Sex and Power: Why Sex/Gender Neuroscience Should Motivate Statistical Reform

  • Cordelia FineEmail author
  • Fiona Fidler
Reference work entry


Towards the end of the last century, statistical reporting in medical research underwent substantial reform, with null hypothesis significance testing replaced with an estimation approach. Interestingly, this reform may have been largely motivated by the social costs of error within medical research, rather than simply scientific error per se. This chapter briefly reviews the benefits of the estimation statistical approach as a means to producing reliable information about nature and then describes how the current statistical method of null hypothesis significance testing specifically contributes to scientific error in sex/gender neuroscience. The potential social harm that can arise from such errors in this area of research is then highlighted. It is suggested that sex/gender neuroscience may therefore provide a valuable model to motivate, on ethical grounds, statistical reform within the psychological sciences.


Gender Stereotype Theoretical Significance Functional Neuroimaging Study Social Harm Null Hypothesis Significance Testing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bastian, B., & Haslam, N. (2006). Psychological essentialism and stereotype endorsement. Journal of Experimental Social Psychology, 42, 228–235.CrossRefGoogle Scholar
  2. Bem, S. (1993). The lenses of gender: Transforming the debate on sexual inequality. New Haven: Yale University Press.Google Scholar
  3. Brescoll, V., & LaFrance, M. (2004). The correlates and consequences of newspaper reports of research on sex differences. Psychological Science, 15(8), 515–520.CrossRefGoogle Scholar
  4. Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., et al. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 365–376.CrossRefGoogle Scholar
  5. Cahill, L. (2006). Why sex matters for neuroscience. Nature Review Neuroscience, 7(6), 477–484.CrossRefGoogle Scholar
  6. Cahill, L. (2010). Sex influences on brain and emotional memory: The burden of proof has shifted. In I. Savic (Ed.), Sex differences in the human brain, their underpinnings and implications (Vol. 186, pp. 29–40). Amsterdam: Elsevier.CrossRefGoogle Scholar
  7. Choudhury, S., Nagel, S., & Slaby, J. (2009). Critical neuroscience: Linking neuroscience and society through critical practice. BioSocieties, 4, 61–77.CrossRefGoogle Scholar
  8. Coleman, J., & Hong, Y.-Y. (2008). Beyond nature and nurture: The influence of lay gender theories on self-stereotyping. Self and Identity, 7(1), 34–53.CrossRefGoogle Scholar
  9. Coulson, M., Healey, M., Fidler, F., & Cumming, G. (2010). Confidence intervals permit, but don’t guarantee, better inference than statistical significance testing. Frontiers in Quantitative Psychology and Measurement, 1.Google Scholar
  10. Cumming, G. (2012). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. New York: Routledge.Google Scholar
  11. Cumming, G., & Fidler, F. (2009). Confidence intervals: Better answers to better questions. Zeitschrift für Psychologie/Journal of Psychology, 217, 15–26.CrossRefGoogle Scholar
  12. Cumming, G., Fidler, F., Leonard, M., Kalinowski, P., Christiansen, A., Kleinig, A., et al. (2007). Statistical reform in psychology: Is anything changing? Psychological Science, 18, 230–232.CrossRefGoogle Scholar
  13. Dambrun, M., Kamiejski, R., Haddadi, N., & Duarte, S. (2009). Why does social dominance orientation decrease with university exposure to the social sciences? The impact of institutional socialization and the mediating role of “geneticism”. European Journal of Social Psychology, 39, 88–100.CrossRefGoogle Scholar
  14. Dar-Nimrod, I., & Heine, S. (2006). Exposure to scientific theories affects women’s math performance. Science, 314, 435.CrossRefGoogle Scholar
  15. Fanelli, D. (2012). Negative results are disappearing from most disciplines and countries. Scientometrics, 90, 891–904.CrossRefGoogle Scholar
  16. Farah, M. J., & Hook, C. J. (2013). The seductive allure of “Seductive Allure”. Perspectives on Psychological Science, 8(1), 88–90.CrossRefGoogle Scholar
  17. Fausto-Sterling, A. (2000). Sexing the body: Gender politics and the construction of sexuality. New York: Basic Books.Google Scholar
  18. Fausto-Sterling, A. (2005). The bare bones of sex: Part 1–sex and gender. Signs: Journal of Women in Culture and Society, 30(2), 1491–1527.CrossRefGoogle Scholar
  19. Fidler, F. (2011). Ethics and statistical reform: Lessons from medicine. In A. T. Panter & S. K. Sterba (Eds.), Handbook of ethics in quantitative methodology. New York: Routledge.Google Scholar
  20. Fidler, F., & Loftus, G. (2009). Why figures with error bars should replace p values: Some conceptual arguments and empirical demonstrations. Zeitschrift für Psychologie/Journal of Psychology, 217, 27–37.CrossRefGoogle Scholar
  21. Fine, C. (2010). Delusions of gender: How our minds, society, and neurosexism create difference. New York: WW Norton.Google Scholar
  22. Fine, C. (2012a). Explaining, or sustaining, the status quo? The potentially self-fulfilling effects of ‘hardwired’ accounts of sex differences. Neuroethics, 5(3), 285–294.CrossRefGoogle Scholar
  23. Fine, C. (2012b). Is there neurosexism in functional neuroimaging investigations of sex differences? Neuroethics, 6(2), 369–409.CrossRefGoogle Scholar
  24. Fine, C. (2013). Neurosexism in functional neuroimaging: From scanner to pseudo-science to psyche. In M. Ryan & N. Branscombe (Eds.), The Sage handbook of gender and psychology. Thousand Oaks, CA: Sage.Google Scholar
  25. Gigerenzer, G. (1998). Surrogates for theory. Theory & Psychology, 8, 195–204.CrossRefGoogle Scholar
  26. Hacking, I. (1995). The looping effects of human kinds. In D. Sperber, D. Premack, & A. Premack (Eds.), Causal cognition: A multidisciplinary approach (pp. 351–383). Oxford: Oxford University Press.Google Scholar
  27. Haller, H., & Krauss, S. (2002). Misinterpretations of significance: A problem students share with their teachers? Methods of Psychological Research, 7, 1–20.Google Scholar
  28. Hoffman, G. (2011). What, if anything, can neuroscience tell us about gender differences? In R. Bluhm, A. Jacobson, & H. Maibom (Eds.), Neurofeminism: Issues at the intersection of feminist theory and cognitive science. Basingstoke: Palgrave Macmillan.Google Scholar
  29. Hunter, J. (1997). Needed: A ban on the significance test. Psychological Science, 8, 3–7.CrossRefGoogle Scholar
  30. Hyde, J. (2005). The gender similarities hypothesis. American Psychologist, 60(6), 581–592.CrossRefGoogle Scholar
  31. Ihnen, S. K. Z., Church, J. A., Petersen, S. E., & Schlaggar, B. L. (2009). Lack of generalizability of sex differences in the fMRI BOLD activity associated with language processing in adults. NeuroImage, 45(3), 1020–1032.CrossRefGoogle Scholar
  32. Joel, D. (2011). Male or female? Brains are intersex. Frontiers in Integrative Neuroscience, 5, 57.CrossRefGoogle Scholar
  33. Joel, D. (2012). Genetic-gonadal-genitals sex (3G-sex) and the misconception of brain and gender, or, why 3G-males and 3G-females have intersex brain and intersex gender. Biology of Sex Differences, 3(1), 27.CrossRefGoogle Scholar
  34. Jordan-Young, R. (2010). Brain storm: The flaws in the science of sex differences. Cambridge, MA: Harvard University Press.Google Scholar
  35. Kaiser, A. (2012). Re-conceptualizing “sex” and “gender” in the human brain. Zeitschrift für Psychologie/Journal of Psychology, 220(2), 130–136.CrossRefGoogle Scholar
  36. Kaiser, A., Haller, S., Schmitz, S., & Nitsch, C. (2009). On sex/gender related similarities and differences in fMRI language research. Brain Research Reviews, 61(2), 49–59.CrossRefGoogle Scholar
  37. Keller, J. (2005). In genes we trust: The biological component of psychological essentialism and its relationship to mechanisms of motivated social cognition. Journal of Personality and Social Psychology, 88(4), 686–702.CrossRefGoogle Scholar
  38. Kitazawa, S., & Kansaku, K. (2005). Sex difference in language lateralization may be task-dependent. Brain, 128(5), E30.CrossRefGoogle Scholar
  39. Kline, R. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. Washington, DC: American Psychological Association.Google Scholar
  40. Lai, J., Fidler, F., & Cumming, G. (2012). Subjective p intervals. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 8(2), 51–62.Google Scholar
  41. Maccoby, E. E., & Jacklin, C. N. (1974). The psychology of sex differences. Stanford: Stanford University Press.Google Scholar
  42. Martin, C., & Parker, S. (1995). Folk theories about sex and race differences. Personality and Social Psychology Bulletin, 21(1), 45–57.CrossRefGoogle Scholar
  43. McCabe, D., & Castel, A. (2008). Seeing is believing: The effect of brain images on judgments of scientific reasoning. Cognition, 107, 343–352.CrossRefGoogle Scholar
  44. McCarthy, M., Arnold, A., Ball, G., Blaustein, J., & De Vries, G. J. (2012). Sex differences in the brain: The not so inconvenient truth. Journal of Neuroscience, 32(7), 2241–2247.CrossRefGoogle Scholar
  45. Meehl, P. (1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology, 46, 806–834.CrossRefGoogle Scholar
  46. Michael, R., Newman, E., Vuorre, M., Cumming, G., & Garry, M. (2013). On the (non)persuasive power of a brain image. Psychonomic Bulletin & Review. doi: 10.3758/s13423-013-0391-6.Google Scholar
  47. Morton, T., Haslam, S., Postmes, T., & Ryan, M. (2006). We value what values us: The appeal of identity-affirming science. Political Psychology, 27(6), 823–838.CrossRefGoogle Scholar
  48. Morton, T., Haslam, S., & Hornsey, M. (2009). Theorizing gender in the face of social change: Is there anything essential about essentialism? Journal of Personality and Social Psychology, 96(3), 653–664.CrossRefGoogle Scholar
  49. Oakes, M. (1986). Statistical inference: A commentary for the social and behavioural sciences. Chichester: Wiley.Google Scholar
  50. Racine, E., Bar-Ilan, O., & Illes, J. (2005). fMRI in the public eye. Nature Reviews Neuroscience, 6(2), 159–164.CrossRefGoogle Scholar
  51. Racine, E., Waldman, S., Rosenberg, J., & Illes, J. (2010). Contemporary neuroscience in the media. Social Science & Medicine, 71(4), 725–733.CrossRefGoogle Scholar
  52. Rossi, J. (1990). Statistical power of psychological research: What have we gained in 20 years? Journal of Consulting and Clinical Psychology, 58, 646–656.CrossRefGoogle Scholar
  53. Sedlmeier, P., & Gigerenzer, G. (1989). Do studies of statistical power have an effect on the power of studies? Psychological Bulletin, 105, 309–315.CrossRefGoogle Scholar
  54. Shaywitz, B., Shaywitz, S., Pugh, K., Constable, R., Skudlarski, P., Fulbright, R., et al. (1995). Sex differences in the functional organization of the brain for language. Nature, 373, 607–609.CrossRefGoogle Scholar
  55. Simmons, J., Nelson, L., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366.CrossRefGoogle Scholar
  56. Sommer, I., Aleman, A., Bouma, A., & Kahn, R. (2004). Do women really have more bilateral language representation than men? A meta-analysis of functional imaging studies. Brain, 127, 1845–1852.CrossRefGoogle Scholar
  57. Sommer, I., Aleman, A., & Kahn, R. S. (2005). Size does count: A reply to Kitazawa and Kansaku. Brain, 128, E31.CrossRefGoogle Scholar
  58. Sommer, I., Aleman, A., Somers, M., Boks, M. P., & Kahn, R. S. (2008). Sex differences in handedness, asymmetry of the Planum Temporale and functional language lateralization. Brain Research, 1206, 76–88.CrossRefGoogle Scholar
  59. Thirion, B., Pinel, P., Mériaux, S., Roche, A., Dehaene, S., & Poline, J.-B. (2007). Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses. NeuroImage, 35(1), 105–120.CrossRefGoogle Scholar
  60. Thoman, D., White, P., Yamawaki, N., & Koishi, H. (2008). Variations of gender-math stereotype content affect women’s vulnerability to stereotype threat. Sex Roles, 58, 702–712.CrossRefGoogle Scholar
  61. Wallentin, M. (2009). Putative sex differences in verbal abilities and language cortex: A critical review. Brain and Language, 108(3), 175–183.CrossRefGoogle Scholar
  62. Weisberg, D., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20(3), 470–477.CrossRefGoogle Scholar
  63. Yong, E. (2012). Bad copy. Nature, 485, 298–300.CrossRefGoogle Scholar
  64. Yzerbyt, V., Rocher, S., & Schadron, G. (1997). A subjective essentialist view of group perception. In R. Spears, P. Oakes, N. Ellemers, & S. A. Haslam (Eds.), The social psychology of stereotyping and group life (pp. 20–50). Oxford: Blackwell.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Melbourne School of Psychological Sciences & MelbourneBusiness School & Centre for Ethical Leadership, University of MelbourneCarltonAustralia
  2. 2.Australian Centre of Excellence for Risk Analysis (ACERA), Environmental Science, School of BotanyUniversity of MelbourneCarltonAustralia

Personalised recommendations