkers don’t resent them as much as they do American tradesmen.

Much of the class hatred in America stems from the suspicions of the intelligentsia that plumbers and mechanics are using their voodoo cognitive ability of staring at 3-D physical objects and somehow understanding why they are broken to overcharge them for repairs. Thus it’s only fair, America’s white-collar managers assume, that they export factory jobs to lower-paid China so that they can afford to throw manufactured junk away when it breaks and buy new junk rather than have to subject themselves to the humiliation of admitting to educationally inferior American repairmen that they don’t understand what is wrong with their own gizmos.


This Chinese lack of diversity is out of style, and yet it seems to make it easier for the Chinese to get things done.

In contrast, India appears more congenial to current-year thinkers. India seems postmodern and postnationalist, although it might be more accurately called premodern and prenationalist.


Another feature that makes our commentariat comfortable with India is that Indians don’t seem to be all that mechanically facile, perhaps especially not the priestly Brahmin caste, with whom Western intellectuals primarily interact.

And the Indians tend to be more verbally agile than the Chinese and more adept at the kind of high-level abstract thinking required by modern computer science, law, and soft major academia. Thousands of years of Brahmin speculations didn’t do much for India’s prosperity, but somehow have prepared Indians to make fortunes in 21st-century America.

- Study used two moderately large American community samples.
- Verbal and not nonverbal ability drives relationship between ability and ideology.
- Ideology and ability appear more related when ability assessed professionally.
- Self-administered or nonverbal ability measures will underestimate this relationship.

Every once in a while I realize something with my conscious mind that I’ve understood implicitly for a long time. Such a thing happened to me yesterday, while reading a post on Stalin, by Amritas. It is this:

S = P + E

Social Status equals Political Capital plus Economic Capital


Here’s an example of its explanatory power: If we assume that a major human drive is to maximize S, we can predict that people with high P will attempt to minimize the value of E (since S-maximization is a zero-sum game). And so we see. Throughout history there has been an attempt to ennoble P while stigmatizing E. Conversely, throughout history, people with high E use it to acquire P. Thus, in today’s society we see that socially adept people, who have inborn P skills, tend to favor socialism or big government – where their skills are most valuable, while economically productive people are often frustrated by the fact that their concrete contribution to society is deplored.

Now, you might ask yourself why the reverse isn’t true, why people with high P don’t use it to acquire E, while people with high E don’t attempt to stigmatize P? Well, I think that is true. But, while the equation is mathematically symmetrical, the nature of P-talent and E-talent is not. P-talent can be used to acquire E from the E-adept, but the E-adept are no match for the P-adept in the attempt to stigmatize P. Furthermore, P is endogenous to the system, while E is exogenous. In other words, the P-adept have the ability to manipulate the system itself to make P-talent more valuable in acquiring E, while the E-adept have no ability to manipulate the external environment to make E-talent more valuable in acquiring P.


1. All institutions will tend to be dominated by the P-adept
2. All institutions that have no in-built exogenous criteria for measuring its members’ status will inevitably be dominated by the P-adept
3. Universities will inevitably be dominated by the P-adept
4. Within a university, humanities and social sciences will be more dominated by the P-adept than … [more]
iq  science  culture  critique  lol  hsu  pre-2013  scitariat  rationality  epistemic  error  bounded-cognition  descriptive  crooked  realness  being-right  info-dynamics  truth  language  intelligence  kumbaya-kult  quantitative-qualitative  multi  study  psychology  cog-psych  social-psych  ideology  politics  elite  correlation  roots  signaling  psychometrics  status  capital  human-capital  things  phalanges  chart  metabuch  institutions  higher-ed  academia  class-warfare  symmetry  coalitions  strategy  class  s:*  c:**  communism  inequality  socs-and-mops  twitter  social  commentary  gnon  unaffiliated  zero-positive-sum  rot  gnxp  adversarial  🎩  stylized-facts  gender  gender-diff  cooperate-defect  ratty  yvain  ssc  tech  sv  identity-politics  culture-war  reddit  subculture  internet  🐸  discrimination  trump  systematic-ad-hoc  urban  britain  brexit  populism  diversity  literature  fiction  media  military  anomie  essay  rhetoric  martial  MENA  history  mostly-modern  stories  government  polisci  org:popup  right-wing  propaganda  counter-r 
september 2016 by nhaliday
A watershed model of individual differences in fluid intelligence
Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes.
study  iq  intelligence  neuro  methodology  psychometrics  psychology  cog-psych  large-factor  brain-scan  psych-architecture  models  neuro-nitgrit 
august 2016 by nhaliday

bundles : patterns

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