Being Googly Is More Important Than Being Right
Googly. Yes, it's a word, at least within Google. It's an adjective describing someone who has the appropriate characteristics of a Google employee.
How do I know this? Because the last time I went through the Google recruitment mill, I got up to the point where we were discussing a trip to Mountain View for in-person interviews. That's when they let me know that one of the in-person interviews was to determine if I was "Googly."
James Damore was just fired for being insufficiently Googly. He rejected Google's internal mythology, and worse, he did so with basic math, in a company where mathiness is supposed to be part of the culture.
He also rejected a piece of the general mythology so firmly that what he said was actively misreported — so blatantly that one has to conclude the reporters either can't read the hard parts of the memo, didn't bother to read the memo, or somehow managed to see things that weren't there. (That last is my guess, based on the examples of Trump Trance we've seen over the last six months.)
My evidence for this is literally dozens of headlines like this one:
"A Google engineer said women may be genetically unsuited for tech jobs."
I encourage you to read the whole memo in its unexpurgated form — the one Gizmodo published carefully deleted all his links to sources and all explanatory diagrams — but I think from the reaction, this bullet point is the key statement that got Damore fired:
Differences in distributions of traits between men and women may in part explain why we don’t have 50% representation of women in tech and leadership. Discrimination to reach equal representation is unfair, divisive, and bad for business.
Damore went on to explain this with references to the literature — and sure enough, a number of social scientists concerned with the field of gender differences have supported him publicly, not that it seems to have mattered. But we can actually see that the first sentence is almost certainly true, just from basic statistics. Yes, there's going to be math, but I promise to try to make it clear even if you're not a math geek.
The theory of probability, and the whole notion of statistics, got started mathematically in the 17th century, but a lot of the major concepts were developed in the late 18th and early 19th centuries. One of the key notions was the Gaussian distribution — the old familiar bell curve — and the Central Limit Theorem. Both of these are demonstrated in this video of falling pachinko balls.
As you see, the bouncing pachinko balls, being knocked around by colliding with a bunch of pins, naturally fall into the bins below in a way that makes the piles form the familiar bell curve.