Curt Doolittle

Source: Original Site Post

  • Runcible

    For a long time. Runcible. In honor of Stephenson. A Runcible is a computer that tutors you through storytelling. It’s essentially an adventure game to teach you how to excel. In Neal Stephenson’s 1995 novel The Diamond Age, Runcible is a code name for the Young Lady’s Illustrated Primer, an educational computer. In The Diamond Age, the Runcible is effectively priceless, and while designed for a princess, ends up in the hands of a poor young girl who eventually, due to its tutelage, conducts a Revolution. RUNCIBLE is also the name of a computer program compiler for an early (late 1950s) programming language. Donald Knuth published the flowchart of the compiler in 1959;[12] this was his first academic paper. The Straight Dope, while treating “runcible” as a nonsense word with no particular meaning, claims that an unspecified 1920s source connected the word “runcible” etymologically to Roncevaux — the connection being that a runcible spoon’s cutting edge resembles a sword such as was used in the Battle of Roncevaux Pass. The Straight Dope adds that “modern students of runciosity” link the word in a different way to Roncevaux: The obsolete adjective “rouncival”, meaning “gigantic”, also derives from Roncevaux, either by way of a certain large variety of pea grown there, or from a once-current find of gigantic fossilized bones in the region. “Runcible” is a nonsense word invented by Edward Lear. The word appears several times in his works, most famously as the “runcible spoon”.

  • It’s Only Arrogance If Your Wrong: Taleb, Doolittle, Lisi, And … Langan.

    It’s only arrogance if you’re wrong. And unwillingness to invest in education of others is not arrogance. It’s just rational choice. Most accusations of arrogance are acts of fraud – attempting to use guilt rather than reason and evidence to obtain consensus. People can engage in denial, but that’s not arrogance. People can engage in fallacy. That’s not arrogance.That’s just deceit. So accuse yourself of incompetency in competing with others’ opinions, or accuse them of denial and deceit. End gossip rally and shaming and work with truth falsehood, productivity and theft. Now, there is a problem with insufficiency of argument. For example, Nassim Taleb has tried the top down method of trying to quantify the information necessary to limit claims in the face of disruptive outliers. And he has recently (as did Hayek, and have I, and to some degree popper) come to the conclusion that only warranty of due diligence can achieve what he’d hope to achieve quantitatively. (I believe the quantitative problem will be solved by a unit of measure we will obtain from analysis of artificial intelligence software, but otherwise there is no unit of measure we can make use of.) So he has produced narratives on one hand, and math on the other, and the reality is that without some unit of measure, all we can say is that knowledge demands increase at least logarithmically. Now, I’ve looked at pseudoscientific claims from dozens if not hundreds of people. And this includes the Electric Universe Theory, and of course, more recently Christopher Langan’s theory. And while I understand someone like taleb cannot achieve his goals because the information doesn’t exist to measure, Langan’s theory is a fictionalism (narrative) that assumes information exists that cannot. In other words, langan is constructing a justification for (proof) of god, instead of stating the obvious: any set of rules whose test of survival is seeking equilibrium will produce candidate operations, in increasing layers (layers of sets produced by possibilities of underlying operations, and that this might appear to be sentience, rather than sentience is just another layer of complexity on top of those rules. Both Taleb and Langan (as well as myself) come off as arrogant. For the simple reason that the cost of education is so high. In the case of correct (Taleb), and incorrect (Langan) both arguments are fairly easy to decompose into operational language (transfers of information). But while Taleb relies on analogy – and he must because the information is not available to describe mathematically – he is correct. Langan relies upon analogy to *justify a prior narrative* that god exists in some form or another, and his analogies are at best parables. Whereas Garrett Lisi’s theory proposes a mathematica model which is terribly simple, and points us at ‘particles’ missing from our existing model, in the same way the Periodic Table pointed us at elements missing from that layer of operations we call Chemistry (molecules). Lisi is not, seemingly, terribly arrogant (I am jealous of his lifestyle and hope to copy it). The same is true of my work on operationalism. But the difference between Taleb and I, and mathematical physicists like Lisi, is that (while taleb isn’t quite there yet) he and I are proposing law that prohibits people from using innumeracy (taleb) and rationalism (doolittle) to produce fraud using fictionalisms (pseudo-math, pseudoscience, pseudo-logic, pseudo-reason, and pseudo-narration). Because frankly, fraud by fictionalism is largely the means of profit in today’s world. In other words, there is more informational fraud today in western civilization than there is informational fraud in the world religions. So the world is incentivized to resist reformation of law demanding due diligence and warranty (skin in the game), for information distributed in the market for information. But the world was resistant to limiting commercial fraud, product fraud, theft, murder, violence and conquest. The most important lesson of Via Negativa reasoning, is that we have built civilization and all its benefits, by incremental suppression of parasitism forcing everyone increasingly into voluntary market production – or extermination. And when we passed human scale in the 1800’s, we did not move from via positiva justificationary reasoning (normative, moral and religious) to via negativa critical reasoning – except in the hard sciences. And that is what people like taleb and I (in our arrogance) are trying to fix.

  • It’s Only Arrogance If Your Wrong: Taleb, Doolittle, Lisi, And … Langan.

    It’s only arrogance if you’re wrong. And unwillingness to invest in education of others is not arrogance. It’s just rational choice. Most accusations of arrogance are acts of fraud – attempting to use guilt rather than reason and evidence to obtain consensus. People can engage in denial, but that’s not arrogance. People can engage in fallacy. That’s not arrogance.That’s just deceit. So accuse yourself of incompetency in competing with others’ opinions, or accuse them of denial and deceit. End gossip rally and shaming and work with truth falsehood, productivity and theft. Now, there is a problem with insufficiency of argument. For example, Nassim Taleb has tried the top down method of trying to quantify the information necessary to limit claims in the face of disruptive outliers. And he has recently (as did Hayek, and have I, and to some degree popper) come to the conclusion that only warranty of due diligence can achieve what he’d hope to achieve quantitatively. (I believe the quantitative problem will be solved by a unit of measure we will obtain from analysis of artificial intelligence software, but otherwise there is no unit of measure we can make use of.) So he has produced narratives on one hand, and math on the other, and the reality is that without some unit of measure, all we can say is that knowledge demands increase at least logarithmically. Now, I’ve looked at pseudoscientific claims from dozens if not hundreds of people. And this includes the Electric Universe Theory, and of course, more recently Christopher Langan’s theory. And while I understand someone like taleb cannot achieve his goals because the information doesn’t exist to measure, Langan’s theory is a fictionalism (narrative) that assumes information exists that cannot. In other words, langan is constructing a justification for (proof) of god, instead of stating the obvious: any set of rules whose test of survival is seeking equilibrium will produce candidate operations, in increasing layers (layers of sets produced by possibilities of underlying operations, and that this might appear to be sentience, rather than sentience is just another layer of complexity on top of those rules. Both Taleb and Langan (as well as myself) come off as arrogant. For the simple reason that the cost of education is so high. In the case of correct (Taleb), and incorrect (Langan) both arguments are fairly easy to decompose into operational language (transfers of information). But while Taleb relies on analogy – and he must because the information is not available to describe mathematically – he is correct. Langan relies upon analogy to *justify a prior narrative* that god exists in some form or another, and his analogies are at best parables. Whereas Garrett Lisi’s theory proposes a mathematica model which is terribly simple, and points us at ‘particles’ missing from our existing model, in the same way the Periodic Table pointed us at elements missing from that layer of operations we call Chemistry (molecules). Lisi is not, seemingly, terribly arrogant (I am jealous of his lifestyle and hope to copy it). The same is true of my work on operationalism. But the difference between Taleb and I, and mathematical physicists like Lisi, is that (while taleb isn’t quite there yet) he and I are proposing law that prohibits people from using innumeracy (taleb) and rationalism (doolittle) to produce fraud using fictionalisms (pseudo-math, pseudoscience, pseudo-logic, pseudo-reason, and pseudo-narration). Because frankly, fraud by fictionalism is largely the means of profit in today’s world. In other words, there is more informational fraud today in western civilization than there is informational fraud in the world religions. So the world is incentivized to resist reformation of law demanding due diligence and warranty (skin in the game), for information distributed in the market for information. But the world was resistant to limiting commercial fraud, product fraud, theft, murder, violence and conquest. The most important lesson of Via Negativa reasoning, is that we have built civilization and all its benefits, by incremental suppression of parasitism forcing everyone increasingly into voluntary market production – or extermination. And when we passed human scale in the 1800’s, we did not move from via positiva justificationary reasoning (normative, moral and religious) to via negativa critical reasoning – except in the hard sciences. And that is what people like taleb and I (in our arrogance) are trying to fix.

  • 100 Citations On Iq From Nature

    (I collect lists of cites and bibliographies.) Gottfredson, L. S. Why g matters: The complexity of everyday life. Intelligence 24, 79–132 (1997). Deary, I. J. et al. Genetic contributions to stability and change in intelligence from childhood to old age. Nature 482, 212–214 (2012). Deary, I. J., Strand, S., Smith, P. & Fernandes, C. Intelligence and educational achievement. Intelligence 35, 13–21 (2007). Schmidt, F. L. & Hunter, J. General mental ability in the world of work: occupational attainment and job performance. J. Pers. Soc. Psychol. 86, 162–173 (2004). Strenze, T. Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence 35, 401–426 (2007). Show context Article 6. Calvin, C. M. et al. Childhood intelligence in relation to major causes of death in 68 year follow-up: prospective population study. Brit. Med. J. 357, 2708 (2017). Show context Article 7. Deary, I. J., Pattie, A. & Starr, J. M. The stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychol. Sci. 24, 2361–2368 (2013). Show context PubMedArticle 8. [No authors listed] Intelligence research should not be held back by its past. Nature 545, 385–386 (2017). This editorial is a landmark in the acceptance of genetic influence on intelligence, concluding, “it’s well established and uncontroversial among geneticists that together, differences in genetics underwrite significant variation in intelligence between people.” Show context 9. Pinker, S. The Blank Slate: The Modern Denial of Human Nature (Penguin, 2003). Show context 10. Block, N. J. & Dworkin, G. E. The IQ Controversy: Critical Readings (Pantheon, 1976). Show context 11. Gould, S. J. The Mismeasure of Man (W.W. Norton, 1982). Show context 12. Kamin, L. J. The Science and Politics of IQ (Routledge, 1974). Show context 13. Bouchard, T. J. & McGue, M. Familial studies of intelligence: a review. Science 212, 1055–1059 (1981). Show context PubMedArticle 14. Knopik, V. S., Neiderheiser, J., DeFries, J. C. & Plomin, R. Behavioral Genetics. 7th edn (Worth, 2017). Show context 15. Haier, R. J. The Neuroscience of Intelligence (Cambridge Univ. Press, 2016). Show context 16. Hare, B. Survival of the friendliest: Homo sapiens evolved via selection for prosociality. Annu. Rev. Psychol. 68, 155–186 (2017). Show context PubMedArticle 17. Sternberg, R. J. & Kaufman, J. C. The Evolution of Intelligence (Psychology Press, 2013). Show context 18. Chabris, C. F. et al. Most reported genetic associations with general intelligence are probably false positives. Psychol. Sci. 23, 1314–1323 (2012). Show context PubMedArticle 19. Benyamin, B. et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol. Psychiatry 19, 253–258 (2014). Show context CASPubMedArticle 20. Butcher, L. M., Davis, O. S., Craig, I. W. & Plomin, R. Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays. Genes Brain Behav. 7, 435–446 (2008). Show context CASPubMedArticle 21. Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). Show context CASPubMedArticle 22. Davies, G. et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53 949). Mol. Psychiatry 20, 183–192 (2015). Show context CASPubMedArticle 23. Davies, G. et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151). Mol. Psychiatry 21, 758–767 (2016). Show context CASPubMedArticle 24. Plomin, R. et al. A genome-wide scan of 1842 DNA markers for allelic associations with general cognitive ability: a five-stage design using DNA pooling and extreme selected groups. Behav. Genet. 31, 497–509 (2001). Show context CASPubMedArticle 25. Trampush, J. et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol. Psychiatry 22, 336 (2017). Show context PubMedArticle 26. Cesarini, D. & Visscher, P. M. Genetics and educational attainment. Sci. Learn. 2, 1–7 (2017). Show context Article 27. Rietveld, C. A. et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc. Natl Acad. Sci. USA 111, 13790–13794 (2014). This study uses EA1 SNPs to predict intelligence, although less than 1% of the variance is predicted. Show context CASPubMedArticle 28. Rietveld, C. A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013). This is the GWAS origin of EA1, which yields a GPS that predicts 1% of the variance in years of education. Show context CASPubMedArticle 29. Rietveld, C. A. et al. Replicability and robustness of genome-wide-association studies for behavioral traits. Psychol. Sci. 25, 1975–1986 (2014). Show context PubMedArticle 30. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016). This is the GWAS origin of EA2 GPS, which increases the prediction of educational attainment from 1% to 3% of the variance. Show context CASPubMedArticle 31. Behavior Genetics Association 47th Annual Meeting Abstracts. Okbay, A. et al. GWAS of educational attainment – phase 3: main results [abstract]. Behav. Genet. 47, 699 (2017). This study refers to the largest GWAS of educational attainment (n = 1,100,000), which increases the power of its GPS, EA3, to predict more than 10% of the variance in the targeted trait. Show context 32. von Stumm, S. & Plomin, R. Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence 48, 30–36 (2015). Show context PubMedArticle 33. Sniekers, S. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat. Genet. 49, 1107–1112 (2017). This is the GWAS origin of IQ2 GPS, which increases the prediction of intelligence from 1% to 3%. Show context PubMedArticle 34. Savage, J. E. et al. GWAS meta-analysis (N = 279,930) identifies new genes and functional links to intelligence. Preprint at https://doi.org/10.1101/184853 (2017). This paper describes the largest GWAS of intelligence to date, which yields a GPS (IQ3) that predicts 4% of the variance in intelligence. Show context 35. Davies, G. et al. Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360). Preprint at https://doi.org/10.1101/176511 (2017). Show context 36. Krapohl, E. et al. Multi-polygenic score approach to trait prediction. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.163 (2017). This study employs a multiple-GPS approach and finds that 81 GPSs derived from well-powered GWAS predict 5% of the variance in intelligence. Show context 37. Hill, W. D., Davies, G., McIntosh, A. M., Gale, C. R. & Deary, I. J. A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence. Preprint at https://doi.org/10.1101/160291 (2017). This study employs multiple-trait analysis of GWAS for intelligence and finds that educational attainment and income predict 7% of the variance in intelligence in an independent sample. Show context 38. Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). Show context CASPubMedArticle 39. Plomin, R. et al. Common DNA markers can account for more than half of the genetic influence on cognitive abilities. Psychol. Sci. 24, 562–568 (2013). Show context PubMedArticle 40. Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017). Show context PubMedArticle 41. Plomin, R. Blueprint: How DNA Makes Us Who We Are (Allen Lane/Penguin, in the press). This book describes genetic research on behaviour from twin studies to the DNA revolution and its implications for science and society. Show context 42. Honzik, M. P., Macfarlane, J. W. & Allen, L. The stability of mental test performance between two and eighteen years. J. Exp. Educ. 17, 309–324 (1948). Show context Article 43. Haworth, C. M. et al. A twin study of the genetics of high cognitive ability selected from 11,000 twin pairs in six studies from four countries. Behav. Genet. 39, 359–370 (2009). Show context PubMedArticle 44. Plomin, R. & Deary, I. J. Genetics and intelligence differences: five special findings. Mol. Psychiatry 20, 98–108 (2015). This article highlights five genetic findings that are special to intelligence differences, including one not mentioned in this Review — assortative mating is much greater for intelligence than for other traits. Show context CASPubMedArticle 45. Briley, D. A. & Tucker-Drob, E. M. Explaining the increasing heritability of cognitive ability across development: a meta-analysis of longitudinal twin and adoption studies. Psychol. Sci. 24, 1704–1713 (2013). Show context PubMedArticle 46. Selzam, S. et al. Predicting educational achievement from DNA. Mol. Psychiatry 22, 267–272 (2017). This study shows that EA2 predicts 9% of the variance in tested educational achievement at age 16, which was the strongest GPS prediction of a behavioural trait at that time. Show context PubMedArticle 47. Plomin, R. & Kovas, Y. Generalist genes and learning disabilities. Psychol. Bull. 131, 592–617 (2005). Show context PubMedArticle 48. Selzam, S. et al. Genome-wide polygenic scores predict reading performance throughout the school years. Sci. Stud. Read. 21, 334–349 (2017). Show context PubMedArticle 49. Carrion-Castillo, A. et al. Evaluation of results from genome-wide studies of language and reading in a novel independent dataset. Genes Brain Behav. 15, 531–541 (2016). Show context PubMedArticle 50. Krapohl, E. et al. Phenome-wide analysis of genome-wide polygenic scores. Mol. Psychiatry 21, 1188–1193 (2015). Show context PubMedArticle 51. Marioni, R. E. et al. Common genetic variants explain the majority of the correlation between height and intelligence: the generation Scotland study. Behav. Genet. 44, 91–96 (2014). Show context PubMedArticle 52. Williams, K. M. et al. Phenotypic and genotypic correlation between myopia and intelligence. Sci. Rep. 7, 45977 (2017). Show context PubMedArticle 53. Hill, W. D. et al. Age-dependent pleiotropy between general cognitive function and major psychiatric disorders. Biol. Psychiatry 80, 266–273 (2016). Show context PubMedArticle 54. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). Show context CASPubMedArticle 55. Plomin, R., Haworth, C. M. & Davis, O. S. Common disorders are quantitative traits. Nat. Rev. Genet. 10, 872–878 (2009). Show context CASPubMedArticle 56. Spain, S. L. et al. A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence. Mol. Psychiatry 21, 1145–1151 (2016). Show context PubMedArticle 57. Zabaneh, D. et al. A genome-wide association study for extremely high intelligence. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.121 (2017). This GWAS of intelligence uses a novel strategy to increase power — a case–control design in which the subjects were individuals with extremely high IQ from the top 0.0003 of the population (mean IQ of 170). Show context 58. Reichenberg, A. et al. Discontinuity in the genetic and environmental causes of the intellectual disability spectrum. Proc. Natl Acad. Sci. USA 113, 1098–1103 (2016). Show context CASPubMedArticle 59. Vissers, L. E., Gilissen, C. & Veltman, J. A. Genetic studies in intellectual disability and related disorders. Nat. Rev. Genet. 17, 9–18 (2016). Show context CASPubMedArticle 60. Plomin, R. & Daniels, D. Why are children in the same family so different from one another? Behav. Brain Sci. 10, 1–16 (1987). Show context Article 61. Tucker-Drob, E. M. & Bates, T. C. Large cross-national differences in gene × socioeconomic status interaction on intelligence. Psychol. Sci. 27, 138–149 (2016). Show context PubMedArticle 62. Hanscombe, K. B. et al. Socioeconomic status (SES) and children’s intelligence (IQ): in a UK-representative sample SES moderates the environmental, not genetic, effect on IQ. PLOS ONE 7, e30320 (2012). Show context PubMedArticle 63. Plomin, R. & Bergeman, C. S. The nature of nurture: genetic influence on “environmental” measures. Behav. Brain Sci. 14, 373–386 (1991). Show context Article 64. Belsky, D. W. et al. The genetics of success. Psychol. Sci. 27, 957–972 (2016). Show context PubMedArticle 65. Krapohl, E. et al. Widespread covariation of early environmental exposures and trait-associated polygenic variation. Proc. Natl Acad. Sci. USA 114, 11727–11732 (2017). Show context PubMedArticle 66. Smith-Woolley, E. et al. Differences in exam performance between pupils attending different school types mirror the genetic differences between them. NPJ Sci. Learn. (in the press). Show context 67. Ayorech, Z., Krapohl, E., Plomin, R. & von Stumm, S. Genetic influence on intergenerational educational attainment. Psychol. Sci. 28, 1302–1310 (2017). This paper describes both twin analyses and EA2 GPSs that show genetic influence on intergenerational EA. Show context PubMedArticle 68. Behavior Genetics Association 46th Annual Meeting Abstracts. Rimfeld, K., Trzaskowski, M., Esko, T., Metspalu, A. & Plomin, R. Genetic influence on educational attainment and occupational status during and after the Soviet era in Estonia [abstract]. Behav. Genet. 46, 803 (2016). Show context 69. Plomin, R. & DeFries, J. C. Genetics and intelligence: recent data. Intelligence 4, 15–24 (1980). Show context Article 70. McEwen, J. E. et al. The ethical, legal, and social implications program of the National Human Genome Research Institute: reflections on an ongoing experiment. Annu. Rev. Genom. Hum. Genet. 15, 481–504 (2014). Show context Article 71. Bouregy, S., Grigorenko, E. L., Latham, S. R. & Tan, M. Genetics, Ethics and Education (Cambridge Univ. Press, 2017). Show context 72. Conley, D. & Fletcher, J. The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, our History, and the Future (Princeton Univ. Press, 2017). Show context 73. Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum Associates, 1977). Show context 74. Gottfredson, L. S. Mainstream science on intelligence. Wall Street Journal (13 December 1994). Show context 75. Carroll, J. B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies (Cambridge Univ. Press, 1993). Show context 76. Spearman, C. ‘General Intelligence’ objectively determined and measured. Am. J. Psychol. 15, 201–292 (1904). Show context Article 77. Jensen, A. R. The g Factor: The Science of Mental Ability (Praeger, 1998). Show context 78. Deary, I. J. Intelligence. Annu. Rev. Psychol. 63, 453–482 (2012). This article is an authoritative overview of intelligence research. Show context PubMedArticle 79. Gow, A. J. et al. Stability and change in intelligence from age 11 to ages 70, 79, and 87: the Lothian Birth Cohorts of 1921 and 1936. Psychol. Ageing 26, 232–240 (2011). Show context Article 80. Schaie, K. W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study (Oxford Univ. Press, 2005). Show context 81. Brinch, C. N. & Galloway, T. A. Schooling in adolescence raises IQ scores. Proc. Natl Acad. Sci. USA 109, 425–430 (2012). Show context PubMedArticle 82. Protzko, J. Does the raising IQ–raising g distinction explain the fadeout effect? Intelligence 56, 65–71 (2016). Show context Article 83. Duyme, M., Dumaret, A.-C. & Tomkiewicz, S. How can we boost IQs of “dull children”?: a late adoption study. Proc. Natl Acad. Sci. USA 96, 8790–8794 (1999). Show context CASPubMedArticle 84. Melby-Lervåg, M. & Hulme, C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 49, 270–291 (2013). Show context PubMedArticle 85. Puma, M. et al. Head Start Impact Study Final Report. Administration for Children and Families https://www.acf.hhs.gov/sites/default/files/opre/hs_impact_study_final.pdf (2010). Show context 86. Plomin, R. & Simpson, M. A. The future of genomics for developmentalists. Dev. Psychopathol. 25, 1263–1278 (2013). Show context PubMedArticle 87. Pasaniuc, B. & Price, A. L. Dissecting the genetics of complex traits using summary association statistics. Nat. Rev. Genet. 18, 117–127 (2017). Show context PubMedArticle 88. Vilhjálmsson, B. J. et al. Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am. J. Hum. Genet. 97, 576–592 (2015). Show context CASPubMedArticle 89. Euseden, J. et al. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015). Show context CASPubMedArticle 90. Hill, W. D. et al. Molecular genetic contributions to social deprivation and household income in UK Biobank. Curr. Biol. 26, 3083–3089 (2016). Show context PubMedArticle 91. Turley, P. et al. MTAG: Multi-Trait Analysis of GWAS. Preprint at https://doi.org/10.1101/118810 (2017). Show context 92. Zheng, J. et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017). Show context PubMedArticle 93. Yang, J. et al. Concepts, estimation and interpretation of SNP-based heritability. Nat. Genet. 49, 1304–1310 (2017). Show context PubMedArticle 94. Sullivan, P. F. et al. Psychiatric genomics: an update and an agenda. Am. J. Psychol. http://dx.doi.org/10.1176/appi.ajp.2017.17030283 (2017). Show context 95. Bacanu, S. A. Sharing extended summary data from contemporary genetic studies is unlikely to threaten subject privacy. PLOS ONE 12, e0179504 (2017). Show context PubMedArticle 96. Calvin, C. M. et al. Multivariate genetic analyses of cognition and academic achievement from two population samples of 174,000 and 166,000 school children. Behav. Genet. 42, 699–710 (2012). Show context PubMedArticle 97. Marioni, R. E. et al. Molecular genetic contributions to socioeconomic status and intelligence. Intelligence 44, 26–32 (2014). Show context PubMedArticle 98. Branigan, A. R., McCallum, K. J. & Freese, J. Variation in the heritability of educational attainment: An international meta-analysis. Soc. Forces 92, 109–140 (2013). Show context Article 99. Krapohl, E. et al. The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proc. Natl Acad. Sci. USA 111, 15273–15278 (2014). Show context CASPubMedArticle 100. Haworth, C. M., Davis, O. S. & Plomin, R. Twins Early Development Study (TEDS): a genetically sensitive investigation of cognitive and behavioral development from childhood to young adulthood. Twin Res. Hum. Genet. 16, 117–125 (2013). Show context

  • 100 Citations On Iq From Nature

    (I collect lists of cites and bibliographies.) Gottfredson, L. S. Why g matters: The complexity of everyday life. Intelligence 24, 79–132 (1997). Deary, I. J. et al. Genetic contributions to stability and change in intelligence from childhood to old age. Nature 482, 212–214 (2012). Deary, I. J., Strand, S., Smith, P. & Fernandes, C. Intelligence and educational achievement. Intelligence 35, 13–21 (2007). Schmidt, F. L. & Hunter, J. General mental ability in the world of work: occupational attainment and job performance. J. Pers. Soc. Psychol. 86, 162–173 (2004). Strenze, T. Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence 35, 401–426 (2007). Show context Article 6. Calvin, C. M. et al. Childhood intelligence in relation to major causes of death in 68 year follow-up: prospective population study. Brit. Med. J. 357, 2708 (2017). Show context Article 7. Deary, I. J., Pattie, A. & Starr, J. M. The stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychol. Sci. 24, 2361–2368 (2013). Show context PubMedArticle 8. [No authors listed] Intelligence research should not be held back by its past. Nature 545, 385–386 (2017). This editorial is a landmark in the acceptance of genetic influence on intelligence, concluding, “it’s well established and uncontroversial among geneticists that together, differences in genetics underwrite significant variation in intelligence between people.” Show context 9. Pinker, S. The Blank Slate: The Modern Denial of Human Nature (Penguin, 2003). Show context 10. Block, N. J. & Dworkin, G. E. The IQ Controversy: Critical Readings (Pantheon, 1976). Show context 11. Gould, S. J. The Mismeasure of Man (W.W. Norton, 1982). Show context 12. Kamin, L. J. The Science and Politics of IQ (Routledge, 1974). Show context 13. Bouchard, T. J. & McGue, M. Familial studies of intelligence: a review. Science 212, 1055–1059 (1981). Show context PubMedArticle 14. Knopik, V. S., Neiderheiser, J., DeFries, J. C. & Plomin, R. Behavioral Genetics. 7th edn (Worth, 2017). Show context 15. Haier, R. J. The Neuroscience of Intelligence (Cambridge Univ. Press, 2016). Show context 16. Hare, B. Survival of the friendliest: Homo sapiens evolved via selection for prosociality. Annu. Rev. Psychol. 68, 155–186 (2017). Show context PubMedArticle 17. Sternberg, R. J. & Kaufman, J. C. The Evolution of Intelligence (Psychology Press, 2013). Show context 18. Chabris, C. F. et al. Most reported genetic associations with general intelligence are probably false positives. Psychol. Sci. 23, 1314–1323 (2012). Show context PubMedArticle 19. Benyamin, B. et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol. Psychiatry 19, 253–258 (2014). Show context CASPubMedArticle 20. Butcher, L. M., Davis, O. S., Craig, I. W. & Plomin, R. Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays. Genes Brain Behav. 7, 435–446 (2008). Show context CASPubMedArticle 21. Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). Show context CASPubMedArticle 22. Davies, G. et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53 949). Mol. Psychiatry 20, 183–192 (2015). Show context CASPubMedArticle 23. Davies, G. et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151). Mol. Psychiatry 21, 758–767 (2016). Show context CASPubMedArticle 24. Plomin, R. et al. A genome-wide scan of 1842 DNA markers for allelic associations with general cognitive ability: a five-stage design using DNA pooling and extreme selected groups. Behav. Genet. 31, 497–509 (2001). Show context CASPubMedArticle 25. Trampush, J. et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol. Psychiatry 22, 336 (2017). Show context PubMedArticle 26. Cesarini, D. & Visscher, P. M. Genetics and educational attainment. Sci. Learn. 2, 1–7 (2017). Show context Article 27. Rietveld, C. A. et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc. Natl Acad. Sci. USA 111, 13790–13794 (2014). This study uses EA1 SNPs to predict intelligence, although less than 1% of the variance is predicted. Show context CASPubMedArticle 28. Rietveld, C. A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013). This is the GWAS origin of EA1, which yields a GPS that predicts 1% of the variance in years of education. Show context CASPubMedArticle 29. Rietveld, C. A. et al. Replicability and robustness of genome-wide-association studies for behavioral traits. Psychol. Sci. 25, 1975–1986 (2014). Show context PubMedArticle 30. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016). This is the GWAS origin of EA2 GPS, which increases the prediction of educational attainment from 1% to 3% of the variance. Show context CASPubMedArticle 31. Behavior Genetics Association 47th Annual Meeting Abstracts. Okbay, A. et al. GWAS of educational attainment – phase 3: main results [abstract]. Behav. Genet. 47, 699 (2017). This study refers to the largest GWAS of educational attainment (n = 1,100,000), which increases the power of its GPS, EA3, to predict more than 10% of the variance in the targeted trait. Show context 32. von Stumm, S. & Plomin, R. Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence 48, 30–36 (2015). Show context PubMedArticle 33. Sniekers, S. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat. Genet. 49, 1107–1112 (2017). This is the GWAS origin of IQ2 GPS, which increases the prediction of intelligence from 1% to 3%. Show context PubMedArticle 34. Savage, J. E. et al. GWAS meta-analysis (N = 279,930) identifies new genes and functional links to intelligence. Preprint at https://doi.org/10.1101/184853 (2017). This paper describes the largest GWAS of intelligence to date, which yields a GPS (IQ3) that predicts 4% of the variance in intelligence. Show context 35. Davies, G. et al. Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360). Preprint at https://doi.org/10.1101/176511 (2017). Show context 36. Krapohl, E. et al. Multi-polygenic score approach to trait prediction. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.163 (2017). This study employs a multiple-GPS approach and finds that 81 GPSs derived from well-powered GWAS predict 5% of the variance in intelligence. Show context 37. Hill, W. D., Davies, G., McIntosh, A. M., Gale, C. R. & Deary, I. J. A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence. Preprint at https://doi.org/10.1101/160291 (2017). This study employs multiple-trait analysis of GWAS for intelligence and finds that educational attainment and income predict 7% of the variance in intelligence in an independent sample. Show context 38. Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). Show context CASPubMedArticle 39. Plomin, R. et al. Common DNA markers can account for more than half of the genetic influence on cognitive abilities. Psychol. Sci. 24, 562–568 (2013). Show context PubMedArticle 40. Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017). Show context PubMedArticle 41. Plomin, R. Blueprint: How DNA Makes Us Who We Are (Allen Lane/Penguin, in the press). This book describes genetic research on behaviour from twin studies to the DNA revolution and its implications for science and society. Show context 42. Honzik, M. P., Macfarlane, J. W. & Allen, L. The stability of mental test performance between two and eighteen years. J. Exp. Educ. 17, 309–324 (1948). Show context Article 43. Haworth, C. M. et al. A twin study of the genetics of high cognitive ability selected from 11,000 twin pairs in six studies from four countries. Behav. Genet. 39, 359–370 (2009). Show context PubMedArticle 44. Plomin, R. & Deary, I. J. Genetics and intelligence differences: five special findings. Mol. Psychiatry 20, 98–108 (2015). This article highlights five genetic findings that are special to intelligence differences, including one not mentioned in this Review — assortative mating is much greater for intelligence than for other traits. Show context CASPubMedArticle 45. Briley, D. A. & Tucker-Drob, E. M. Explaining the increasing heritability of cognitive ability across development: a meta-analysis of longitudinal twin and adoption studies. Psychol. Sci. 24, 1704–1713 (2013). Show context PubMedArticle 46. Selzam, S. et al. Predicting educational achievement from DNA. Mol. Psychiatry 22, 267–272 (2017). This study shows that EA2 predicts 9% of the variance in tested educational achievement at age 16, which was the strongest GPS prediction of a behavioural trait at that time. Show context PubMedArticle 47. Plomin, R. & Kovas, Y. Generalist genes and learning disabilities. Psychol. Bull. 131, 592–617 (2005). Show context PubMedArticle 48. Selzam, S. et al. Genome-wide polygenic scores predict reading performance throughout the school years. Sci. Stud. Read. 21, 334–349 (2017). Show context PubMedArticle 49. Carrion-Castillo, A. et al. Evaluation of results from genome-wide studies of language and reading in a novel independent dataset. Genes Brain Behav. 15, 531–541 (2016). Show context PubMedArticle 50. Krapohl, E. et al. Phenome-wide analysis of genome-wide polygenic scores. Mol. Psychiatry 21, 1188–1193 (2015). Show context PubMedArticle 51. Marioni, R. E. et al. Common genetic variants explain the majority of the correlation between height and intelligence: the generation Scotland study. Behav. Genet. 44, 91–96 (2014). Show context PubMedArticle 52. Williams, K. M. et al. Phenotypic and genotypic correlation between myopia and intelligence. Sci. Rep. 7, 45977 (2017). Show context PubMedArticle 53. Hill, W. D. et al. Age-dependent pleiotropy between general cognitive function and major psychiatric disorders. Biol. Psychiatry 80, 266–273 (2016). Show context PubMedArticle 54. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). Show context CASPubMedArticle 55. Plomin, R., Haworth, C. M. & Davis, O. S. Common disorders are quantitative traits. Nat. Rev. Genet. 10, 872–878 (2009). Show context CASPubMedArticle 56. Spain, S. L. et al. A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence. Mol. Psychiatry 21, 1145–1151 (2016). Show context PubMedArticle 57. Zabaneh, D. et al. A genome-wide association study for extremely high intelligence. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.121 (2017). This GWAS of intelligence uses a novel strategy to increase power — a case–control design in which the subjects were individuals with extremely high IQ from the top 0.0003 of the population (mean IQ of 170). Show context 58. Reichenberg, A. et al. Discontinuity in the genetic and environmental causes of the intellectual disability spectrum. Proc. Natl Acad. Sci. USA 113, 1098–1103 (2016). Show context CASPubMedArticle 59. Vissers, L. E., Gilissen, C. & Veltman, J. A. Genetic studies in intellectual disability and related disorders. Nat. Rev. Genet. 17, 9–18 (2016). Show context CASPubMedArticle 60. Plomin, R. & Daniels, D. Why are children in the same family so different from one another? Behav. Brain Sci. 10, 1–16 (1987). Show context Article 61. Tucker-Drob, E. M. & Bates, T. C. Large cross-national differences in gene × socioeconomic status interaction on intelligence. Psychol. Sci. 27, 138–149 (2016). Show context PubMedArticle 62. Hanscombe, K. B. et al. Socioeconomic status (SES) and children’s intelligence (IQ): in a UK-representative sample SES moderates the environmental, not genetic, effect on IQ. PLOS ONE 7, e30320 (2012). Show context PubMedArticle 63. Plomin, R. & Bergeman, C. S. The nature of nurture: genetic influence on “environmental” measures. Behav. Brain Sci. 14, 373–386 (1991). Show context Article 64. Belsky, D. W. et al. The genetics of success. Psychol. Sci. 27, 957–972 (2016). Show context PubMedArticle 65. Krapohl, E. et al. Widespread covariation of early environmental exposures and trait-associated polygenic variation. Proc. Natl Acad. Sci. USA 114, 11727–11732 (2017). Show context PubMedArticle 66. Smith-Woolley, E. et al. Differences in exam performance between pupils attending different school types mirror the genetic differences between them. NPJ Sci. Learn. (in the press). Show context 67. Ayorech, Z., Krapohl, E., Plomin, R. & von Stumm, S. Genetic influence on intergenerational educational attainment. Psychol. Sci. 28, 1302–1310 (2017). This paper describes both twin analyses and EA2 GPSs that show genetic influence on intergenerational EA. Show context PubMedArticle 68. Behavior Genetics Association 46th Annual Meeting Abstracts. Rimfeld, K., Trzaskowski, M., Esko, T., Metspalu, A. & Plomin, R. Genetic influence on educational attainment and occupational status during and after the Soviet era in Estonia [abstract]. Behav. Genet. 46, 803 (2016). Show context 69. Plomin, R. & DeFries, J. C. Genetics and intelligence: recent data. Intelligence 4, 15–24 (1980). Show context Article 70. McEwen, J. E. et al. The ethical, legal, and social implications program of the National Human Genome Research Institute: reflections on an ongoing experiment. Annu. Rev. Genom. Hum. Genet. 15, 481–504 (2014). Show context Article 71. Bouregy, S., Grigorenko, E. L., Latham, S. R. & Tan, M. Genetics, Ethics and Education (Cambridge Univ. Press, 2017). Show context 72. Conley, D. & Fletcher, J. The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, our History, and the Future (Princeton Univ. Press, 2017). Show context 73. Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum Associates, 1977). Show context 74. Gottfredson, L. S. Mainstream science on intelligence. Wall Street Journal (13 December 1994). Show context 75. Carroll, J. B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies (Cambridge Univ. Press, 1993). Show context 76. Spearman, C. ‘General Intelligence’ objectively determined and measured. Am. J. Psychol. 15, 201–292 (1904). Show context Article 77. Jensen, A. R. The g Factor: The Science of Mental Ability (Praeger, 1998). Show context 78. Deary, I. J. Intelligence. Annu. Rev. Psychol. 63, 453–482 (2012). This article is an authoritative overview of intelligence research. Show context PubMedArticle 79. Gow, A. J. et al. Stability and change in intelligence from age 11 to ages 70, 79, and 87: the Lothian Birth Cohorts of 1921 and 1936. Psychol. Ageing 26, 232–240 (2011). Show context Article 80. Schaie, K. W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study (Oxford Univ. Press, 2005). Show context 81. Brinch, C. N. & Galloway, T. A. Schooling in adolescence raises IQ scores. Proc. Natl Acad. Sci. USA 109, 425–430 (2012). Show context PubMedArticle 82. Protzko, J. Does the raising IQ–raising g distinction explain the fadeout effect? Intelligence 56, 65–71 (2016). Show context Article 83. Duyme, M., Dumaret, A.-C. & Tomkiewicz, S. How can we boost IQs of “dull children”?: a late adoption study. Proc. Natl Acad. Sci. USA 96, 8790–8794 (1999). Show context CASPubMedArticle 84. Melby-Lervåg, M. & Hulme, C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 49, 270–291 (2013). Show context PubMedArticle 85. Puma, M. et al. Head Start Impact Study Final Report. Administration for Children and Families https://www.acf.hhs.gov/sites/default/files/opre/hs_impact_study_final.pdf (2010). Show context 86. Plomin, R. & Simpson, M. A. The future of genomics for developmentalists. Dev. Psychopathol. 25, 1263–1278 (2013). Show context PubMedArticle 87. Pasaniuc, B. & Price, A. L. Dissecting the genetics of complex traits using summary association statistics. Nat. Rev. Genet. 18, 117–127 (2017). Show context PubMedArticle 88. Vilhjálmsson, B. J. et al. Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am. J. Hum. Genet. 97, 576–592 (2015). Show context CASPubMedArticle 89. Euseden, J. et al. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015). Show context CASPubMedArticle 90. Hill, W. D. et al. Molecular genetic contributions to social deprivation and household income in UK Biobank. Curr. Biol. 26, 3083–3089 (2016). Show context PubMedArticle 91. Turley, P. et al. MTAG: Multi-Trait Analysis of GWAS. Preprint at https://doi.org/10.1101/118810 (2017). Show context 92. Zheng, J. et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017). Show context PubMedArticle 93. Yang, J. et al. Concepts, estimation and interpretation of SNP-based heritability. Nat. Genet. 49, 1304–1310 (2017). Show context PubMedArticle 94. Sullivan, P. F. et al. Psychiatric genomics: an update and an agenda. Am. J. Psychol. http://dx.doi.org/10.1176/appi.ajp.2017.17030283 (2017). 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  • by @MartialSociety The Great Intellectual division of The West—Aristotle vs Plat

    by @MartialSociety The Great Intellectual division of The West—Aristotle vs Platonism, Empiricism vs Rationalism, Naturalism vs Idealism—finds its origins in the acquisitional (worldly) conflict between those who posses agency, and consequently produce order & the transcendence of Man from beast… …to gods through the incremental mastery over self, ignorance & nature against those who lack agency, submit to chaos, produce a dysgenic dominance hierarchy & surrender to a hostile & unknowble nature. Less poetically, this conflict has always been familial (genetic) in nature, and that by the time of the Axial age, that warfare became of those who can compete in the market for rule & sovereignty against those who could not compete nor provide sufficient incentive to… …cooperate by market through strict observance to the natural laws of sovereign men & to the norms that produce (increase) & maintain agency. More scientifically, Inter-group (familial, tribal, ethnic, racial) competition in the acquisition of (a) resources (free-energy & raw materials, which we employ in the production of consumption goods, capital & (warfare) technologies at increasing rates of entropy dissipation).. … (b) females (temporal persistence: genetic survival across time) & (c) territorial assets (strategic holdings of superior land, ports, trade routes & natural defense) selects for groups with marginally, yet incrementally, superior/optimal management of human capital by norm.. …law & institutions via incremental elimination/suppression (negativa) of groups with suboptimal, marginally inferior institutions, norms, genetic capital, territorial (resource) holdings. Let us return from our detour, though it is worthy to note that I found the reduction necessary so as to avoid any charges that I hold to convictions contrary to the facts produced by the sciences, but I also wanted to preface a more abstract discussion on language and grammars.. …with parallel (commensurable) arguments, written with increasing informational completeness covarying with specificity in terminology, and varying inversely with the degree of assumed context (shared frames of reference). As outlined above, incompletely admittedly, the origin of philosophical (metaphysical, epistemic & methodological) disagreement stems from genetic conflict. And we know that from the cognitive sciences that the latter determines the former, though the particular-manifestations… …will vary according to the relevant decision-ecologies; which can be modeled as Nash equilibriums, as acquisitional games between competing agents & clusters (familial, tribal, class, ethnic & racial) with three means of acquisition: (a) remuneration, (b) violence… (c) manipulation of social accnting (gossip, fraud & deceit). The agents will be bounded by these constraints & and produce a Pareto-optimal distribution as they inter-act (make choices in a social ecology) w/ other agents in forming & joining clusters (defect<->cooperate axes). & when competing with other agents and clusters (suppression/defense<->parasitism/predation axes). I maintain that competitively-inferior kin-groups and their individual members, have the incentive to form larger coalitions inasmuch as they *must* do so in order to survive… …(resist domestication), &that in order to maintain the cohesiveness (sufficient degree of non-conflict) of coalitions between non-kin requires the production of abstract (non-worldly) symbols and memes, and consequently the norms & signals required for… …the functioning of the dominance hierarchy.

  • by @MartialSociety The Great Intellectual division of The West—Aristotle vs Plat

    by @MartialSociety The Great Intellectual division of The West—Aristotle vs Platonism, Empiricism vs Rationalism, Naturalism vs Idealism—finds its origins in the acquisitional (worldly) conflict between those who posses agency, and consequently produce order & the transcendence of Man from beast… …to gods through the incremental mastery over self, ignorance & nature against those who lack agency, submit to chaos, produce a dysgenic dominance hierarchy & surrender to a hostile & unknowble nature. Less poetically, this conflict has always been familial (genetic) in nature, and that by the time of the Axial age, that warfare became of those who can compete in the market for rule & sovereignty against those who could not compete nor provide sufficient incentive to… …cooperate by market through strict observance to the natural laws of sovereign men & to the norms that produce (increase) & maintain agency. More scientifically, Inter-group (familial, tribal, ethnic, racial) competition in the acquisition of (a) resources (free-energy & raw materials, which we employ in the production of consumption goods, capital & (warfare) technologies at increasing rates of entropy dissipation).. … (b) females (temporal persistence: genetic survival across time) & (c) territorial assets (strategic holdings of superior land, ports, trade routes & natural defense) selects for groups with marginally, yet incrementally, superior/optimal management of human capital by norm.. …law & institutions via incremental elimination/suppression (negativa) of groups with suboptimal, marginally inferior institutions, norms, genetic capital, territorial (resource) holdings. Let us return from our detour, though it is worthy to note that I found the reduction necessary so as to avoid any charges that I hold to convictions contrary to the facts produced by the sciences, but I also wanted to preface a more abstract discussion on language and grammars.. …with parallel (commensurable) arguments, written with increasing informational completeness covarying with specificity in terminology, and varying inversely with the degree of assumed context (shared frames of reference). As outlined above, incompletely admittedly, the origin of philosophical (metaphysical, epistemic & methodological) disagreement stems from genetic conflict. And we know that from the cognitive sciences that the latter determines the former, though the particular-manifestations… …will vary according to the relevant decision-ecologies; which can be modeled as Nash equilibriums, as acquisitional games between competing agents & clusters (familial, tribal, class, ethnic & racial) with three means of acquisition: (a) remuneration, (b) violence… (c) manipulation of social accnting (gossip, fraud & deceit). The agents will be bounded by these constraints & and produce a Pareto-optimal distribution as they inter-act (make choices in a social ecology) w/ other agents in forming & joining clusters (defect<->cooperate axes). & when competing with other agents and clusters (suppression/defense<->parasitism/predation axes). I maintain that competitively-inferior kin-groups and their individual members, have the incentive to form larger coalitions inasmuch as they *must* do so in order to survive… …(resist domestication), &that in order to maintain the cohesiveness (sufficient degree of non-conflict) of coalitions between non-kin requires the production of abstract (non-worldly) symbols and memes, and consequently the norms & signals required for… …the functioning of the dominance hierarchy.

  • Who Are The Leading Scholars/experts On Human Stupidity?

    (You know, it’s very hard to find research on Via-Negativa subjects. Books on Lying and Deceit are laughable. Books on dishonest argument are positioned as the study of error. Works on intellectual fraud (marx, freud, boaz), are positioned as analysis of error rather than deception. Works on stupidity are actively suppressed, and work on intelligence is only slightly less suppressed.)

    (See current month’s nature. I just took 100 cites from the article on the (genetic) heritability of intelligence.)

    https://www.quora.com/Who-are-the-leading-scholars-experts-on-human-stupidity

  • Who Are The Leading Scholars/experts On Human Stupidity?

    (You know, it’s very hard to find research on Via-Negativa subjects. Books on Lying and Deceit are laughable. Books on dishonest argument are positioned as the study of error. Works on intellectual fraud (marx, freud, boaz), are positioned as analysis of error rather than deception. Works on stupidity are actively suppressed, and work on intelligence is only slightly less suppressed.)

    (See current month’s nature. I just took 100 cites from the article on the (genetic) heritability of intelligence.)

    https://www.quora.com/Who-are-the-leading-scholars-experts-on-human-stupidity

  • “men make endless informational videos, arguments, and trade false insults and t

    —“men make endless informational videos, arguments, and trade false insults and true compliments. Women make selfies, give false compliments, and disapprove, shame, and ridicule anything that implies depreciation of their status, impulses, or emotions.”—