On Herbert Spencer: Encyclopædia Britannica: www.britannica.com/EBchecked/topic/559249/Herbert-Spencer.Google Scholar

Probably the most accessible account of the history of IQ testing from Galton onwards, including Alfred Binet’s work, though tending to favour IQ testing in general: Mackintosh, N. J. (2011). IQ and Human Intelligence. Oxford: Oxford University Press.Google Scholar

Johnson, R. C., McClearn, G., Yuen, S., et al. (1985). Galton’s data a century later. American Psychologist, 40: 875–892.CrossRefGoogle Scholar

On medieval urinalysis: What medieval doctors used to do with urine was once disgusting, cutting edge medicine: www.viralnova.com/urine-doctors. A fairly light introduction to Binet and his legacy: Byford, J., McAvoy, J., and Banyard, P. (2014). Investigating Intelligence. Milton Keynes: Open University Press.Google Scholar

For a history of eugenics in IQ and education: Chitty, C. (2007). Eugenics, Race and Intelligence in Education. London: Bloomsbury. Gould, S. J. (1996). The Mismeasure of Man. New York: W.W. Norton.Google Scholar

On test validity: Markus, K., and Borsboom, D. (2013). Frontiers of Validity Theory: Measurement, Causation, and Meaning. New York: Routledge.Google Scholar

A useful summary of the myriad tests, the results of which are used by Schmidt and colleagues: Bertua, C., Anderson, N., and Salgado, J. F. (2005). The predictive validity of cognitive ability tests: a UK meta-analysis. Journal of Occupational and Organizational Psychology, 78: 387–409.CrossRefGoogle Scholar

On the ‘Flynn effect’: Flynn, J. R. (2013). Are We Getting Smarter? Rising IQ in the Twenty-First Century. Cambridge: Cambridge University Press.Google Scholar

On prior experience and complex problem solving in simulated real-world contexts: Süß, H.-M. and Kretzschmar, A. (2018). Impact of cognitive abilities and prior knowledge on complex problem solving performance: empirical results and a plea for ecologically valid microworlds. Frontiers in Psychology, 9: 626. DOI: 10.3389/fpsyg.2018.00626.Google Scholar

A fuller account of what IQ tests (really) test, including non-cognitive factors: Richardson, K. and Norgate, S. H. (2014). Does IQ measure ability for complex cognition? Theory & Psychology, 24: 795–812. See also Lee, J. and Stankov, L. (2017). Noncognitive Psychological Processes and Academic Achievement. London: Routledge.CrossRefGoogle Scholar

A collection of ‘many different perspectives’ is presented in Sternberg, R. J. (2018). The Nature of Human Intelligence. Cambridge: Cambridge University Press. It includes a chapter by Howard Gardner, but broadly illustrates the continuing dominance of the IQ framework. Sternberg’s website is www.robertjsternberg.com.Google Scholar

Descriptions and critiques of Fisher’s genetic model: Barton, N., Hermisson, J., and Nordborg, M. (2019). Population genetics: why structure matters. eLife, 8: e45380. DOI: 10.7554/eLife.45380; Nelson, R. M., Pettersson, M. E., and Carlborg, O. (2013). A century after Fisher: time for a new paradigm in quantitative genetics. Trends in Genetics, 29: 669–676; Portin, P. and Wilkins, A. (2017). The evolving definition of the term ‘Gene’. Genetics, 205: 1353–1364; Fisher, R. A. (1951). Comment. British Agricultural Bulletin, 4: 217–218.CrossRefGoogle ScholarPubMed

Earlier critique of twin studies and their wider social and scientific implications: Kamin, L. J., Rose, S., and Lewontin, R. C. (1984). Not in Our Genes: Biology, Ideology and Human Nature. New York: Pantheon Books.Google Scholar

Links to Jay Joseph’s more recent critiques: www.madinamerica.com/2020/02/exploding-twin-study-myth; https://thegeneillusion.blogspot.com/2020/08/its-time-to-radically-reevaluate-reared_9.html.Google Scholar

Description of online testing in a large twin study: Haworth, C. M. A., Harlaar, N., Kovas, Y., et al. (2007). Internet cognitive testing of large samples needed in genetic research. Twin Research and Human Genetics, 10: 554–563.Google Scholar

Average IQ is higher in adopted children: Kendler, K., Turkheimer, E., Ohlsson, H., et al. (2015). Family environment and the malleability of cognitive ability: a Swedish national home-reared and adopted-away cosibling control study. Proceedings of the National Academy of Sciences, 112(15): 4612–4617.Google Scholar

On GWAS/PGS for education/intelligence: Lee, J. J., Wedow, R., Okbay, A., et al. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics, 50: 1112–1121.CrossRefGoogle ScholarPubMed

National Institute of Health website on SNPs: https://ghr.nlm.nih.gov/primer/genomicresearch/snp. On the role of interactions: Morgante, F., Huang, W., Maltecca, C., and Mackay, T. F. C. (2018). Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals. Heredity, 120: 500–514.Google Scholar

For problems with GWAS/polygenic scores: Richardson, K. (2020). Polygenic scores are an even bigger social hazard. Progress in Biophysics and Molecular Biology, 153: 13–16; Mostafavi, H. et al. (2020). Variable prediction accuracy of polygenic scores within an ancestry group. eLife, 9: e48376. DOI: 10.7554/eLife.48376.Google Scholar

The study finding association between the polygenic score of a weed and a country’s GDP: Kern, A. (2020). Creating a PGS for GDP using Arabidopsis data: https://github.com/andrewkern/gdp_pgs/blob/master/araThal.ipynb.Google Scholar

For life origins: Steel, M., Hordijk, W., and Xavier, J. C. (2019). Autocatalytic networks in biology: structural theory and algorithms. Journal of the Royal Society Interface, 16(151): 20180808. DOI: 10.1098/rsif.2018.0808. Goldford, J. E. and Segrè, D. (2018). Modern views of ancient metabolic networks. Current Opinion in Systems Biology, 8: 117–124.Google Scholar

Bruce Damer’s blog post: Niche Construction, 8 May 2019, https://extendedevolutionarysynthesis.com/the-hot-spring-hypothesis-for-the-origin-of-life-and-the-extended-evolutionary-synthesis.Google Scholar

On RNA as original catalysts: Shen, L. and Ji, H.-F. (2011). Small cofactors may assist protein emergence from RNA world: clues from RNA–protein complexes. PLoS One, 6(7): e22494. DOI: 10.1371/journal.pone.0022494. A popular article by Zimmer, C. (2014). A tiny emissary from the ancient past, New York Times, 25 September, relates that role to today’s viruses and ‘viroids’ (basically RNA viruses without their protein jackets). McGregor, S., Vasas, V., Husbands, P., and Fernando, C. (2012). Evolution of associative learning in chemical networks. PLoS Computational Biology, 8: e1002739. DOI: 10.1371/journal.pcbi.1002739.Google Scholar

On the subordinate role of natural selection in natural conditions: Pujol, B., Blanchet, S., Charmantier, A., et al. (2019). The missing response to selection in the wild. Trends in Ecology and Evolution, 33: 337–346.CrossRefGoogle Scholar

On survival in changeable environments: Richardson, K. (2020). In the light of the environment: Evolution through biogrammars not programmers. Biological Theory, 15: 212–222.Google Scholar

On the subordinate role of the genes: Noble, D. (2016). Dancing to the Tune of Life. Cambridge: Cambridge University Press; Baverstock, K. (2021). The gene: an appraisal. Progress in Biophysics and Molecular Biology. DOI: 10.1016/j.pbiomolbio.2021.04.005.Google Scholar

Discussions of cognitive biology: Baluška, F. and Levin, M. (2016). On having no head: cognition throughout biological systems. Frontiers in Psychology, 7: 902. DOI: 10.3389/fpsyg.2016.00902. On similar lines: Levin, M. and Dennet, D. C. (2020). Cognition all the way down. Aeon: https://aeon.co/essays/how-to-understand-cells-tissues-and-organisms-as-agents-with-agendas (this has been criticized for allusions to human-like agency and purpose).CrossRefGoogle ScholarPubMed

A more extended discussion on the nature of the gene in relation to development and function: Kampourakis, K. (2022). Understanding Genes. Cambridge: Cambridge University Press.Google Scholar

On mismatch between gene products and cell outcomes: Piran, M., Karbalace, R., Piran, M., et al. (2019). Do signaling networks and whole-transcriptome gene expression profiles orchestrate the same symphony? bioRxiv preprint: http://dx.doi.org/10.1101/643866; Yang, C. Farias, F. G., Ibanez, L., et al. (2020). Genomic and multi-tissue proteomic integration for understanding the biology of disease and other complex traits. medRxiv preprint: https://doi.org/10.1101/2020.06.25.20140277.Google Scholar

Bizzarri, M., Brash, D. E., Briscoe, J., et al. (2019). A call for a better understanding of causation in cell biology Nature Reviews Molecular Cell Biology, 20(5): 261–262.Google Scholar

Evolution/adaptation in changing environments: Richardson, K. (2020). In the light of the environment: Evolution through biogrammars not programmers. Biological Theory, 15: 212–222.CrossRefGoogle Scholar

On the ‘complexity’ problem: Duclos, K. K., Hendrikse, J. L., and Jamniczky, H. A. (2019) Investigating the evolution and development of biological complexity under the framework of epigenetics. Evolution and Development. DOI: 10.1111/ede.12301.Google Scholar

On slime mould intelligence: Lee, J., and Zhang, L. (2015). The hierarchy quorum sensing network in Pseudomonas aeruginosa. Protein & Cell, 6(1): 26–41. Vallverdú, J., Castro, O., Mayne, R., et al. (2018). Slime mould: the fundamental mechanisms of biological cognition. Biosystems, 165: 57–70. And an entertaining article by Levy, M. G. (2020). A slime mold changes its mind: an interview with slime mold scientist Audrey Dussutour. Massive Science: https://massivesci.com/articles/slime-mold-ants-audrey-dussutour-breakthrough/?s=09. Cavalier-Smith, T. (2017). Origin of animal multicellularity: precursors, causes, consequences: the choanoflagellate/sponge transition, neurogenesis and the Cambrian explosion. Philosophical Transactions of the Royal Society B, 372: 20150476. Sogabe, S. Hatleberg, W. L., Kocot, K. M., et al. (2019). Pluripotency and the origin of animal multicellularity. Nature, 570: 519–525.CrossRefGoogle ScholarPubMed

On anticipatory processes in physiology: Woods, S. C. and Ramsay, D. S. (2007). Homeostasis: beyond Curt Richter. Appetite, 49: 388–398. Ivanov, P. C. and Bartsch, R. P. (2014). Network physiology: mapping interactions between networks of physiologic networks. In D’Agostino, G. and Scala, A. (eds), Networks of Networks: The Last Frontier of Complexity. New York: Springer. Blanchard, D. C., McKittrick, C. R., Blanchard, R. D., and Hardy, M. P. (2002). Effects of social stress on hormones, brain and behaviour. Part I. In Pfaff, D. W., Arnold, A. P., Farbach, S. E., et al. (eds), Hormones, Brain and Behaviour. New York: Elsevier.Google Scholar

On mechanical (and better) theories of behaviour: Gomez-Marin, A. and Ghazanfar, A. A. (2019). The life of behavior. Neuron, 104. DOI: 10.1016/j.neuron.2019.09.017Google Scholar

On functional aspects of the nervous system of a roundworm: Pan, R. K., Chatterjee, N., and Sinha, S. (2010). Mesoscopic organization reveals the constraints governing Caenorhabditis elegans nervous system. PLoS One, 5(2): e9240. DOI: 10.1371/journal.pone.0009240.CrossRefGoogle ScholarPubMed

On primitive brains: Pagán, O. R. (2019). The brain: a concept in flux. Philosophical Transactions of the Royal Society B. DOI: 10.1098/rstb.2018.0383.CrossRefGoogle Scholar

How cells differentiate: Stathopoulos, A. and Iber, D. (2013). Studies of morphogens: keep calm and carry on. Development, 140: 4119–4124. Small, S. and Briscoe, J. (eds) (2020). Gradients and Tissue Patterning. London: Elsevier.Google Scholar

For feed-forward/feedback loops in stem cell differentiation: Pardo-Saganta, A., Tata, P. R., Law, B. M., et al. (2015). Parent stem cells can serve as niches for their daughter cells. Nature, 523: 597–601. Waddington, C. H. (1968–72). Towards a Theoretical Biology (in 4 volumes). Edinburgh: Edinburgh University Press.Google Scholar

Molecular biology of canalisation: Balaskas, N., Ribeiro, A., Panovska, J., et al. (2012). Gene regulatory logic for reading the sonic hedgehog signaling gradient in the vertebrate neural tube. Cell, 148: 273–284. Mringa Sur’s website: www.surlab.org.Google Scholar

A comprehensive review of developmental plasticity: Kelly, S. A., Panhuis, T. M., and Stoehr, A. M. (2012). Phenotypic plasticity: molecular mechanisms and adaptive significance. Comprehensive Physiology, 2: 1417–1439.CrossRefGoogle ScholarPubMed

On epigenetics of development, with special reference to brain, stress, and nutrition: Nugent, B. M. and McCarthy, M. M. (2015). Epigenetic influences on the developing brain: effects of hormones and nutrition. Advances in Genomics and Genetics, 5: 215–225. Silver, D. L., Rakic, P., Grove E. A., et al. (2019). Evolution and ontogenetic development of cortical structures. In Singer, W., Sejnowski, T. J., and Rakic, P. (eds), The Neocortex. Cambridge, MA: MIT Press.Google Scholar

A lively review of (life-long) brain plasticity: Engleman, D. (2015). The Brain. Edinburgh: Canongate Books. See also Lövdén, M., Wenger, E., and Mårtensson, J. (2013). Structural brain plasticity in adult learning and development. Neuroscience and Biobehavioral Reviews, 37: 2296–2310.Google Scholar

On the distinction between instincts and intelligence: Bateson, P. (2017). Behaviour, Development and Evolution. London: Open Book Publishers. Blumberg, M. S. (2017). Development evolving: the origins and meanings of instinct. WIREs Cognitive Science, 8: e1371. DOI: 10.1002/wcs.1371.Google Scholar

On causes and difference-makers: DiFrisco, J. and Jaeger, J. (2020). Genetic causation in complex regulatory systems: an integrative dynamic perspective. BioEssays, 42: 1900226. See also Kampourakis, K. (2019). Genetics makes more sense in the light of development. In G. Fusco (ed.), Perspectives on Evolutionary and Developmental Biology. Padova: Padova University Press.CrossRefGoogle ScholarPubMed

A modern evolutionary-developmental perspective is provided by Wallace Arthur in Evo-Devo in this series. See also Lickliter, R. (2017). Developmental evolution. WIREs Cognitive Science, 8(1–2). DOI: 10.1002/wcs.1422.Google Scholar

The quotations from Kevin Mitchell are from his blog, Wiring the Brain (4 January 2020), a lively centre of discussion on the latest research. Global Brain Workshop 2016 Attendees (2016). Global challenges for the brain sciences. 2016 Conference Abstract. F1000Research, 5: 2873. Pagán, O.R. (2019). The brain: a concept in flux. Philosophical Transactions of the Royal Society B. DOI: 10.1098/rstb.2018.0383 Cobb, M. (2018). The Idea of the Brain. London: Profile Books.Google Scholar

On feed-forward/feedback processing in the brain: Bányai, M., Lazar, A., Klein, L., et al. (2019). Stimulus complexity shapes response correlations in primary visual cortex. Proceedings of the National Academy of Sciences, 116(7): 201816766. Bao, S. (2015). Perceptual learning in the developing auditory cortex. European Journal of Neuroscience, 41: 718–724. Schrader, S., Gewaltig, M-O., Körner, U., and Körner, E. (2009). Cortext: a columnar model of bottom-up and top-down processing in the neocortex. Neural Networks, 22: 1037–1200 (a special issue devoted to cortical columns).Google Scholar

On dynamic systems in the brain: Brakespear, M. (2017). Dynamic models of large-scale brain activity. Nature Neuroscience, 20: 340–352.Google Scholar

On olfaction: Barwich, A.-S. (2019). A critique of olfactory objects. Frontiers in Psychology, 10: 1337. DOI: 10.3389/fpsyg.2019.01337. Freeman, W. J. (1999). How Brains Make Up Their Minds. London: Weidenfeld and Nicolson.Google Scholar

On audition: Bao, S. (2015). Perceptual learning in the developing auditory cortex. European Journal of Neuroscience, 41: 718–724.Google Scholar

On experience-dependence in brain networks: Lövdén, M., Wenger, E., Mårtensson, J., et al. (2013). Structural brain plasticity in adult learning and development. Neuroscience and Biobehavioral Reviews, 37: 2296–2310.Google Scholar

On emotion and intelligence: Okon-Singer, H. Hendler, T., Pessoa, L., and Shackman, A. J. (2015). The neurobiology of emotion–cognition interactions: fundamental questions and strategies for future research. Frontiers in Human Neuroscience, 9: 58. DOI: 10.3389/fnhum.2015.00058.Google Scholar

On efforts to relate intelligence to size and other aspects of brain: Allen, J. S. (2009). The Lives of the Brain. Cambridge, MA: The Belknap Press.Google Scholar

On the effects of extreme deprivation on physical aspects of the brain: Mackes, N. K., Golm, D., Sarkar, S., et al. (2020). Early childhood deprivation is associated with alterations in adult brain structure despite subsequent environmental enrichment. Proceedings of the National Academy of Sciences USA, 117: 641–649. Nugent, B. M. and McCarthy, M. M. (2015). Epigenetic influences on the developing brain: effects of hormones and nutrition. Advances in Genomics and Genetics, 5: 215–225.Google Scholar

On the unreliability of MRI scans: Botvinik-Nezer, R. Holzmeister, F., Camerer, C. F., et al. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582: 84–88. Weinberger, D. R. and Radulescu, E. (2020). Structural magnetic resonance imaging all over again. JAMA Psychiatry. DOI: 10.1001/jamapsychiatry.2020.1941.Google Scholar

On the notion of fixed wring: Salehi, M., Greene, A. S., Karbasi, A., et al. (2020). There is no single functional atlas even for a single individual: functional parcel definitions change with task. NeuroImage 208: 116366.Google Scholar

On the problems of a competitive-selectionist view of intelligence: Smith, S. E. (2020). Is evolutionary psychology possible? Biological Theory, 15: 39–49.Google Scholar

For social hunting and brain size: Drea, C. M. and Carter, A. N. (2009). Cooperative problem solving in a social carnivore. Animal Behaviour, 78: 967–977. Holekamp, K. E. and Benson-Amram, S. (2017). The evolution of intelligence in mammalian carnivores. Interface Focus. DOI: 10.1098/rsfs.2016.0108.Google Scholar

On the ‘social brain’ idea: Dunbar, R., Gamble, C., and Gowlett, J. (2017). Thinking Big: How the Evolution of Social Life Shaped the Human Mind. New York: Thames and Hudson.Google Scholar

Considering brain size in relation to wider ecological demands in primates: Charvet, C. J. and Finlay, B. L. (2012). Embracing covariation in brain evolution: large brains, extended development, and flexible primate social systems. In Homan, M. A. and Falk, D. (eds), Progress in Brain Research. Amsterdam: Elsevier.Google Scholar

On cooperative hunting in chimpanzees: Boesch, C., Boesch, H., and Vigilant, L. (2006). Cooperative hunting in chimpanzees: kinship or mutualism? In Kappeler, P.M. and van Schaik, C. P. (eds), Cooperation in Primates and Humans. Berlin: Springer.Google Scholar

For the conventional primate-centred view of culture (or ‘cultural primatology’): Humle, T. and Newton-Fisher, N. E. (2013). Culture in non-human primates: definitions and evidence. In Ellen, R. F., Lycett, S. J. and Johns, S. E. (eds), Understanding Cultural Transmission in Anthropology: A Critical Synthesis. New York: Berghahn Books.Google Scholar

For an outline of human evolution: Stringer, C. and Galway-Witham, J. (2017). Palaeoanthropology: on the origin of our species. Nature, 546: 212–214; Antón, S. C., Potts, R., and Aiello, L. C. (2014). Evolution of early Homo: an integrated biological perspective. Science, 345. DOI: 10.1126/science.12368280. Gabora, L. and Russon, A. (2011). The evolution of human intelligence. In Sternberg, R. and Kaufman, S. (eds), The Cambridge Handbook of Intelligence. Cambridge: Cambridge University Press.Google Scholar

On wide resource networks of stone-age humans: Tollefson, J. (2018). Advances in human behaviour came surprisingly early in Stone Age. Nature, 555: 424–425.Google Scholar

For another view on the importance of cooperation: Corning, P. (2018). Synergistic Selection: How Cooperation Has Shaped Evolution and the Rise of Humankind. Singapore: World Scientific.Google Scholar

On the variety of approaches to ‘collective intelligence’: Nguyen, N. T., Kowalczyk, R., Mercik, J., and Motylska-Kuźma, A. (eds) (2020). Transactions on Computational Collective Intelligence XXXV. New York: Springer. Woolley, A. W., Aggarwal, I., and Malone, T. W. (2015). Collective intelligence and group performance. Current Directions in Psychological Science, 24(6): 420–424. See also papers from the MIT Center for Collective Intelligence.Google Scholar

For the theory of cultural tools: Bruner, J. S. (1985). Vygotsky: a historical and conceptual perspective. In Wertsch, J. V. (ed.), Culture, Communication and Cognition: Vygotskian Perspectives. Cambridge: Cambridge University Press. Vygotsky, L. S. (1988). The genesis of higher mental functions. In Richardson, K. and Sheldon, S. (eds), Cognitive Development to Adolescence. Hove: Erlbaum.Google Scholar

Intersubjectivity in development: Beebe, B. and Bahrick, L. E. (2016). A systems view of mother–infant face-to-face communication. Developmental Psychology, 52: 556–571.Google Scholar

On grounded (context-bound) reasoning: Littleton, K. and Mercer, N. (2018). Interthinking: Putting Talk to Work. London: Routledge. Bonnardel, N., Wojtczuk, A., Gilles, P.-Y., and Mazon, S. (2018). The creative process in design. In Lubart, T. (ed.), The Creative Process. London: Palgrave. See also various works from the Centre for Real World Learning, especially Thinking Like an Engineer in conjunction with the Royal Academy of Engineering, at: www.winchester.ac.uk/realworldlearning. Shteynberg, G., Hirsch, J. B., Bentley, R. A., and Garthoff, J., et al. (2020). Shared worlds and shared minds: a theory of collective learning and a psychology of common knowledge. Psychological Review. DOI: 10.1037/rev0000200.Google Scholar

For recent relational/constructivist ideas in language theory: Jackendoff, R. and Audring, J. (2020). Relational morphology: a cousin of construction grammar. Frontiers in Psychology, 11: 2241. DOI: 10.3389/fpsyg.2020.02241.Google Scholar

For assumptions underlying cognitive theories: Richardson, K. (2020). Models of Cognitive Development. London: Routledge.Google Scholar

For papers on hunter-gatherers: Panter-Brick, C., Layton, R. H. and Rowley-Conwy, P. (eds) (2001). Hunter-Gatherers: An Interdisciplinary Perspectives. Cambridge: Cambridge University Press.Google Scholar

On the origins of social class structures: Marrison, R. (2020). Ancient Mesopotamia social classes: www.historyten.com/mesopotamia/ancient-mesopotamia-social-classes.Google Scholar

For concepts of entitlement: Edmiston, D. (2017). How the other half live: poor and rich citizenship in austere welfare regimes. Social Policy & Society, 16: 315–325.Google Scholar

Discussion of effects of class structure on self-concept mediating school preparedness (including results from China): Li, S., Xu, Q., and Xia, R. (2020). Relationship between SES and academic achievement. Frontiers in Psychology. DOI: 10.3389/fpsyg.2019.02513Google Scholar

On health and well-being related to social class: Jackson, B., Richman, L. S., LaBelle, O., et al. (2015). Experimental evidence that low social status is most toxic to well-being when internalized. Self and Identity, 14:2, 157–172. See also Loi. M., Del Savio, L., and Stupka, E. (2013). Social epigenetics and equality of opportunity. Public Health Ethics, 6: 142–153. For a succinct summary of background ‘factors’ associated with educational outcomes, see the Equality Trust: www.equalitytrust.org.uk.Google Scholar

For critical views of the environment: Mayes, L. C. and Lewis, M. (2012). The Cambridge Handbook of Environment in Human Development. Cambridge: Cambridge University Press.Google Scholar

For systemic consequences of extreme environments experienced during development: Nugent, B. and McCarthy, M. M. (2015). Epigenetic influences on the developing brain: effects of hormones and nutrition. Advances in Genomics and Genetics, 5: 215–225. See also the study by Mackes, N. K., Golm, D., Sarkar, S., et al. (2020). Early childhood deprivation is associated with alterations in adult brain structure despite subsequent environmental enrichment. Proceedings of the National Academy of Sciences USA, 117: 641–649.Google Scholar

For a critical review of the concept of giftedness: Freeman, J. (2006), Giftedness in the long term. Journal for the Education of the Gifted, 29: 384–403. For a wider review: Myers, T., Carey, E., and Szűcs, D. (2017). Cognitive and neural correlates of mathematical giftedness in adults and children: a review. Frontiers in Psychology, 8: 1646. DOI: 10.3389/fpsyg.2017.01646. For a different view: Kaufman, S. B. (2017). Ungifted: Intelligence Redefined. New York: Basic Books.Google Scholar

On giftedness in Einstein: Janssen, M. and Renn, J. (2015). History: Einstein was no lone genius. Nature, 527: 298–300.Google Scholar

Scientists on race and genetics: Yudell, M., Roberts, D., DeSalle, R., and Tishkoff, S. (2016). Taking race out of human genetics. Science, 351(6273): 564–565. Panofski, A., Dasgupta, K., and Iturriaga, N. (2020). How White nationalists mobilize genetics: from genetic ancestry and human biodiversity to counterscience and metapolitics. American Journal of Physical Anthropology. DOI: 10.1002/ajpa.24150.Google Scholar

Predicting educational performance: Anders, J., Dilnot, C., Macmillan, L., and Wyness, G. (2020). Grade expectations: how well can we predict future grades based on past performance? Centre for Education Policy and Equalising Opportunities, UCL Institute of Education. Richardson, M., Abraham, C., and Bond, R. (2012). Psychological correlates of university students’ academic performance: a systematic review and meta-analysis. Psychological Bulletin, 138: 353–387.Google Scholar

Predictability of medical school performance: McManus, I., Woolf, K., Dacre, J., et al. (2013). The academic backbone: longitudinal continuities in educational achievement from secondary school and medical school to MRCP(UK) and the specialist register in UK medical students and doctors. BMC Medicine, 11: 242. DOI: 10.1186/1741-7015-11-242. MacKenzie, R. K., Cleland, J. A., Ayansina, D., et al. (2016). Does the UKCAT predict performance on exit from medical school? A national cohort study. BMJ Open, 6(10): e011313.Google Scholar

On use of IQ-type tests to boost predictability: Benton, T. and Lin, Y. (2011). Investigating the Relationship Between A Level Results and Prior Attainment at GCSE. Slough: National Foundation for Educational Research.Google Scholar

Poor predictability of IQ and school attainments for later achievement: Imlach, A.-R., Ward, D. D., Stuart, K. E., et al. (2017). Age is no barrier: predictors of academic success in older learners. Science of Learning, 2: 13. DOI:10.1038/s41539-017-0014-5. For life in the real world: Armstrong, J. S. (2011). Natural learning in higher education. In Encyclopedia of the Sciences of Learning. London: Springer.Google Scholar

On hollow meritocracy in education, see Sandel, M. (2020). The Tyranny of Merit: What’s Become of the Common Good? New York: Allen Lane.Google Scholar

For comments on the Finnish school system: https://pasisahlberg.com.On ‘Vygotskian’ attempts to change school curricula: Erbil, D. E. (2020). A review of Flipped Classroom and cooperative learning method within the context of Vygotsky Theory. Frontiers in Psychology. DOI: 10.3389/fpsyg.2020.01157.Google Scholar

An OECD-sponsored review: Kautz, T., Heckman, J. J., Diris, R., et al. (2015). Fostering and measuring skills: improving cognitive and non-cognitive skills to promote lifetime success. National Bureau of Economic Research Working Paper 20749.Google Scholar

On concepts of environment: Ball, N., Mercado, E., and Orduña, I. (2019). Enriched environments as a potential treatment for developmental disorders: a critical assessment. Frontiers in Psychology. DOI: 10.3389/fpsyg.2019.00466.Google Scholar

On compensatory education: Melhuish, E., Belsky, J., and Barnes, J. (2015). Sure Start and its evaluation in England. In Tremblay, R. E., Boivin, M., and Peters, R. (eds), Encyclopedia on Early Childhood Development: www.child-encyclopedia.com/integrated-early-childhood-development-services/according-experts/sure-start-and-its-evaluation.Google Scholar

Critique of neuroscience proposals for education: Bowers, J. S. (2016). The practical and principled problems with educational neuroscience. Psychological Review. DOI: 10.1037/rev0000025.Google Scholar

On cognitive enhancement programmes: Farah, M. J. (2015). The unknowns of cognitive enhancement. Science, 350: 379–380.Google Scholar

On AI promises: Fjelland, R. (2020). Why general artificial intelligence will not be realized. Humanities and Social Sciences Communications, 7: 10. DOI: 10.1057/s41599-020-0494-4. Beede, E., Baylor, E. E., Hersch, F., et al. (2020). A human-centered evaluation of a deep learning system deployed in clinics for the detection of diabetic retinopathy. In CHI ’20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. DOI: 10.1145/3313831.3376718.Google Scholar