This continues my last piece on the “Global Gender Gap Report.”
Better than I can, Dr. David Geary dismantles the World Economic Forum’s Global Gender Gap Index, but his Quillette essay is far more than just a takedown. Geary’s created his own index that, unlike the GGGI, actually compares male-female inequalities in various countries. By treating male inequalities as equalities, the GGGI is not and cannot be an actual index of where men’s and women’s outcomes differ. In what must be called a tour de force of dissimulation, the WEF both admits the fact and lies about it in the same sentence.
The index rewards countries that reach a point where outcomes for women equal those for men, but it neither rewards nor penalizes cases in which women are outperforming men in particular indicators in some countries.
So the Report admits the truth - that there are areas in which women outperform men - but the rest denies that truth as my last piece makes clear. The WEF’s idea of a “reward” is giving a country a ‘1’ rating in one of the four areas – economic and political opportunity, health and education – analyzed. So, by rating as ‘1’ every area in which men’s outcomes are worse than women’s, it in fact does reward anti-male inequalities. Geary draws the right conclusion:
In other words, this is not actually a measure of equality per se, but rather the extent to which women are equal to men overall on several (but not all) dimensions of life that are important in modern contexts.
Then Geary takes on the astonishing decision by the WEF to use a rating system for gender lifespans that is different from the one it uses in every other category. (See my previous piece for a full explanation.) To most of us, that’s just avoidance of the simple fact that, in most cultures, women tend to live longer than men. Rather than admit the reality of male inequality, the GGGI dishonestly pretends that it’s women who suffer despite their greater longevity. To my mind, Geary lets the WEF off too easily.
It is true that males have shorter lifespans than females in species with intense male-on-male competition for status and access to mates, so the assertion that women naturally live longer than men (assuming a relatively benign environment) is correct.
That may be true, but it may not be. After all, without access to modern medical practices, women die from the complications of childbirth at a pretty high rate. Do we actually know that, in pre-modern societies, women lived longer than men on average or that they did far back in pre-history?
More importantly, in modern developed nations, the difference in male and female lifespans varies considerably. Consider the chart in this article regarding various European and Scandinavian countries. It’s clear that male-female lifespan ratios vary not only by country but by year. For example, in Italy in 1885, men and women’s life expectancies were the same, but today, Italian women outlive men by over three years. By contrast, in France in 1885, women outlived men by three years, a gap that expanded to eight years in 1975, remained there until 1995 and then declined to six years today. So how does the WEF come up with the 1.06:1 female-to-male lifespan ratio? What data did it use, and when and where were they collected?
That quibble aside, Geary gets down to business:
The first [problem] is that although the GGGI purports to only measure outcomes and not the inputs that create those outcomes, here they are asserting that a biological input results in a female advantage in lifespan and this justifies the 1.06 benchmark.
The WEF’s casual misrepresentation that it’s only recording male-female outcomes and not the factors that produce those outcomes, while in fact, when it suits its purposes, it considers inputs as well, opens it to some of the most damning criticism of all.
But the reliance on inputs in this instance opens the door to a more thorough examination of the core sources of the overall GGGI gap.
The door being open, Geary storms through. Unlike the WEF and unlike pretty much all of current discourse on inequalities, be they racial, ethnic or gender-related, he states why men’s and women’s outcomes differ.
The same evolutionary and biological processes that, all other things being equal, result in a shorter average lifespan for men than women also contribute to the sex differences in economic outcomes (e.g., annual income) and political participation. It is the gap on these dimensions that drives the overall GGGI gap in highly developed countries and triggers political posturing and handwringing.
Again, just so. Overwhelmingly, men’s and women’s outcomes differ even in countries in which neither sex suffers legal disabilities that seriously limit their behavior. As Dr. Catherine Hakim and others have repeatedly shown, women’s and men’s preferences about how they spend their time differ, a fact that shows up in virtually every set of data comparing the two. Those preferences explain the earnings gap, the gap in electoral office outcomes, the childcare gap, the gap in hours worked, the gap in choice of college majors, etc. Time after time studies demonstrate the facts of those preferences, but, instead of sensible public policies, they produce only “political posturing and handwringing.”
The sex differences in economic and political engagement are a modern-day reflection of this more fundamental sex difference in the motivation to achieve status and resource control. In every culture in which it has been studied and across historical periods, higher status conferred (and still confers) more reproductive gains to men than to women, and in many contexts influences which men reproduce and which do not…
That one fact, so well known among those who study differences between the sexes, essentially obviates the purpose of the GGGI, at least in developed countries in which women’s choices are neither limited nor constrained by religious dogma, hidebound custom, poverty, etc.
That fact leads to the main part of Geary’s essay, the Basic Index of Gender Inequality (BIGI), his answer to the GGGI, that takes a stab at identifying and comparing where and to what extent gender inequalities actually exist.
I’ll delve into that next time.