Delusions of Gender (42 page)

1
(Gray, 2008), pp. 44 and 45, respectively.

2
(Gurian & Annis, 2008), p. 9.

3
(Gurian, 2003), p. 88.

4
(Gurian & Annis, 2008), p. 34.

5
(Gurian & Annis, 2008), p. 59, emphasis in original.

6
(Rogers, Zucca, & Vallortigara, 2004). Thanks to Lesley Rogers for alerting me to this study.

7
(Young & Balaban, 2006), p. 634.

8
http://itre.cis.upenn.edu/~myl/languagelog/archives/003923.html
, accessed on October 5, 2009.

9
The study cited is (Raingruber, 2001).

10
(Brizendine, 2007), p. 162.

11
(Hall, 1978; Hall, 1984; McClure, 2000).

12
(Brizendine, 2007), p. 162.

13
The study cited is (Oberman et al., 2005).

14
(Brizendine, 2007), p. 163.

15
The study cited is (Singer et al., 2004).

16
(Brizendine, 2007), p. 163.

17
The study cited is T. Iidaka, ‘fMRI study of age related differences in the medial temporal lobe responses to emotional faces’, Society for Neuroscience, New Orleans [
sic
, should be San Diego], 2001. The first author confirmed that the research presented at this conference was subsequently published in (Iidaka et al., 2002) and that, as in the published report, gender differences were not mentioned.

18
The study cited is (Zahn-Waxler, Klimes-Dougan, & Slattery, 2000), p. 458, emphasis in original.

19
(Brizendine, 2007), p. 163.

20
The study cited is (Singer et al., 2006).

21
(Brizendine, 2007), pp. 163 and 164. Note that the researchers actually interpret their empathy-related responses to the pain of another as being limited to the affective aspect of the pain response, rather than the sensory aspects of pain.

22
(Brizendine, 2007), p. 158. The citations are, in order discussed in current text: (Orzhekhovskaia, 2005); (Uddin et al., 2005); (Oberman et al., 2005); (Ohnishi et al., 2004); and L. M. Oberman, ‘There may be a difference in male and female mirror neuron functioning’, personal communication, 2005.

23
Lindsay M. Oberman, personal communication (with me), October 21, 2008.

24
(Brizendine, 2007), p. 210.

25
(Brizendine, 2007), pp. 188 and 189.

26
http://itre.cis.upenn.edu/~myl/languagelog/archives/004926.html
, accessed March 3, 2010.

27
Quoted in (Weil, 2008), para. 14.

28
(Sax, 2006), pp. 106 and 107 and p. 106, respectively. The study Sax bases this claim on is described on pp. 29 and 30 of his book
Why Gender Matters
.

29
See (Freese & Amaral, 2009).

30
The study cited is (Killgore, Oki, & Yurgelun-Todd, 2001).

31
Although negative emotions conveyed in faces can be contagious, the children were not asked to try to induce a particular mood, and it was not the purpose of the experimental design to induce negative emotion in the children.

32
Brain activity was measured in two small parts of the brain bilaterally, in the amygdala and a region of the dorsolateral prefrontal cortex. For further critique of Sax’s interpretation of this study, see Mark Liberman’s discussion at
http://itre.cis.upenn.edu/~myl/languagelog/archives/003284.html
.

33
http://itre.cis.upenn.edu/~myl/languagelog/archives/003284.html
, accessed September 2, 2009.

34
Sax cites one other study as support for his claim that in women brain activity associated with negative affect is ‘mostly up in the cerebral cortex’ whereas in men it is ‘stuck down in the amygdala’ (Sax, 2006), p. 29. This study (Schneider et al., 2000), involving thirteen men and thirteen women, found increased activity in the right amygdala in males but not females during induced sadness (but similar left amygdala activity during induced sadness, and similar amygdala activation in both hemispheres during induced happiness). Gender differences in cortical activations during induced sadness and happiness are not discussed. Sax also cites two other studies as evidence that emotions are processed differently in the sexes. Although he does not claim that these studies support the hypothesis that negative emotional experience is more subcortical in males and cortical in females, for the sake of completeness it is worth noting that these studies do not offer support for this idea. The first study (Killgore & Yurgelun-Todd, 2001) did not involve emotional experience but looked at amygdala activity in seven men and six women as they looked at fearful or happy faces (compared with the control condition of looking at a small circle). It did not look at brain activations in cortical regions. Amygdala response while looking at fearful faces was similar in the two sexes. When looking at happy faces, amygdala activation was lateralised to the right in men but not women – a lateralisation difference, rather than a difference in the engagement of the amygdala per se. Second, Sax cites a meta-analysis of functional imaging studies of emotion (Wager et al., 2003) as evidence that emotions are processed differently in the sexes. However, the conclusions of this study are not consistent with the idea that emotional experience is more subcortical in males and more cortical in women. The authors tentatively summarise the gender differences from their analysis as follows: ‘Men tend to activate posterior sensory and association cortex, left inferior frontal cortex, and dorsal striatum more reliably than women, whereas women tend to activate medial frontal cortex, thalamus, and cerebellum more reliably’ (p. 528). Translation: Men [cortical, cortical, cortical, subcortical] versus Women [cortical, subcortical, subcortical].

35
(Bachelard & Power, 2008), para. 46.

36
(Sax, 2006), p. 102 (boys) and p. 104 (girls). The term ‘neurofallacy’ coined by (Racine et al., 2005). For details of hippocampus-cortex connections, take your pick from the articles in the 2000 Special Issue of the journal
Hippocampus
entitled ‘The nature of hippocampal-cortical interaction: Theoretical and experimental perspectives’.

37
See (Sax, 2006), pp. 100–101. Perhaps the most important reason that implications for maths education cannot be drawn from the cited neuroimaging study is that it did not involve maths, or even numbers. Rather, the task involved navigating out of a complex three-dimensional virtual maze. The
control condition involved looking at a frozen shot of the maze and making key presses in response to flickering rectangles. We can immediately see that this study will not tell us anything about the parts of the brain involved in mathematical processing. Even if the debate concerned whether single-sex classrooms are necessary for lessons in virtual maze navigation, this study would not help us much. More male activity was seen in the left hippocampus while women showed greater activation in right prefrontal and parietal areas, but this is in the context of ‘great overlap’ between the sexes in which regions were activated (Grön et al., 2000), p. 405. It’s impossible to make useful inferences from these differences. What do we make of greater male activation of the left hippocampus given that the right was activated equally in the sexes? What is the significance of greater female activation of the superior parietal lobule on one side of the brain but not the other? It does not make sense to say that only females use the cerebral cortex and only males use the hippocampus while performing spatial navigation (and even less sense to make this claim for maths)! Moreover, we don’t know whether more activation means ‘better’. It could mean ‘less efficient’. Were the differences due to performance differences rather than sex per se? (The men were significantly faster at getting out of the maze.) What cognitive role are these regions playing in the performance of the task? We have no idea – which makes developing educational strategies on the basis of these findings impossible. Discussing a similar claim about sex differences in maths processing made by a commentator on the BBC’s ‘Today’ programme, the blogger known as Neurosceptic provides a useful explanation of some of the confusion behind such claims (see
http://neuroskeptic.blogspot. com/2008/11/educational-neuro-nonsense-or-return-of.html
, accessed on September 10, 2009).

38
http://itre.cis.upenn.edu/~myl/languagelog/archives/004618.html
, accessed December 9, 2009.

39
Quoted in (Garner, 2008), para. 7.

40
(Bruer, 1997), p. 4.

41
(Clarke, 1873).

42
(Lewontin, 2000), p. 208.

43
Quoted in (Garner, 2008), para. 3.

44
http://neuroskeptic.blogspot.com/2008/11/educational-neuro-nonsense-or-return-of.html
, accessed September 2, 2009.

1
(Sax, 2005), para. 8. In fairness to Sax, he is following the lead of the authors of the research paper on which this claim is made. They found different patterns of EEG waves (synchrony versus asynchrony) in children at rest, related these EEG patterns to complex psychological processes like language, mathematics and social cognition (which, recall, the children were not engaged in), and then suggested that their results ‘have implications for gender differences in “readiness-to-learn”’ – even though they report no gender differences in any of the cognitive abilities their EEG data were supposedly tapping (Hanlon, Thatcher, & Cline, 1999), p. 503.

2
From Sax’s Web site:
http://www.whygendermatters.com
, accessed on December 9, 2009. More recently, the NASSPE Web site (see
http://www.singlesexschools.org/research-brain.htm
) has drawn on a structural imaging study (Lenroot et al., 2007) to further bolster this argument. This study found sex differences in the trajectory of volume changes in the brain across time, although many of these differences did not survive correction for total brain volume, which is greater in boys. In any case, the psychological implications of these findings are unknown. As the researchers put it: ‘Differences in brain size between males and females should not be interpreted as implying any sort of functional advantage or disadvantage.’ (p. 1072).

3
Quoted in (Dakss, 2005), para. 29.

4
(Hyde et al., 2008).

5
(Kemper, 1990), p. 13.

6
(Racine, Bar-Ilan, & Illes, 2005), p. 160.

7
(Gurian & Stevens, 2005), p. 42.

8
http://itre.cis.upenn.edu/~myl/languagelog/archives/003246.html
, accessed on October 5, 2009.

9
http://www.jsmf.org/neuromill/chaff.htm#bn64
, accessed on October 5, 2009.

10
(Weisberg et al., 2008). A similar favouring of findings attained from neuroscientific methods was found by (Morton et al., 2006).

11
(McCabe & Castel, 2008).

12
(Weisberg, 2008), p. 54.

13
(Gurian, Henley, & Trueman, 2001), p. 45 and see p. 53.

14
(Brescoll & LaFrance, 2004; Coleman & Hong, 2008; Dar-Nimrod & Heine, 2006; Thoman et al., 2008).

15
(Dar-Nimrod & Heine, 2006), p. 435.

16
(Kimura, 1999), p. 8.

17
See also arguments made by Bleier with regard to scientists’ responsibility for
the presentation of data in their writing (Bleier, 1986), and also (Bishop & Wahlsten, 1997).

18
(Weisberg, 2008), p. 55.

19
Hats off to the bloggers who regularly discuss these issues, in particular the tireless Mark Liberman.

1
For details, and contrast with maturational viewpoint, see (Westermann et al., 2007), in particular figure 4, p. 80. Also (Lickliter & Honeycutt, 2003; Mareschal et al., 2007).

2
(Wexler, 2006), pp. 3 and 4.

3
(Bleier, 1984), p. 52, footnote removed.

4
(Grossi, 2008).

5
(Shields, 1982), pp. 778 and 779. See also (Shields, 1975).

6
As Steven Pinker put it (Edge, 2005b).

7
For a history of the Greater Male Variability hypothesis see (Shields, 1982).

8
E. L. Thorndike,
Educational Psychology
(1910), p. 35. Quoted in (Hollingworth, 1914), p. 510.

9
(Summers, 2005), para. 4.

10
Quoted in (Edge, 2005b).

11
(Pinker, 2008), p. 13.

12
(Hollingworth, 1914). Wendy Johnson, Andrew Carothers, and Ian Deary published a reanalysis of these data in 2008. They concluded that males were
especially
variable at lower levels of IQ. They also noted that, with a ratio of about 2 boys to 1 girl at the very highest levels of intelligence, this did not go very far in explaining the much steeper ratios for high-level academic physical science, maths, and engineering positions (Johnson, Carothers, & Deary, 2008), p. 520.

13
(Grossi, 2008), p. 98.

14
(Feingold, 1994).

15
(Hyde et al., 2008).

16
(Guiso et al., 2008).

17
(Penner 2008; Machin & Pekkarinen 2008). These latter authors stress the strong pattern of greater male variability, but the boy/girl ratio (shown in parentheses) at the top 5 percent of maths ability was more-or-less equal in Indonesia (0.91), Thailand (0.92), Iceland (1.04) and the UK (1.08). Penner found greater female variability in the Netherlands, Germany and Lithuania. For useful discussion of these data, see (Hyde & Mertz, 2009).

18
(Andreescu et al., 2008), p. 1248.

19
See (Andreescu et al., 2008), p. 1248.

20
(Andreescu et al., 2008), p. 1251.

21
(Andreescu et al., 2008), p. 1252.

22
(Andreescu et al., 2008), pp. 1253 and 1254. See table 7, p. 1253.

23
(Summers, 2005), para. 4.

24
(Pinker, 2005), para. 3.

25
(Dweck, 2007), p. 49.

26
See (Blackwell, Trzesniewski, & Dweck, 2007; Dweck, 2007; Good, Aronson, & Inzlicht, 2003).

27
This has been surprisingly little discussed in the academic literature, but see (Chalfin, Murphy, & Karkazis, 2008; Fine, 2008).

28
(Morton et al., 2009), pp. 661 and 656 (reference removed), respectively.

29
This is thanks, in no small part, to books aimed at a general audience that have critiqued popular myths of gender. Recent examples of such efforts include (Barnett & Rivers, 2004; Cameron, 2007; Fausto-Sterling, 1985, 2000; Rogers, 1999; Tavris, 1992).

30
This is a point made in a general way by the instigators of the Critical Neuroscience project, which ‘holds that while neuroscience potentially discloses facts about behaviour and its instantiation in the brain, the cultural context of science interacts with these knowledge claims, adds new meaning to them and influences the experience of the people to whom they pertain’ (Choudhury, Nagel, & Slaby, 2009), p. 66, references removed.