On the Science of Changing Sex

Mars and Venus in Conjunction…

Posted in Brain Sex by Kay Brown on March 30, 2017

Teenage-brainOr, Yes, We CAN Tell Men and Women Apart By Their Personalities

In my last post, we looked at the idea that though the brain is comprised of many areas that individually are only mildly sexually dimorphic the pattern of which adds up to a very sexually dimorphic brain mosaic.  It reminded me of an earlier study in which they found that personality traits were also only mildly sexually dimorphic when examined individually, but the overall personality, the matrix of traits, was also very sexually dimorphic.  That is to say, that men and women, on average, do have different personalities, but no one trait is all that different.

Given that brains and minds are intimately linked, that minds are the function of brains, the fact that both brain mosaic and personality are both individually only mildly sexually dimorphic, but collectively very dimorphic should not surprise us.

The idea that men and women have different personalities has been widely accepted for millenia, but recently has been seriously questioned by feminists and some social scientists and psychologists, most notably Prof. Janet S. Hyde.  But even she, in propounding the “Gender Similarity Hypothesis” did find obviously sexually dimorphic behaviors in humans, as Guidice, et Al remarked,

“Specifically, Hyde found consistently “large” (d between .66 and .99) or “very large” (d≥1.00) sex differences in only some motor behaviors and some aspects of sexuality; “moderate” differences (d between .35 and .65) in aggression”

“…some aspects of sexuality…” Yeah!  Duh!  As in sexual orientation, the single largest sexually dimorphic difference between men and women, also motor behaviors that are highly correlated with sexual orientation.  Finally, aggression; yes, men are more aggressive than women by nature.  But what of the more subtle areas of personality?

In this study, the authors chose to use a very well established personality inventory, the 16PF which underlie the more well known Big Five factor personality inventory.

First, we need to discuss the matter of looking at individual aspects of personality as single variables then averaging this difference between the sexes as the authors pointed out,

“The problem with this approach is that it fails to provide an accurate estimate of overall sex differences; in fact, average effect sizes grossly underestimate the true extent to which the sexes differ. When two groups differ on more than one variable, many comparatively small differences may add up to a large overall effect; in addition, the pattern of correlations between variables can substantially affect the end result. As a simple illustrative example, consider two fictional towns, Lowtown and Hightown. The distance between the two towns can be measured on three (orthogonal) dimensions: longitude, latitude, and altitude. Hightown is 3,000 feet higher than Lowtown, and they are located 3 miles apart in the north-south direction and 3 miles apart in the east-west direction. What is the overall distance between Hightown and Lowtown? The average of the three measures is 2.2 miles, but it is easy to see that this is the wrong answer. The actual distance is the Euclidean distance, i.e., 4.3 miles – almost twice the “average” value. The same reasoning applies to between-group differences in multidimensional constructs such as personality. When groups differ along many variables at once, the overall between-group difference is not accurately represented by the average of univariate effect sizes; in order to properly aggregate differences across variables while keeping correlation patterns into account, it is necessary to compute a multivariate effect size. The Mahalanobis distance D is the natural metric for such comparisons. Mahalanobis’ D is the multivariate generalization of Cohen’s d, and has the same substantive meaning. Specifically, D represents the standardized difference between two groups along the discriminant axis; for example, D = 1.00 means that the two group centroids are one standard deviation apart on the discriminant axis.”

f1-largeIn the figure here, we can see that we have two very distinct population when looking at two variables at once, but can hardly be differentiated using one at a time.  Using Mahalonobis’ D allows us to see the real difference in personalities of men and women taking into account the global pattern of  multiple personality traits, rather than one at a time.  From this the authors found,

“We found a global effect size D = 2.71, corresponding to an overlap of only 10% between the male and female distributions. Even excluding the factor showing the largest univariate ES, the global effect size was D = 1.71 (24% overlap). These are extremely large differences by psychological standards.  The idea that there are only minor differences between the personality profiles of males and females should be rejected as based on inadequate methodology.”

‘Gee willikers Mr. Wilson’… that 10% overlap sounds awfully familiar – Oh yeah, that’s similar to that found for the global pattern of the sexually dimorphic mosaic of the brain.  And just as I suggested that this might represent the effect of the non-heterosexual population, I again hypothesize that we might see a larger effect size if all known LGBT folk were excluded from the study subjects.  If so, that would further support my hypothesis that humans don’t have sexually dimorphic brains so much as having androphilic vs. gynephilic ones.

Further Reading:

Essay on Sexually Dimorphic Brain Mosaic

Essay on Sexually Dimorphic Motor Behaviors

Reference:

Guidice, et Al, “The Distance Between Mars and Venus: Measuring Global Sex Differences In Personality”
http://dx.doi.org/10.1371/journal.pone.0029265

 


 

Fun Reading:

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