Заключение
Растим бесстрашных дочерей (и сострадательных сыновей)
1. S.-J. Blakemore, Inventing Ourselves: The Secret Life of the Teenage Brain (London, Doubleday, 2018). • 2. L. H. Somerville, ‘The Teenage Brain: Sensitivity to Social Evaluation’, Current Directions in Psychological Science 22:2 (2013), pp. 121–7. • 3. S.-J. Blakemore, ‘The Social Brain in Adolescence’, Nature Reviews Neuroscience 9:4 (2008), p. 267. • 4. B. London, G. Downey, R. Romero-Canyas, A. Rattan and D. Tyson, ‘Gender-Based Rejection Sensitivity and Academic Self-Silencing in Women’, Journal of Personality and Social Psychology 102:5 (2012), p. 961; E. Kross, T. Egner, K. Ochsner, J. Hirsch and G. Downey, ‘Neural Dynamics of Rejection Sensitivity’, Journal of Cognitive Neuroscience 19:6 (2007), pp. 945–56. • 5. Damore, ‘Google’s Ideological Echo Chamber’. • 6. Stoet and Geary, ‘The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education’. • 7. J. Clark Blickenstaff, ‘Women and Science Careers: Leaky Pipeline or Gender Filter?’, Gender and Education 17:4 (2005), pp. 369–86. • 8. A. Tintori and R. Palomba, Turn on the Light on Science: A Research-Based Guide to Break Down Popular Stereotypes about Science and Scientists (London, Ubiquity Press, 2017). • 9. London et al., ‘Gender-Based Rejection Sensitivity’. • 10. J. A. Mangels, C. Good, R. C. Whiteman, B. Maniscalco and C. S. Dweck, ‘Emotion Blocks the Path to Learning under Stereotype Threat’, Social Cognitive and Affective Neuroscience 7:2 (2011), pp. 230–41. • 11. E. A. Maloney and S. L. Beilock, ‘Math Anxiety: Who Has It, Why It Develops, and How to Guard against It’, Trends in Cognitive Sciences 16:8 (2012), pp. 404–6. • 12. K. J. Van Loo and R. J. Rydell, ‘On the Experience of Feeling Powerful: Perceived Power Moderates the Effect of Stereotype Threat on Women’s Math Performance’, Personality and Social Psychology Bulletin 39:3 (2013), pp. 387–400. • 13. T. Harada, D. Bridge and J. Y. Chiao, ‘Dynamic Social Power Modulates Neural Basis of Math Calculation’, Frontiers in Human Neuroscience 6 (2013), p. 350. • 14. I. M. Latu, M. S. Mast, J. Lammers and D. Bombari, ‘Successful Female Leaders Empower Women’s Behavior in Leadership Tasks’, Journal of Experimental Social Psychology 49:3 (2013), pp. 444–8. • 15. J. G. Stout, N. Dasgupta, M. Hunsinger and M. A. McManus, ‘STEMing the Tide: Using Ingroup Experts to Inoculate Women’s Self-Concept in Science, Technology, Engineering, and Mathematics (STEM)’, Journal of Personality and Social Psychology 100:2 (2011), p. 255. • 16. ‘Inspiring girls with People Like Me’, WISE website, https://www.wisecampaign.org.uk/what-we-do/expertise/inspiring-girls-with-people-likeme (accessed 10 November 2018). • 17. C. Ainsworth, ‘Sex Redefined’, Nature 518:7539 (2015), p. 288. • 18. E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris and R. T. Constable, ‘Functional Connectome Fingerprinting: Identifying Individuals Using Patterns of Brain Connectivity’, Nature Neuroscience 18:11 (2015), p. 1664; E. S. Finn, ‘Brain activity is as unique – and identifying – as a fingerprint’, Conversation, 12 October 2015, https://theconversation.com/brainactivity-is-as-unique-and-identifying-as-a-fingerprint-48723 (accessed 10 November 2018). • 19. D. Joel and A. Fausto-Sterling, ‘Beyond Sex Differences: New Approaches for Thinking about Variation in Brain Structure and Function’, Philosophical Transactions of the Royal Society B: Biological Sciences 371:1688 (2016), 20150451; Joel et al., ‘Sex beyond the Genitalia’. • 20. L. Foulkes and S. J. Blakemore, ‘Studying Individual Differences in Human Adolescent Brain Development’, Nature Neuroscience 21:3 (2018), pp. 315–23. • 21. Q. J. Huys, T. V. Maia and M. J. Frank, ‘Computational Psychiatry as a Bridge from Neuroscience to Clinical Applications’, Nature Neuroscience 19:3 (2016), p. 404; O. Moody, ‘Artificial intelligence can see what’s in your mind’s eye’, The Times, 3 January 2018, https://www.thetimes.co.uk/article/artificial-intelligence-can-see-whatsin-your-minds-eye-w6k9pjsh6 (accessed 10 November 2018). • 22. M. M. Mielke, P. Vemuri and W. A. Rocca, ‘Clinical Epidemiology of Alzheimer’s Disease: Assessing Sex and Gender Differences’, Clinical Epidemiology 6 (2014), p. 37; S. L. Klein and K. L. Flanagan, ‘Sex Differences in Immune Responses’, Nature Reviews Immunology 16:10 (2016), p. 626. • 23. L. D. McCullough, G. J. De Vries, V. M. Miller, J. B. Becker, K. Sandberg and M. M. McCarthy, ‘NIH Initiative to Balance Sex of Animals in Preclinical Studies: Generative Questions to Guide Policy, Implementation, and Metrics’, Biology of Sex Differences 5:1 (2014), p. 15. • 24. D. L. Maney, ‘Perils and Pitfalls of Reporting Sex Differences’, Philosophical Transactions of the Royal Society B: Biological Sciences 371:1688 (2016), 20150119. • 25. http://lettoysbetoys.org.uk • 26. R. Nicholson, ‘No More Boys and Girls: Can Kids Go Gender Free review – reasons to start treating children equally’, Guardian, 17 August 2017, https://www.theguardian.com/tv-and-radio/tvandradioblog/2017/aug/17/no-more-boys-and-girls-can-kids-go-genderfree-review-reasons-to-start-treating-children-equally (accessed 10 November 2018); J. Rees, ‘No More Boys and Girls: Can Our Kids Go Gender Free? should be compulsory viewing in schools – review’, Telegraph, 23 August 2017, https://www.telegraph.co.uk/tv/2017/08/23/no-boysgirls-can-kids-go-gender-free-should-compulsory-viewing (accessed 10 November 2018). • 27. S. Quadflieg and C. N. Macrae, ‘Stereotypes and Stereotyping: What’s the Brain Got to Do with It?’, European Review of Social Psychology 22:1 (2011), pp. 215–73. • 28. C. Fine, J. Dupré and D. Joel, ‘Sex-Linked Behavior: Evolution, Stability, and Variability’, Trends in Cognitive Sciences 21:9 (2017), pp. 666–73. • 29. D. Victor, ‘Microsoft created a Twitter bot to learn from users. It quickly became a racist jerk’, New York Times, 24 March 2016, https://www.nytimes.com/2016/03/25/technology/microsoft-created-a-twitter-bot-to-learn-from-users-it-quicklybecame-a-racist-jerk.html (accessed 10 November 2018). • 30. Hunt, ‘Tay, Microsoft’s AI chatbot, gets a crash course in racism from Twitter’.