In fact, some of the scientists dared to appear on TV. And the early surveys were smaller than the later ones, imagine the heresy. And surely all the papers that found differences must be refuted by some future ones, the ladies promise us.
Now, Rippon is a clear feminist activist, and so is the reviewer, Lise Eliot. For example, the root "gender" appears 13 times in the review, more than 11 times of "sex" – and most of the places with "sex" are meant to be negative (like "sexism"). You know, the biological research into the differences between men and women focuses on their sexual identity, not "gender" which is a deliberately vaguely sounding word that suggests "the sex" but one that may be changed by social habits.
While Rippon is a clear feminist activist (a member of the notorious team Rippon-Ripoff), I think she's not the most radical one because she admits that there are differences between male and female brains, at least statistically, e.g. when it comes to the size. (I first got into some mild trouble related to the brains at Rutgers in 1998 when my comment about the different number of neurons in the male and female brains was treated as the ultimate blasphemy by a feminist postdoc – that postdoc looks like a more hardcore anatomy denier than Ms Rippon.) But these are "differences in degree, not kind", Rippon says. Now, this is a very delicate statement.
How can we distinguish "differences in degree" from "differences in kind"? And is the difference between "differences in degrees" and "differences in kind" a difference in degree or in kind? ;-)
Is the difference between an SUV and a hatchback a difference in degree or a difference in kind? You may describe the dimensions of the cars and their parts by real, continuous numbers. Once these numbers become adjustable, it becomes possible to interpolate between an SUV and a hatchback. So you might say that the differences between the two cars are just differences in degree, not in kind.
However, this conclusion is just a reflection of the description you have chosen. The difference between an SUV and a hatchback is pretty deep and your ability to interpolate between the points hasn't changed it. The people who produced the cars probably knew in advance which of the two categories they wanted to produce. The same comments apply everywhere. Even the difference between a man's penis and a woman's – whatever is at a similar place, resembling the penis – may be said to be a difference in degree, not a difference in kind. But when the difference in degree becomes large or self-evident, it becomes silly to downplay the difference by talking about "degrees".
One of the classes of statements that Gina Rippon finds inconvenient are statements about the differences in white-vs-grey matter. A huge number of papers agrees that the percentage of the grey matter and the percentage of the white matter rather dramatically differ in the male and female brain. I think you shouldn't be manipulated by anyone and you should try to look at the papers, what the experts' literature says and what seems convincing.
Why don't you search Google Scholar for male female brain white grey matter, for example? You will find lots of relevant papers and as far as I can see, all the papers with a high number of followups – those that you get at the beginning – agree that they may see clear differences between the male and female brains.
Male brains are some 10% larger by volume than female brains. It's not shocking because men's bodies are larger in average, too. Even the density of the man's brain is some 1 or 2 percent higher than that of woman's brain. But you find lots of differences in the proportion of white and grey matter and other things. This 2008 paper with 990 citations studied the trajectories of the growth of the brain. And the trajectories are extremely different; the difference in trajectories is arguably more striking than the difference in the "outcome". The total cerebral volume of teenagers peaks at age of 14.5 for boys and 10.5 for girls. Just imagine that you have a standardized boy's brain and you compare the numbers 14.5 and 10.5. The difference is huge, indeed. Rippon faces an uphill battle if her chosen task is to downplay this difference between the two curves or the numbers 14.5 and 10.5, indeed. Much of the puberty-related growth is nearly absent in girls. Needless to say, this isn't an independent difference from the well-known fact that girls enter the puberty a bit earlier and they're finished earlier, too.
There are some really new papers that are relevant. This November 2018 paper – it's just three months old – used the data processed by source-based morphometry and its machine learning has achieved a 93% success rate in distinguishing male and female brains. It's not a perfect score but it's pretty high. You would get a similar score if you were distinguishing men's and women's breasts. ;-) You know, some women's chests are rather flat while some fatty men's busts look rather female. (You need to think about the real world men and women, not some idealized ones.) Also, the paper only used some aspects of the data. It could have gotten a much higher score if it looked at the brains from a different perspective.
But I am not terribly certain that individual male and female brains may be "very safely distinguished", even with lots of anatomic data. It's plausible that you could only increase the success rate from the 93% "somewhat". Maybe you could only get to 99% with similar tools. But the existence and relevance of the sexual dimorphism for the statistical men-women asymmetries in the society is totally self-evident.
Just imagine that you're building your "thinking team" and you have had the experience that men's brains do better. So you're not choosing your members according to the penises or breasts but according to the anatomic data about the brain. You will be able to determine the sex correctly in 93% of cases. So some 93% of your team will be men.
Again, 93% is not a spectacularly overwhelming majority. And indeed, I believe that whenever you get much more extreme majorities of men, it's not because of some "repeatable and reliable differences" between individual men's and women's brains. I believe that all the "much higher than 93% representation of men" in some fields (e.g. the near 99% majority in the Fields Medals) is due to the greater width of the men's statistical distribution.
There might be lots of technical things to discuss. It's clearly a whole scientific field – a branch of neuroscience – and while I have followed it rather closely for decades, I am no real expert. But the broader point I find problematic is that a science journal that has been considered prestigious for a very long time publishes ideologically driven stuff like that. Geneviene Fox published a similar positive review of the same book in The Guardian but at least everyone knows that it's just a left-wing rag, not a journal claiming to be scientific and politically impartial.
"The history of sex-difference research is rife with innumeracy, misinterpretation, publication bias, weak statistical power, inadequate controls and worse." https://t.co/SR8OFPjv1u— Nature News & Comment (@NatureNews) February 27, 2019
If you study the responses to this rather... hostile... tweet, most of them are actually negative. The most upvoted responses do say things like:
Everybody except a few academics like Cordelia Fine realise that there are differences between men and women. They seem terrified that if they admit this they will unleash unbridled patriarchy upon the world.— Dr John Barry (@MalePsychology) February 28, 2019
Oh no! Even Nature.....one of the premier science publications has been infected by the dangerous leftist anti-science ideology.— Bubba Lewsh (@BubbaLewsh) February 28, 2019
The march through our institutions is certainly thorough.
It will take 2 generations to completely purge our institutions of these radicals.
So folks like Gina Rippon and Lise Eliot aren't manipulating the whole society or the whole scientific community – yet. But ideologues like that have acquired a disproportionate amount of power – e.g. the power over decision what opinion pieces are published in Nature. Those who realize that the power of an ideology over science is wrong should work hard to reverse these developments – and they should make sure that it will be reversed in much less than 2 generations.