Damore's Pseudoscientific Google manifesto is a better evidence for sexism than it is for intellectual sex differences

Pseudoscience is effective. If it weren’t, people wouldn’t generate so much of it to try to justify opinions not supported by the bulk of the evidence. It’s effective because people trust science as a method of understanding the world, and ideological actors want that trust conferred to their opinions. They want their opinions to carry that authority, so they imitate science to try to steal some of that legitimacy for themselves. However, science is not flattered by this behavior, it is undermined and diminished.
The Damore Manifesto (PDF with hyperlinks) or “Google anti-diversity memo” is just such an example of pseudoscience, and largely by accident, it has gained outsize attention for what is essentially a C-grade highschool research paper. We will get to a deconstruction of Damore’s scientific case for gender differences in a moment (See the Scientific Critique section below), but I would first like to point out that it has served as an excellent bellwether for those who have more sexism than sense when it comes to evaluating scientific claims. It has proven itself compelling to a large number of people in the media, for example intellectual lightweight David Brooks, who finds it so compelling he calls on Google’s CEO to resign. He makes the astonishing claim that Damore is championing “scientific research” while his opponents are merely concerned with “Gender equality” (Classic false bifurcation fallacy). He also declares Evolutionary Psychology to be “winning the debate” and goes on to talk about superior female “brain connectivity”, and with a sigh, I wonder what Snapple cap he learned these “facts” from. Not only is this highly debatable, but even if male vs female patterning exists there is no reason to think that it is unaffected by environment and cultural patterning on brain plasticity. If boys supposedly have more developed motor cortex and girls more emotional wiring is that because the boy’s first toy was a ball, and the girl’s is a doll? The declarations that this is a settled question is absurd. We don’t know, and there are too many confounders to be making statements about biological inevitability with regards to gender when we are positively soaking in gendered norms of behavior.

XKCD evo-psych

Brooks conclusion, an example of being incompetent and unaware of it, is the Google leadership either “is unprepared to understand the research (unlikely), is not capable of handling complex data flows (a bad trait in a C.E.O.) or was simply too afraid to stand up to a mob”. He never considers the possibility, and given this is Brooks the inevitability, that he is wrong and has been hoodwinked by rather mediocre pseudoscientific argumentation. In these reactions, we learn more about these authors’ biases than we have learned about the suitability of women to write code, as the “manifesto” conforms to Brooks’ rather predictable biases and therefore receives almost no skepticism relative to the weight of the claims, which are hefty. Why is Brooks so blind to the shoddy scholarship of the Google memo?
Ironically, within the memo itself, we have the answer:

We all have biases and use motivated reasoning to dismiss ideas that run counter to our internal values.

With this we see the continuing evolution of pseudoscience, as they continue to evolve and mimic actual scientific debate and knowledge, the scientific language of motivated reasoning (the cultural or identity-protective cognition responsible for denialism), has filtered into their lingo. This is fascinating in itself, as the author has clearly read about motivated reasoning, yet is completely blind to it for the rest of his essay. This essay is classic pseudoscience, built on motivated reasoning, that uses a half a dozen references, cherry-picked from the literature, to make the astonishing claim that women are underrepresented in his white-collar workforce because of fundamental biological differences (read defects) affecting their capability to perform in a purely intellectual job. It is another in a long line of “just so” pseudoscientific justifications of gender or racial disparities that just happens to defend the status quo (subtext – “why I shouldn’t have to sit through any more mandatory diversity training”).
This is a wonderful example of Panglossian reasoning and if you haven’t read Candide, here is an example:

Master Pangloss taught the metaphysico-theologo-cosmolonigology. He could prove to admiration that there is no effect without a cause; and, that in this best of all possible worlds, the Baron’s castle was the most magnificent of all castles, and My Lady the best of all possible baronesses.
“It is demonstrable,” said he, “that things cannot be otherwise than as they are; for as all things have been created for some end, they must necessarily be created for the best end. Observe, for instance, the nose is formed for spectacles, therefore we wear spectacles. The legs are visibly designed for stockings, accordingly we wear stockings. Stones were made to be hewn and to construct castles, therefore My Lord has a magnificent castle; for the greatest baron in the province ought to be the best lodged. Swine were intended to be eaten, therefore we eat pork all the year round: and they, who assert that everything is right, do not express themselves correctly; they should say that everything is best.”
Candide listened attentively and believed implicitly, for he thought Miss Cunegund excessively handsome, though he never had the courage to tell her so. He concluded that next to the happiness of being Baron of Thunder-ten-tronckh, the next was that of being Miss Cunegund, the next that of seeing her every day, and the last that of hearing the doctrine of Master Pangloss, the greatest philosopher of the whole province, and consequently of the whole world.

Everything old is new again. What Voltaire was mocking were the glib and facile justifications of injustice in his time, which presume the current state of the world is in its best possible state and everything you see is the result of natural inevitability. Candide in Silicon Valley would exclaim, “Oh Pangloss, why is it that men are so over-represented in tech?” and Pangloss’s response, “For men are better at tech because of their intrinsic personality traits, and in this best of all possible worlds, male personality traits and even their flaws make for the best-possible technology and business practices.”
Anyone who has been following the Uber saga might question Panglossian reasoning about why tech is male. Even if the tech sector, as it exists today, is male-dominated because men perform better in the current pathological and Machiavellian environment, that doesn’t mean this is ideal, that it isn’t hugely, culturally flawed, and maybe desperately in need of womanly empathy. Taking such data at face value, an industry that is blind to the needs of fully half of its customers, or blind to the potential benefit of the perspective of the other half of the population, is playing with fire. Do we really think situations like Uber’s are a coincidence given the toxic masculinity of its leadership? The male-dominated model is not the best of all possible worlds. The male-dominated model was built by men, for men, so why be surprised when less women are attracted to it and fare worse within it?
A Scientific Critique of Damore’s Claims
Other authors have already done some of the heavy lifting, tackling the low scientific credibility of these claims and placing them in the historical context of the usual power-dynamic of trying to scientifically justify the status quo. These are useful, but we can expand upon them and use this essay as a learning opportunity for how to detect pseudoscience, so one hopefully doesn’t have to go through all the effort of endless debunking every time an ideologue vomits up some new dreck to explain why it’s only natural males, or whites, or whomever comes out on top.
And that is one thing we should immediately detect, the similarity to historical “just-so” arguments of scientific racism from the last few centuries. These arguments are old news, as anyone who has read Stephen Jay Gould’s Mismeasure of Man can tell you, and crop up whenever the dominant class in society has to explain why they’re on top without admitting it’s because they pushed everyone else down then pulled the ladder up after themselves. Once you hear people talking about why current race or gender divisions are natural, one should immediately take whatever argument is coming with a massive dose of skepticism. We have heard this nonsense before.
Let’s start with Damore’s words so it’s clear I’m addressing the scientific claims of his argument, contained in the last element of his TL;DR section and supported by the handful of actual scientific citation.

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.

Now keep in mind, this is in the context of an 69:31 M:F ratio at Google which is even higher in the engineering at 80:20, and arguments there is a strong business case for diversity.

Possible non-bias causes of the gender gap in tech
On average, men and women biologically differ in many ways. These differences aren’t just
socially constructed because:
● They’re universal across human cultures
● They often have clear biological causes and links to prenatal testosterone
● Biological males that were castrated at birth and raised as females often still identify
and act like males
● The underlying traits are highly heritable
● They’re exactly what we would predict from an evolutionary psychology perspective
Note, I’m not saying that all men differ from all women in the following ways or that these
differences are “just.” I’m simply stating that the distribution of preferences and abilities of men
and women differ in part due to biological causes and that these differences may explain why
we don’t see equal representation of women in tech and leadership. Many of these differences
are small and there’s significant overlap between men and women, so you can’t say anything
about an individual given these population level distributions.

It’s so nice that he cleared that up about not applying these findings to individuals this is hard to reconcile with the fact he is suggesting the 69:31 ratio or 80:20 engineering ratio at Google is in some meaningful way affected by these differences. Further, each of these statements lacks citation and can not be taken at face value, and I would describe them as either all wrong or grossly oversimplified. While the differences in gendered personality he subsequently describes is consistent within any culture examined, they are not consistent between cultures, which shows these are still culturally-dependent and not purely biologically deterministic (And of course, there is no matriarchal culture for comparison 😉 ) I have no idea why he conflated the research on androgens on personality development using CAH or androgen insensitivity with studies of personality changes in castration related to sex-reassignment, and prostate cancer treatment (if anyone can find a study of those “castrated at birth” please show me as I cant find it – I suspect he’s confused). He mixes two effects by saying androgens in the womb have effects on subsequent personality (likely but difficult to separate from gender norms) but then saying traits are heritable. Which is it? The Y chromosome or exposure to androgens? One is genetic, one is congenital. Finally, it’s rare to find examples where EP is truly “predicting” anything and not just indulging in the just-so stories and adaptationism (my favorite example of an evo-psych just so), i.e. more Panglossian logic. The field is…problematic, and strong statements about EP predictions like “exactly what we would predict from an evolutionary psychology perspective” should set off alarm bells.
Each of these statements are gross simplifications of large bodies of research, some of which are highly problematic areas with reproducibility problems, to justify a 2:1 or even 4:1 difference in hiring of men:women at Google. There is a general rule that “extraordinary claims require extraordinary proof”, well here is a man saying the reason Google has 2-4x as many men as women isn’t just the known, historic, institutional sexism that kept women from voting, owning property, having access to college education, equal pay etc., but fundamental biological differences across all cultures, that exists from birth, programmed by testosterone yet highly heritable (wah?) and conforming to predictions of a controversial scientific field that starts with conclusions and works backward to explanation. These effects are large enough, apparently, that Google should not try for parity in hiring and stop diversity training. Riiight. You better have some rock solid data to back this up.
Let’s look at the extraordinary data on why the women are so terribly disadvantaged based on their biology for software engineering (heads up, it’s a couple of wikipedia articles, and about 3 scientific citations)

Personality differences
Women, on average, have more:
Openness directed towards feelings and aesthetics rather than ideas. Women generally also have a stronger interest in people rather than things, relative to men (also interpreted as empathizing vs. systemizing).
These two differences in part explain why women relatively prefer jobs in social or artistic areas. More men may like coding because it requires systemizing and even within SWEs, comparatively more women work on front end, which deals with both people and aesthetics.
Extraversion expressed as gregariousness rather than assertiveness. Also, higher agreeableness.
This leads to women generally having a harder time negotiating salary, asking for raises, speaking up, and leading. Note that these are just average differences and there’s overlap between men and women, but this is seen solely as a women’s issue. This leads to exclusory programs like Stretch and swaths of men without support.
Neuroticism (higher anxiety, lower stress tolerance).This may contribute to the higher levels of anxiety women report on Googlegeist and to the lower number of women in high stress jobs.
Note that contrary to what a social constructionist would argue, research suggests that “greater nation-level gender equality leads to psychological dissimilarity in men’s and women’s personality traits.” Because as “society becomes more prosperous and more egalitarian, innate dispositional differences between men and women have more space to develop and the gap that exists between men and women in their personality becomes wider.” We need to stop assuming that gender gaps imply sexism.

For this segment he cites the wikipedia page on “sex differences in psychology; personality traits”, only useful for some background, not proof women!=engineers.
He cites This paper, which summarizes meta-analyses in the literature of personality with a reproducible effect showing that in a 6 dimensional model of personality traits women and men consistently score differently on being interested in “persons” vs “things”, and also that these sex differences in behavior are consistent across cultures. To be fair supporting literature exists which correlates these personality trends with differences in vocational choices, so it’s plausible that, all things being equal, there may be a gender gap in some professions based on personality traits.
This may be the only item of interest in his entire paper, as it is reproducible and there is evidence it impacts what choices the different sexes make about jobs. The problem I have with it is there is no way to control for the effect of how humans, starting when we’re toddlers, start to consolidate gender roles. If the image of the engineer or tech industry is predominantly male, this becomes a self-fulfilling prophecy. It also assumes that the current male-dominated status of tech couldn’t benefit from traits on the female axis including better interest in “persons” and creativity/artistic expression. The argument becomes a tautology, men are attracted to the tech sector because the tech sector is male. Add to that the tendency of institutions to maintain homogeneity by effects like in-group bias, and you see why male-dominated fields may remain static. Just imagine if we had accepted similar Panglossian logic 50 years ago that these gender-distributions as some kind of inevitable consequence of natural gender preferences, we’d still have only male doctors, lawyers, and executives, because, this is the best of all possible worlds, and there must be some evolutionary psychology to explain why there are no women doctors, or lawyers, or executives.
Damore then cites the wikipedia article on the Empathizing–systemizing theory. This appears to be moderately central to his argument, but again it is weak evidence. Not to beat a dead horse, but we are once again starting with the assumption that the current state of affairs represents some kind of ideal – the dominance of men in the field is “just so” because they’re more adapted to it, rather than they adapted the field to themselves or that there’s a host of historical factors such as women only got the right to vote in the last 100 years, co-ed schools in the last 50 years, they are still treated as second-class citizens including when it comes to pay. It also accepts one of the authors underlying assumptions, which is outside of my experience, which is that empathy is bad for engineering at Google. I can’t debate that, but least one former Googler has responded to this assertion and says absolutely not:

What I am is an engineer, and I was rather surprised that anyone has managed to make it this far without understanding some very basic points about what the job is. The manifesto talks about making “software engineering more people-oriented with pair programming and more collaboration” but that this is fundamentally limited by “how people-oriented certain roles and Google can be;” and even more surprisingly, it has an entire section titled “de-emphasize empathy,” as one of the proposed solutions.
People who haven’t done engineering, or people who have done just the basics, sometimes think that what engineering looks like is sitting at your computer and hyper-optimizing an inner loop, or cleaning up a class API. We’ve all done this kind of thing, and for many of us (including me) it’s tremendous fun. And when you’re at the novice stages of engineering, this is the large bulk of your work: something straightforward and bounded which can be done right or wrong, and where you can hone your basic skills.
But it’s not a coincidence that job titles at Google switch from numbers to words at a certain point. That’s precisely the point at which you have, in a way, completed your first apprenticeship: you can operate independently without close supervision. And this is the point where you start doing real engineering.

And once you’ve understood the system, and worked out what has to be built, do you retreat to a cave and start writing code? If you’re a hobbyist, yes. If you’re a professional, especially one working on systems that can use terms like “planet-scale” and “carrier-class” without the slightest exaggeration, then you’ll quickly find that the large bulk of your job is about coordinating and cooperating with other groups.

Essentially, engineering is all about cooperation, collaboration, and empathy for both your colleagues and your customers. If someone told you that engineering was a field where you could get away with not dealing with people or feelings, then I’m very sorry to tell you that you have been lied to. Solitary work is something that only happens at the most junior levels, and even then it’s only possible because someone senior to you — most likely your manager — has been putting in long hours to build up the social structures in your group that let you focus on code.
All of these traits which the manifesto described as “female” are the core traits which make someone successful at engineering. Anyone can learn how to write code; hell, by the time someone reaches L7 or so, it’s expected that they have an essentially complete mastery of technique. The truly hard parts about this job are knowing which code to write, building the clear plan of what has to be done in order to achieve which goal, and building the consensus required to make that happen.

Tom Smykowski says, engineers need more empathy
If true, this kind of knocks the teeth out of this particular “just so” justification that empathy is maladaptive. Is it possible, that the current culture of masculinity and therefore insularity is holding tech back? Couldn’t one make just as good an argument here, that Google hasn’t maxed its potential until it harnesses women’s superior social and interpersonal skills to help with things like teamwork and management? Is there no positive side to hiring women? And that is assuming these are large enough difference between women and men on these behavioral traits to justify hiring twice as many men as women.
Take a look at a recent paper from the theorist behind the E-S scale – Simon Baron-Cohen – and the differences on his Autism Spectrum Quotient scores (a newer scale Baron-Cohen has validated from the EQ SQ research and seems to have moved onto) for women vs men and STEM fields vs others that Damore is alluding to (I have to make some leaps here, Damore links the “E-S scale” wikipedia, which is a touch dated, without indicating a specific study, and ostensibly is referring to this work by Baron-Cohen who has advanced the idea of the “male mind” and autism being an excess of male mental traits – this itself has been critiqued as “neurosexist”). Studying an enormous database Baron Cohen finds a statistically-significant difference in AQ score between men and women, and women and those in STEM:
https://doi.org/10.1371/journal.pone.0141229.g005

While this may be statistically significant, it’s still a tiny difference – a matter of about 3 points on this scale between men and women, and women and STEM workers who, on average, also tend to have a similar 2-3 point higher AQ score than the female mean. To put this in perspective, this is a 50 point scale, and the nonclinical range of AQ is consistently in the teens to twenties while those diagnosed with autistic spectrum disorder have a mean around 35. It is also hard to conclude the differences between women’s score and STEM isn’t due to intrinsic or cultural factors – again, the best of all possible worlds fallacy, and it is no evidence to believe that 2-3 points difference in the mean score explains 2-4 fold gaps in hiring of men vs women. Draw a line at about 21 and ballpark an SD, of +/- 8 points, are there 2-4x as many men under the curve right there? Of course not. There’s too much meat under that curve to justify more than a couple of points difference in outcomes, assuming the effect is highly meaningful or beneficial. Alternatively, you could make an argument from the tails, that you could conceive of the extremes of the population such as AQ > 40 having approximately 2x as many men with this trait. One would have to believe that the population at google is so far shifted to the right in terms of male braininess, that the majority of the population at google has a mean AQ beyond 40, basically suggesting they all would score higher than the mean for those with autism spectrum disorder.
At the same time that Damore is critical of reducing populations to their means when there is significant overlap, to believe his argument – that tech is segregated by gender because not enough women have the “male mind” described by Baron-Cohen – requires one to believe that the status-quo ratio represents the ideal workforce, that these tiny differences in gender behavior are so debilitating as to explain the 2-4x difference in hiring, and that nothing beneficial is brought to the table by “empathic” team members. This makes no sense, these differences are slight. The area under the curve doesn’t support that these tiny differences – even if they were intensely meaningful, could generate such large differences in hiring. The areas where the variance between the populations becomes larger than the female population size is far above typical scores for ASD. Is the contention that the neurotypical can’t code?
Barely worth mentioning, he alludes to negative female personality traits by including a link to this wikipedia article on Neuroticism. This is a similarly weak argument. Again the effect is meaningless in size, if you go to the primary literature it’s consistent but small. There is no evidence such an mild difference in gender behaviors with regards to neuroticism would result in such a dramatic difference in hiring or performance, nor is it explained why neuroticism would be less adaptive in engineering vs other fields.
Finally he cites this opinion piece dismissing wage gaps between genders from a Libertarian online magazine, ignored without comment.
Does anyone maybe feel already the evidence here is a bit…light? You’re going to tell an entire gender they can’t do engineering based on a 3 psychology papers showing small and likely irrelevant differences in gendered behavior, a couple of wikipedia pages, and a libertarian opinion piece about how the wage gap is imaginary? You are surprised when women read this and they’re pissed? Do those saying this is “science” like David Brooks want to maybe rethink their expertise on this topic? Because they’re not looking too competent right now. This is classic pseudoscience – a weak, cherry-picked literature is flogged to support extreme ideological nonsense.
Next Damore asks why might men be more suited for software engineering? Well he’s got a whole paragraph and three more “sciencey” citations to justify that:

Men’s higher drive for status
We always ask why we don’t see women in top leadership positions, but we never ask why we
see so many men in these jobs. These positions often require long, stressful hours that may not
be worth it if you want a balanced and fulfilling life.
Status is the primary metric that men are judged on4, pushing many men into these higher
paying, less satisfying jobs for the status that they entail. Note, the same forces that lead men
into high pay/high stress jobs in tech and leadership cause men to take undesirable and
dangerous jobs like coal mining, garbage collection, and firefighting, and suffer 93% of
work-related deaths.

To justify this he cites the Atlantic opinion piece “The War Against Boys” which counter-intuitively suggests women are better at school than boys, and it’s boys whose performance is undermined (and this helps Damore’s argument how?). He cites this paper on gender differences in mate selection criteria, sadly is paywalled but it’s conclusions are college men prefer good looks, and college women want financial success in a mate, therefore men are more competitive for status jobs in order to satisfy female sexual selection. One could point out, this is a gross simplification of human mating dynamics and is one effect among many in human attraction or every woman alive would coo over Donald Trump. Finally he cites this paper on effects of testosterone on college age men that found when injected with additional testosterone in an Ultimatum game they behaved more aggressively, but also more generous to those who made them bigger offers thus supporting the idea testosterone enhances “status seeking” behavior. Again one would have to believe this is a large enough effect that women and men have no interest in tech or engineering for any other reason than mate selection. Or show that those engineers seeking status are running higher testosterone levels than men in other “high status” jobs to show this is anything other than a suggestive result. It is further discredited by the fact that over the last 40 years women have pursued more and more “high status” jobs. Although their numbers are more uneven with regards to “things important” type (read engineering) fields, to say this is biological determinism and not male obstructionism is not justified based on a single testosterone experiment done in college students and a oversimplified view of mate selection. It ignores that women are perfectly capable of being engineers and functioning at the top of fields like physics or mathematics, and human mating behaviors are far more complex than “women are gold-diggers.”
Again. Does anyone here find the evidence here a bit light? David Schmitt seems to agree and his research is that being cited by Damore:

Still, it is not clear to me how such sex differences are relevant to the Google workplace. And even if sex differences in negative emotionality were relevant to occupational performance at Google (e.g., not being able to handle stressful assignments), the size of these negative emotion sex differences is not very large (typically, ranging between “small” to “moderate” in statistical effect size terminology; accounting for perhaps 10% of the variance1). Using someone’s biological sex to essentialize an entire group of people’s personality is like surgically operating with an axe. Not precise enough to do much good, probably will cause a lot of harm. Moreover, men are more emotional than women in certain ways, too. Sex differences in emotion depend on the type of emotion, how it is measured, where it is expressed, when it is expressed, and lots of other contextual factors. How this all fits into the Google workplace is unclear to me. But perhaps it does.

As to sex differences in mate preferences and status-seeking, these topics also have been heavily researched across cultures (for a review, see here). Again, though, most of these sex differences are moderate in size and in my view are unlikely to be all that relevant to the Google workplace (accounting for, perhaps, a few percentage points of the variability between men’s and women’s performance outcomes).

Culturally universal sex differences in personal values and certain cognitive abilities are a bit larger in size (see here), and sex differences in occupational interests are quite large2. It seems likely these culturally universal and biologically-linked sex differences play some role in the gendered hiring patterns of Google employees. For instance, in 2013, 18% of bachelor’s degrees in computing were earned by women, and about 20% of Google technological jobs are currently held by women. Whatever affirmative action procedures Google is using appear to be working pretty well (at least at the tech job level). Still, I think it’s important to keep in mind that most psychological sex differences are only small to moderate in size, and rather than grouping men and women into dichotomous groups, I think sex and sex differences are best thought of scientifically as multidimensional dials, anyway (see here).

Not exactly a ringing endorsement of Damore’s use of his research and the data on increasing “status” vs “things” jobs suggests women might have been settling for those jobs only as they were in enforced gendered roles. Schmitt also seems to agree, extraordinary claims require extraordinary evidence, and these effects are small. Linking gendered behavioral differences to massive differences in performance in tech or engineering is an enormous stretch of logic. Schmitt emphasizes uncertainty, and the need to recognize complex role of gender on human behavior, he sure sounds like a scientist (for an Evolutionary Psychologist 😉 ).
The one who doesn’t sound like a scientist is Damore, who it turns out falsely claimed to have a PhD, gave his first interviews to alt-right youtubers, compared Google to Soviet prison labor camps even wearing a “Goolag” shirt for his WSJ editorial. He sounds less like a scientist, and more like he’s read the Crank Howto. I don’t understand how he ever expected to keep his job, after it turns out he did not have a PhD, he blasted a crank manifesto at his workplace that demeans a significant portion of the Google workforce, managed to embarrass his company on a national level, and ultimately demonstrated fundamental incompetencies in analysis and workplace etiquette. He would probably benefit from some training along the empathy axis, but instead is nursing a google-sized persecution complex.
To summarize, a junior, not-PhD employee of Google has written a 10 page document which purports to explain that the massive imbalance in male:female ratio at the company is not necessarily due to historic struggles of women for equal representation in equality, readily measurable bias, or structural sexism, but is instead due to female biology. The evidentiary basis for this argument is 3 bullet points followed by 3 short paragraphs that cite a few wikipedia pages, some libertarian/rightwing opinion pieces, a handful of papers on gendered differences in behavior showing some interesting but small differences between men and women, a bizarre reference to data from males castrated at birth (please someone find me that paper), some handwaving about male/female sex selection and “status” belied by a 40 year trend in women increasingly taking higher status jobs, and a borderline sexist psychological theory about “masculine brains” with similarly small differences between men and women. Notably, all of his arguments are dependent on the assumption that the male brain is fundamentally better at engineering because they got these jobs first and are thus appropriately over represented, and qualities like empathy and interpersonal skills don’t contribute to what is already a flawlessly healthy corporate culture in tech. By this logic women don’t do well in this culture because female cognition is inadequate to the task, not because it’s hard to fit in as a woman in at the boys club.

https://imgs.xkcd.com/comics/how_it_works.png

He does not discuss or cite any of the extensive literature for the constant measurable bias women undergo in the workplace. His argument dismisses the more probable negative effects of historical oppression of women (denial of the vote, of property, of jobs, of education) well into the last century as well as ongoing structural sexism. He fails to link these effects to actual performance or interest in software engineering, he grossly oversimplifies the relationship between culture and behavior in favor of radical biological determinism, and wraps it into a typical Panglossian “just-so” story.
After predictably being fired for sending a crudely-argued, c-grade essay on why “girls like talking not math”, he has now made the rounds of the alt-right internet, the antediluvian editorial page of the WSJ, and has cried persecution at Google comparing himself to a slave laborer. He denies he’s an ideologue, even though as example of left wing denialism he cites John Tierney of the Manhattan Institute, and his argument that global warming scientists are the real threat to science (plus Rachel Carson DDT revisionism – yay!). By their fruits you shall know them.
What this shows is, the people who are impressed by his line of argumentation and series of events are ideologically-primed to accept it, not that they are particularly good judges of science. Pay attention to who buys into this uncritically, it’s better evidence for weak, sexist minds than it is for weak minds of a sex.

58 thoughts on “Damore's Pseudoscientific Google manifesto is a better evidence for sexism than it is for intellectual sex differences”

  1. If there is to be equality, why don’t women have to register for the draft?

  2. I’m sorry, has there been a draft lately that I missed? Have you been put out by filling out a selective service card despite having a volunteer army for the last 40 years?

  3. You might like to consider this. It’s the best piece I’ve seen so far about the whole controversy and not just because it fits perfectly with my own experience. And it’s written by a women who’s an ex-tech.
    http://www.courant.com/opinion/op-ed/hc-op-mcardle-women-less-tech-inclined-20170812-story.html
    It;s been more than a little irritating over the past few days seeing countless articles by journalistic types who have very little idea how coders operate. This article nails it.

  4. I will be the first to admit Damore’s has some serious problems with his memo. What surprised me most about this whole insecticide is that Trump was right, the new is fake, too left leaning to be believed. Unlike other stories, we have both the original memo and media summaries to compare. The two partly lines are Democrats believe the gender inequality is because of sexist managers, while Republicans believe it is do to biology. Opinions on this topic often fall along party lines. Sexist articles about how female CEOs deliver better on average stock performance, are championed by the same people that criticize Damore.
    The proof is in the pudding. You may be surprised to find Damore’s ideas have been real word tested. The idea that you can make engineering more attractive to women by pink washing it. Talent Sonar is a consulting firm that specializes in pink washing job descriptions and apparently successful at it.

  5. By having these polices Google discriminates against adults with learning disabilities in the work force. Gender is not a disability, if you have a fully functioning brain it’s equal game.

  6. Your scientific response is anything but scientific. I tried to get through it but found all the hand waving and unsupported dismissive comments to be too much. Judging something to be insignificant based on your opinion alone is hardly scientific. You actually supported one of the whole underlying themes when you stated….”To be fair supporting literature exists which correlates these personality trends with differences in vocational choices, so it’s plausible that, all things being equal, there may be a gender gap in some professions based on personality traits”. But then are quick to dismiss that notion because we can’t control for childhood conditioning. Oh my!

    1. I’m not making an argument that the effect does not exist. I’m making the argument that the effect is too small to explain the 80:20 ratio. As the author of the literature that Damore cites says, the effects are small. So it’s not about denying male:female personality differences between populations exist, it’s about the link between these differences and the degree of this effect.
      Secondarily I argue that the underlying assumption, that the male-adapted status quo in tech, is somehow inevitable is false and this the “best of all possible worlds” fallacy. This is more related to the argument citing Baron-Cohen’s literature, and is even weaker. Women are perfectly capable of doing these jobs, and while they may have stronger preference for other work, it’s unlikely to be at the ratio observed.
      Is that short enough to follow?

  7. @#1:
    Are you a strong supporter of the feminist fight to make sure women are able to serve in combat roles?

  8. @#7 “Are you a strong supporter of the feminist fight to make sure women are able to serve in combat roles?
    No, not at all. What upsets me is that males seem to be second-class citizens in America. Why can’t they alternate between registering males one year, and females the next year, back and forth? When the issue came up for a Supreme Court vote, why did Justice Sandra Day O’Connor not recuse herself? Why does Fourth Love torture me by letting me stay with her for a week and by telling me every evening that we “are not romantically involved” even as we sit on the L-shaped bench for her to watch movies and for me to watch her legs in the flickering TV light of otherwise total darkness? [Please delete this Comment after 24 million views.]

    1. Finally, someone addressing the science. This is article you linked to actually a fantastic summary of the literature, although I think it focuses more on the first claim which is the “people” vs “things” alignment on a personality axis. Two comments
      1. I disagree with heterodox that Schmitt agreed with Damore’s conclusions. Based on the response I cited, he described Damore’s reasoning as “surgically operating with an axe”, part of why I quoted him so extensively is that he is an expert in the field and the author of the research being cited.
      This effect is appears real in the literature, it is consistent and replicated multiple times. But I agree with Schmitt that the significance here is overblown. It deals less with the ES analysis, or other claims Damore made, and maybe reasonably deals with the strongest evidentiary claim, that female preferences in vocation may be based on biologically-driven personality traits, but not their ability, which heterodox confirms small differences in.
      2. No one is disputing the actual literature itself, the question is whether or not Damore’s claims are backed by evidence in his memo. Heterodox does an excellent job in basically performing a systematic review and coming up with an exhaustive summary of the literature and they confirm the research discussed in (1) above. Yes, it exists and is real. However, they fail to address the fundamental argument. No one is saying he didn’t actually cite some actual science based on real effects. The question is whether or not you can use those results to explain an 80:20 ratio at Google, or that the current culture that is male predominant is the “best of all possible worlds” for tech. Of course men are going to perform better in a field dominated by men, designed for men, and if women prefer people-oriented, vs thing-oriented, and you make the entire field thing-oriented, you will see fewer women interested. This has to do more with his empathy claims which seemed to reject that female personality traits could benefit tech, and creates an effective feedback loop that will exclude women. This is a bug, not a feature. It’s structural sexism, that dismisses the potential contribution of half the population that also uses tech, is affected by tech, and has interest in working in tech.
      So ultimately heterodox in sticking to claims out of the context of the argument is failing to see the forest for the trees. Yes the citations he uses are to a real field in psychology, no one is saying the science he cites is wrong. The question is whether the citations support the extremity of his conclusions or his oversimplification of complex issues. They do not.

  9. So, since no one believes that the guys at google are sitting around conspiring against women, what is the cause of this, which you claim can’t be simple biology? Or are you claiming some conspiracy? Simply evidence of the patriarchy?! Truly pathetic.
    If this is as you seem to be claiming, why haven’t you started a business that hires only women? You could beat the pants off of your competition on labor costs.
    I do not believe that you even believe what you are claiming here. You have surely met a woman or two in your life. Pretending that they have the same goals and desires as men is obtuse, or simply ignorant. The reason that there is a disparity at google is because individual human beings are not collectivist carbon copies of one another, as much as the Socialists want to insist that they are.

  10. You started out by saying:
    ” The Damore Manifesto or “Google anti-diversity memo” is just such an example of pseudoscience…” and now say that
    :”No one is saying he didn’t actually cite some actual science based on real effects. The question is whether or not you can use those results to explain an 80:20 ratio…”
    So I guess now we are arguing only about the effect size. This was an inappropriate use of the term “pseudoscience” wasn’t it?
    Since only about 18% of undergraduate computer engineering majors are women, it might be hard for tech companies to all reach 50%. The problem is that women seem to be choosing other careers in college, many of them scientific and math-based, rather than engineering.
    http://www.aei.org/wp-content/uploads/2017/08/PHD.jpg
    Or, maybe it’s not a problem. Maybe they’re simply exercising their right to work in a field they’re most interested in.

  11. “What this shows is, the people who are impressed by his line of argumentation and series of events are ideologically-primed to accept it, not that they are particularly good judges of science. Pay attention to who buys into this uncritically, it’s better evidence for weak, sexist minds than it is for weak minds of a sex.”
    All that…just so you could say…if you don’t agree with me…your sexist.
    “Ideology binds and it blinds”

  12. This is a terribly written and argued piece. First, it starts off with paragraph after paragraph of leaden invective, ad hominem attacks, tautologies, and assumptions before we get to any actual arguments of the facts. Then, when we do< we get this type of strawman nonsense:
    +++ He cites this paper on gender differences in mate selection criteria, sadly is paywalled but it’s conclusions are college men prefer good looks, and college women want financial success in a mate, therefore men are more competitive for status jobs in order to satisfy female sexual selection. One could point out, this is a gross simplification of human mating dynamics +++
    This is not a "gross simplification." This a general observation of a massive and universally observed human trait. There is no culture known to exist or ever to have existed where men do not desire attractiveness in their mates and women desire financially successful men. There are obvious deviations from this massive norm, but it is entirely scientific to extrapolate how men and women might behave in large numbers in response to what is obvious to anyone who's lived in the real world.
    Worse is this piece, like most of the snowflake nonsense perpetuated by the tech press, accuses Damore of saying women can't program. Clearly, this is not true. The first computer program was written by a woman, Ada Lovelace.
    The point Damore makes is that women don't seem as attracted to his profession as men. I don't want to argue that point here, as I don't think its the right venue. I will note that to argue that women have not been encouraged to become programmers and engineers is PC nonsense. Schools, companies, the press, and so on have written about the topic at great length, have put in place "diversity" programs to recruit more women, and subjected people like Damore to auto da fes for arguing this point.
    Yet the women have not come. They've certainly come to other former male preserves such as veterinary medicine. Coding in cubicles, no. It is just possible that the job and its requirements are less attractive to women than men.
    rick

  13. #15
    Part of the reason they have not come is because screeds like Hoofnagle tell young women that the field is so full of sexism that they’ll never be able to make it on their own. This discourages young engineers from going into the field in the first place…choosing biology for example.
    This creates a self perpetuating cycle…less women go into the field…and people like Hoof say it’s because of sexism (any data that doesn’t confirm his bias gets the “ignored without comment” treatment). More young women feel that the field is even more sexist than before…look at the number of women in that field drop! The “only” way that can happen is because of rampant sexism and discrimination….repeat.

  14. Damore’s internal memo is not a “manifesto”. Damore had the bravery to try to affect change within Google’s intolerant and now proven echo chamber. Damore’s real point, is not that women can’t do math, but that women that can do math, prefer to work with humans. Damore tries to make the case that if Google would acknowledge that women want a different work environment (explain this graph MarkH: http://www.aei.org/wp-content/uploads/2017/08/PHD.jpg) and that if Google better accommodated what women want, more women would work at Google. It’s an effort to INCREASE the number of women at Google.
    Bill #13 makes an excellent case.
    MarkH goes off on a total virtue signaling shamefest tangent disguised as science.

  15. MarkH (the author if this commentary!) says:
    I’m sorry, has there been a draft lately that I missed? Have you been put out by filling out a selective service card despite having a volunteer army for the last 40 years?
    Yes, you did miss something (much like you missed the vast amount of scientific evidence (as well as common sense) that indicates that men and women (on average!!!! as Damore constantly emphasizes) do, indeed, have different interests and aptitudes.
    All MALES (sexist, huh!) between the ages of 18 and 25 are required by federal law to register for selective service. Here’s the penalty, as indicated by SSS.GOV. “Failing to register or comply with the Military Selective Service Act is a felony punishable by a fine of up to $250,000 or a prison term of up to five years, or a combination of both. Also, a person who knowingly counsels, aids, or abets another to fail to comply with the Act is subject to the same penalties.” If you were “put out put out by filling out a selective service card” then you’ve committed a federal felony and, if there’s any justice, you’ll be tracked down by the SSS goons and thrown into prison and fined $250,000 since you’re too ignorant or lazy to have registered as you were required to do.

    1. This is off topic, boring trolling. Stop talking about selective service. I don’t care (and I did register fwiw). It is boring and irrelevant to the discussion at hand. I’ll delete any further attempts to derail the thread this way.

  16. I am actually disheartened to see a piece on scienceblogs(!) in which the author strikes me with a big “PSEUDOSCIENCE!”-alert sign (like those we use for homeopathy or anti-vaxxers), but proceeds to admit in the commentary that it is basically how the effect sizes are weighed.
    Very dissappointing piece.
    Seems like the elephant got the upper hand yet again.

  17. I am actually disheartened to see a piece on scienceblogs(!) in which the author strikes me with a big “PSEUDOSCIENCE!”-alert sign (like those we use for homeopathy or anti-vaxxers), but proceeds to admit in the commentary that it is basically about how the effect sizes should be weighted when explaining a 80-20 sex disparity in a given field.
    I can’t remember that Damore even claimed that the available effect sizes can do that. (In my humble opinion, it is very well possible that small but significant biologically induced preferences are socially amplified.) I’d call that a classical straw man.
    Very disappointing piece.
    Seems like the elephant got the upper hand yet again.

    1. Damore says that they should cease efforts for gender parity and mandatory diversity training. That is tacit acceptance of the ratio

  18. “” The Damore Manifesto or “Google anti-diversity memo” is just such an example of pseudoscience…” and now say that
    :”No one is saying he didn’t actually cite some actual science based on real effects. The question is whether or not you can use those results to explain an 80:20 ratio…”
    So I guess now we are arguing only about the effect size. This was an inappropriate use of the term “pseudoscience” wasn’t it?”
    I think you missed a major point here. Citing science isn’t the same as doing science. The memo author cited some results – and those citations are not being questioned. The added value that he is purporting to give us is the argument that these differences justify an 80-20 hiring ratio. You are acting like this is just a minor detail, but it’s the entire justification of the memo!
    I am reminded of the people who argue that solar flares are the cause of any observed climate change. They certainly can cite plenty of literature showing that solar flares do, in fact, exist and that they effect our planet. But you cannot jump from “has some kind of effect” to “is the only factor having any effect” that easily, especially when the purported effect is, at best, minor.
    A more rigorous approach tries to tease out exactly _how much_ of an effect is present. But it’s one thing to do this in climate science which (believe it or not) is relatively simple – at least compared to human behavior!
    I feel like Damore’s supporters just are not comprehending the enormity of his claim. He’s oversimplifying like crazy and basing all his conclusions on little more than “just so” logic. It really is a classic case of an engineer letting his ego get in the way of a sober consideration of all possible variables. And we’ve seen many such engineers in both evolution discussions and climate change discussions!

  19. Ah, “don’t mistake denalism for debate.”
    That would tell me that this site is run by followers of the Worldwide Church of Global Warming, and that anyone who disagrees will be burned as a witch.

  20. If the science Damore cited is not being questioned but only his interpretation of it, then I still believe the use of the term “Pseudoscience” was misplaced.
    I agree that some of Damore’s statements do seem like oversimplifications of evidence from evolutionary psychology and elsewhere. But the totality of his memo seems to be a criticism that Google’s Diversity training is itself oversimplified, accepting only one possible cause for the gender gap: implicit bias. What he seems to be pleading for is the inclusion of other possible factors into the discussion. He suggests that the diversity goal might be better achieved that way. One of his specific suggestions is that Google should “be open about the science of human nature.” This seems quite reasonable to me.
    As far as Google’s “80-20 hiring ratio,” the difficulty with that seems to begin at the undergraduate level. Have you looked at the distribution of college majors by gender?
    http://www.aei.org/wp-content/uploads/2017/08/PHD.jpg
    Computer science majors are only 18% female. It seems that women with scientific/quantitative interest are choosing fields other than engineering to major in. Many of the life sciences, veterinary science, psychology have very heavy female majorities. Is this a problem? Or is it just women choosing work that they imagine they will enjoy? Why would you want any of them to make a different choice? What would you say to them?
    And, this being the reality, why blame tech companies for not hiring more women engineers?

    1. Bill, pseudoscience is all about over-interpreting weak data to support an ideological point.
      To your second point, I agree, Google faces an obstacle in hiring, they’re not going to get to 50% tomorrow, or if the small effects in gendered vocational preference are real, maybe not ever. I’m not critical of Google for having difficulty reaching gender parity, I’m critical of those who give a “just so” justification for why it is. Being in medicine, just such stories were used for decades to keep doctors, like my mother, from getting into medschool, residency, paid equally for equal work by her partners. In training she was told she was only there because the draft, and otherwise they would never have taken a woman for mans work. When she challenged her partners in her first job as to why they paid her less they told her she has a husband, she didn’t need the money. She persisted because she’s a tough as hell, but not everyone wants to deal with that garbage for 30 years and so not surprisingly gendered norms in professions, even medicine, take a long time to overturn. in 2000 my medical school class was the first at UVa that was 50/50 female. It takes time, and conscious effort to undo these attitudes. But the existence of these differences won’t go away until there are dedicated efforts to change the culture and attitudes, like Damore’s that create these differences.
      What I dispute is that the 80:20 difference is immutable, and is more related to cultural gender norms that establish math and engineering are for boys despite no actual difference in ability. This was my critique of “just-so” or Panglossian reasoning that suggests the distribution is inevitable. It will be as long as the fields are perceived as excessively male and hostile to women, it becomes self-fulfilling prophecy. Just as it was in medicine for decades, tech will have to go through similar convulsions to expel ingrained sexist attitudes about the value of half our population.

  21. One guy making a bunch of hand waving arguments that the other guy making hand waving arguments is completely wrong.
    Maybe next time we can argue about how many angels can dance on the head of a pin.
    Alternatively, how about you try taking all of those great studies you cite and their statistical distributions, create a model and analyze the results. You know, sorta like you were doing science or something.

  22. My first Fortran textbook had an example which required writing a program to determine the trajectory of an air launched missile aimed at a building. That was almost 50 years ago. It always struck me as a a great training example for anyone who was turned on by slaughter and destruction. At the time, we were slaughtering millions in Southeast Asia in a proxy war, with that and related devices But it was a great example for someone yearning to be a warrior, someone yearning for power and respect. Read adolescent male.
    Some years later, one of my co-workers wrote a textbook to teach Oracle. The examples he included in the textbook were clearly male oriented and misogynistic to the point of actually being cruel, pathological, sadistic. One involved the programmer exalting in being in a position to exercise power over a female subordinate by how he allotted or denied access privileges . Sick.
    And on and on. I have recollections of a surprising number of computer science professors who were basically emotionally incompetent and fascists. I remember a computer programmer co-worker (and part time professor of CS) who was essentially a heartless Nazi at his core. He made a really painful joke about the KKK to a new black employee on his first day on the job. A real people person….
    And so, in my limited experience, a surprising proportion of IT professionals I worked with were racist, misogynist, right wing, rabidly climate science denying, and basically human pin heads at many important areas outside of IT. Geez, I almost forgot my MIT trained PhD boss, a renowned database expert, who was so worried about the Unibomber sending him a present that he had the receptionist take suspicious packages addressed to him out into the parking lot, so she could risk getting blown up instead of him!. Empathy and compassion for other human beings ? Bah! ! Inferiors are expendable!
    Damore doesn’t surprise me a bit, unfortunately. The business IT world I worked in for many years was rife with people who loved the determinism of the computer and, having mastered some level of computer science, they thought that they were fonts of wisdom on any and all subjects. When someone like that misperceives that their road to power and glory is thwarted by HR policies, they can sometimes go full Nazi, IMO. The Nuremberg Psychologist Gustave Gilbert is said to have felt ” that Hitlerism was the product of the social and economic anxieties of a people long used to order.” Yeah, that is an interesting hypothesis.
    Oh yeah, and then there are the computer folks I’ve met who were also young Earth creationists. So no. Damore doesn’t surprise me a bit.

  23. >My thesis is that men and women aren’t different
    ” Even if the tech sector, as it exists today, is male-dominated because men perform better in the current pathological and Machiavellian environment, that doesn’t mean this is ideal, that it isn’t hugely, culturally flawed, and maybe desperately in need of womanly empathy.”
    >But the workplace would be different if women were in charge, because they have more empathy! *snarky remark* *winky emoji*

    1. A straw man if there ever was one, I never said men and women aren’t different. So see here for what dishonest debate looks like. I actually affirm one of the central points to Damore’s argument, the literature cited is consistent in demonstrating a difference in behaviors by gender, this may affect choices in vocation.
      What I dispute is this is biologically deterministic (limited data in literature to support), that the effects are small, in fact the APA has a brief summary on just this question in which they point this out.

      Mars-Venus sex differences appear to be as mythical as the Man in the Moon. A 2005 analysis of 46 meta-analyses that were conducted during the last two decades of the 20th century underscores that men and women are basically alike in terms of personality, cognitive ability and leadership. Psychologist Janet Shibley Hyde, PhD, of the University of Wisconsin in Madison, discovered that males and females from childhood to adulthood are more alike than different on most psychological variables, resulting in what she calls a gender similarities hypothesis. Using meta-analytical techniques that revolutionized the study of gender differences starting in the 1980s, she analyzed how prior research assessed the impact of gender on many psychological traits and abilities, including cognitive abilities, verbal and nonverbal communication, aggression, leadership, self-esteem, moral reasoning and motor behaviors.

      Psychologist Diane Halpern, PhD, a professor at Claremont College and past-president (2005) of the American Psychological Association, points out that even where there are patterns of cognitive differences between males and females, “differences are not deficiencies.” She continues, “Even when differences are found, we cannot conclude that they are immutable because the continuous interplay of biological and environmental influences can change the size and direction of the effects some time in the future.”

      My statements, which do not at all resemble your straw man, are more consistent with experts in the field.

  24. See thread, which has the links, but I’d summarize as:
    1) CA has “at will” employment which makes it very easy to fire people, balanced by 3 facts.
    2) (a) Unlike most states, CA disallows most non-compete agreements.
    (b) San Francisco, Peninsula & Silicon Valley form a dense market for engineering jobs, especially in software. Common joke here: “Joe changed jobs at lunch, didn’t move his car.” although Facebook HQ is a 12min drive from the Googleplex.
    See map.
    3) Tech recruiters are ~piranhas (not derogatory). If a company is in trouble or is really making a lot of employees unhappy, it’s like blood in the water.
    The thread above gives example of Mozilla, in which a Board fired a CEO quickly, because they would have bled people very fast.
    Given the expense of housing, companies love to hire people who already live here, and the social network is pretty tight-coupled. People move around.
    ===
    Having been a hiring manager / Director or VP at 4 different tech companies, starting with Bell Labs (whose hiring was ~selective as Google, with the same challenges), there are good ways and bad ways to make sensitive criticisms,
    especially if the topics are outside one’s domain of training and expertise.
    Good ways:
    1A) Write a thoughtful, well-researched (not Damore’s) letter, and give to boss and ask to discuss it with them. If need be, copy several levels in management chain, which may require skip-level if you are complaining about managers.
    I have no idea if Damore did any of this, but it doesn’t seem his style.
    (I once wrote a strongly critical letter about managers 2 & 3 levels above me, to one 4 levels above … but it didn’t stop me from being promoted to manager. In general, savvy management chains usually appreciate well-argued criticism.)
    Even the best management teams make mistakes on personnel policies, and this particular one (demographics) has been hard … for at least 50 years., from personal experience. The pipeline problem is real, but then there is negative feedback from ~male-dominated work environments. Elite organizations simply cannot hire and promote marginal performers, although good ones hire people they think will perform well in the longer term, which isn’t always the same.
    Companies err, however, young software people lacking management experience tend to err more and worse. (I’ve managed quite a few).
    If you think there are others who agree, talk to them privately and see if there’s a statement a bunch of you can sign.
    1B) If you get no satisfaction from this, and you really, really can’t bear management policies … line up another job & then leave without burning bridges.
    2) Not-so-good ways
    2A) Post something that some may agree with, but will cause serious upset among many employees (remember piranhas: if you were a recruiter, who would you be calling). As Mark & others have noted, Damore’s science claims are not very good, but easily confuse nonspecialists. Posting something contentious electronically, even to a small discussion group, in a place like Google, is a good way to get it spread rapidly.
    2B) Get fired. Threaten lawsuits, gather support from lots of people with strong ideology and relatively little relevant knowledge/expertise in this turf. Make as much fuss as possible, since you can talk & the company cant’ (mostly).
    When I was teaching CMPSC in early 1970s, ~35+% students were female, and they were quite competitive, worked as hard as the guys, including long nights at computer center.
    There was some difference of expectations among my advisees. The best male students expected to go to grad school, but not all the best females had such expectations.
    Me: “What are you thinking about grad school? She: oh, I never thought of that. Me: not for everybody, but you really ought to think of getting at least an M.S., I’ll be glad to write recommendation letters for assistantships.”
    See also So, about this Googler’s manifesto. by recently ex-Googler with 14 years there.

  25. thread, has links, but I’d summarize as:
    1) CA has “at will” employment which makes it very easy to fire people, balanced by 3 facts.
    2) (a) Unlike most states, CA disallows most non-compete agreements.
    (b) San Francisco, Peninsula & Silicon Valley form a dense market for engineering jobs, especially in software.
    Common joke here: “Joe changed jobs at lunch, didn’t move his car.” although Facebook HQ is a 12min drive from the Googleplex,Google Maps.
    3) Tech recruiters are ~piranhas (not derogatory). If a company is really making a lot of employees unhappy, it’s like blood in the water.
    The thread above gives example of Mozilla, in which a Board fired a CEO quickly, because they would have bled staff. The social network here is well-coupled.
    ===
    I’ve been a hiring manager / Director or VP at 4 different tech companies, starting with Bell Labs (whose hiring was ~selective as Google, with the same challenges), there are good and bad ways to make sensitive criticisms, especially if the topics are outside one’s domain of training and expertise.
    Good ways:
    1A) Write a thoughtful, well-researched (not Damore’s) letter, give to boss and ask to discuss it with them. If need be, copy several levels in management chain, which may require skip-level if you are complaining about managers.
    I have no idea if Damore did any of this, but it doesn’t seem his style.
    (I once wrote a strongly critical letter about managers 2 & 3 levels above me, to one 4 levels above … In general, savvy management usually appreciate well-argued criticism delivered appropriately.)
    Even the best management teams make mistakes on personnel policies, and this particular one (gender demographics) has been hard … for at least 50 years., from personal experience.
    Companies err, however, young software people lacking management experience tend to err more and worse. (I’ve managed quite a few).
    If you think there are others who agree, talk to them privately and see if there’s a statement a bunch of you can sign.
    1B) If you get no satisfaction from this, and you really, really can’t bear management policies … line up another job & then leave without burning bridges.
    2) Not-so-good way
    2A) Post something that some may agree with, but will cause serious upset among many employees (remember piranhas: if you were a recruiter, who would you be calling?).
    As Mark & others have noted, Damore’s science claims are not very good, but easily confuse nonspecialists. Posting something contentious electronically, even to a small discussion group, in a place like Google, is a good way to get it spread rapidly.
    2B) Get fired. Threaten lawsuits, gather support from lots of people with strong ideology and relatively little relevant knowledge/expertise in this turf. Make as much fuss as possible, since you can talk & the company can’t (mostly).
    When I was teaching CMPSC in early 1970s, ~35+% students were female, and they were quite competitive, worked as hard as the guys, including long nights at computer center. There were some differences of expectations among my advisees. The best male students expected to go to grad school, but not all the best females did.
    Me: “What about grad school? She: oh, I never thought of that.
    Me: not for everybody, but you’re one of the best students, really ought to think of getting at least an M.S., I’ll be glad to write recommendation letters for assistantships.”
    See also So, about this Googler’s manifesto. and
    short thread illustrates related issues.

  26. @Bill #23:

    If the science Damore cited is not being questioned but only his interpretation of it, then I still believe the use of the term “Pseudoscience” was misplaced.

    And you’d be wrong. One tactic of pseudoscience is to misuse real science to support bad conclusions.
    If Damore misinterpreted the evidence, then he’s guilty of peddling pseudoscience.

  27. #27.
    Hm, no. Scientists _always_ have been drawing poor conclusions based on solid data. It inevitably happens, and that does not make those scientists performing pseudoscience.
    Being split about the interpretation of data is part of the game.
    #21:
    Rick, i am not sure where Damore concluded that the cited evidence was 100% responsible for the observed effect.
    I don’t think any respectable scientists can or should do that. In fact, at least in my field, much of observed variance must remain unexplained because of unmeasured predictors.
    My biggest critique btw is that Damore should have been much more clear and precise in disentangling ability from interest.
    The data does not show that women are on average too stupid to code, it does show that they – even if they would be able to code – rather do other things.
    Why that is – biologically or socially induced – remains to be answered.
    My take is, as with most scientists, that this interaction cannot be disentangled. A handy model would be that existing, possibly small, but significant “hard-wired” preferences are amplified by stereotyping effects.
    What Damore then asks is simply:
    If gender/sex disparity is not based on stereotyping and discrimination alone, why should diversity programs operate only on the assumption that stereotyping and discrimination is the only factor contributing to said disparity?

    1. Most definitions of pseudoscience rely on a disparity between evidence and strength of claims. Psuedoscience is usually based on some evidence – cherry picked, or misinterpreted. My main point, which was supported by Schmitt, the author of much of the relevant research, is that the effect sizes were small. Schmitt agrees saying Damore was performing surgery with an axe.

  28. Let’s assume he was completely wrong. I don’t, however, accept your odd claim that the short memo was “crudely” done. Every scientist is wrong most of the time. This guy wasn’t even a scientist. What about being wrong justifies the firing? If your scientific position is strong, you have no reason to suppress dissent. Or to defend suppression.

    1. I describe it as crudely written because it simplifies complex problems in a way that is glib.
      It’s also not about suppressing dissent, he can dissent all he wants in his own time, but when you dissent in a way that causes public embarrassment for your company, you’re going to get fired. His dissent, far from being suppressed, has gone from Google, to right-wing blogosphere and youtube, to the editorial page of the WSJ. It’s hard to say his ideas are being suppressed, and I didn’t say he doesn’t have the right to disseminate them, but Google absolutely has the right to fire him for this fiasco.

        1. John, I really was trying to address your comment. Where have I failed? You mentioned it was odd that I found it crude. I explained why I felt it was so. You said it didn’t justify suppression of dissent, I don’t agree that his dissent has been suppressed, only that Google is protecting itself from embarrassment.

  29. Three words. Employment at will.
    If you upset your co-workers with fumbling, inarticulate, unscientific and/or grandiose attempts to ‘splain the world, and at the same time, you embarrass your company on the world stage, you had better be one exceptionally valuable asset to your company, or your young asset has a rather high probability of being made redundant.
    Perhaps his programming job just wasn’t that interesting or challenging to him, so he decided to take the time to pontificate on a subject about which he was poorly / self educated? Who knows.

    1. I didn’t say they didn’t have the right to fire him. I complain that they did fire him; which in turn elevated his memo to a huge deal which diminished and embarrassed themselves. Left alone, no one in the world would have cared about the memo.

  30. Chris: I posted a comment ~midnight, I think it was accepted, but seems lost. Spam filter?

  31. #29 & #31
    John: how long have you lived&worked in Silicon Valley?
    I posted something last night that explains why this forced Google.

  32. Posted last night, but seems lost. Try again.
    thread, has links, but I’d summarize as:
    Not firing Damore would have been serious trouble for Google, given the way Silicon Valley works, and the mobility of talent around here.
    1) CA has “at will” employment which makes it very easy to fire people, balanced by 3 facts.
    2) (a) Unlike most states, CA disallows most non-compete agreements.
    (b) San Francisco, Peninsula & Silicon Valley form a dense market for engineering jobs, especially in software.
    Common joke here: “Joe changed jobs at lunch, didn’t move his car.” although Facebook HQ is a 12min drive from the Googleplex,Google Maps.
    3) Tech recruiters are ~piranhas (not derogatory). If a company is really making a lot of employees unhappy, it’s like blood in the water.
    The thread above gives example of Mozilla, in which a Board fired a CEO quickly, because they would have bled staff. The social network here is well-coupled.
    ===
    I’ve been a hiring manager / Director or VP at 4 different tech companies, starting with Bell Labs (whose hiring was ~selective as Google, with the same challenges), there are good and bad ways to make sensitive criticisms, especially if the topics are outside one’s domain of training and expertise.
    Good ways:
    1A) Write a thoughtful, well-researched (not Damore’s) letter, give to boss and ask to discuss it with them. If need be, copy several levels in management chain, which may require skip-level if you are complaining about managers.
    I have no idea if Damore did any of this, but it doesn’t seem his style.
    (I once wrote a strongly critical letter about managers 2 & 3 levels above me, to one 4 levels above … In general, savvy management usually appreciate well-argued criticism delivered appropriately.)
    Even the best management teams make mistakes on personnel policies, and this particular one (gender demographics) has been hard … for at least 50 years., from personal experience.
    Companies err, however, young software people lacking management experience tend to err more and worse. (I’ve managed quite a few).
    If you think there are others who agree, talk to them privately and see if there’s a statement a bunch of you can sign.
    1B) If you get no satisfaction from this, and you really, really can’t bear management policies … line up another job & then leave without burning bridges.
    2) Not-so-good way
    2A) Post something that some may agree with, but will cause serious upset among many employees (remember piranhas: if you were a recruiter, who would you be calling?).
    As Mark & others have noted, Damore’s science claims are not very good, but easily confuse nonspecialists. Posting something contentious electronically, even to a small discussion group, in a place like Google, is a good way to get it spread rapidly.
    2B) Get fired. Threaten lawsuits, gather support from lots of people with strong ideology and relatively little relevant knowledge/expertise in this turf. Make as much fuss as possible, since you can talk & the company can’t (mostly).
    When I was teaching CMPSC in early 1970s, ~35+% students were female, and they were quite competitive, worked as hard as the guys, including long nights at computer center. There were some differences of expectations among my advisees. The best male students expected to go to grad school, but not all the best females did.
    Me: “What about grad school? She: oh, I never thought of that.
    Me: not for everybody, but you’re one of the best students, really ought to think of getting at least an M.S., I’ll be glad to write recommendation letters for assistantships.”
    See also So, about this Googler’s manifesto. and
    short thread illustrates related issues.

    1. I love all the persecuted cries of censorship. It was caught by a spam filter – multiple links tend to set it off. Chill out, it’s restored.

  33. Denialism? Wow. You are perpetrating that very thing. This is the worst abuse of pseudo-scientific knowledge I’ve read in a long time. The writer clearly knows nothing about the underlying science (and science generally) of gender differences but he knows a lot about ideology (read his previous posts). The writer clearly has never done real science himself. Worse than reprehensible. Charlatans like you love to massage your own egos while leaving others to clean up the mess. Go away.

  34. John Mashey
    “When I was teaching CMPSC in early 1970s, ~35+% students were female, and they were quite competitive, worked as hard as the guys, including long nights at computer center. ”
    Why do you think the percent of female computer science majors has dropped so much in the succeeding 40 years? It seems to be around 18% now.

  35. #53 Bill
    The 35% was late 1960s/early 1970s at Penn State, whose CMPSC dept was spinoff of math dept. CMPSC depts originated in EE (and sometimes other engineering), physics, business and at least one library science department. EE tended to have very low female % (and still does), math and maybe business were higher. Some schools had multiple CMPSC depts (Michigan had 3 for a while) & there was a lot of variation – in early 1980s, I gave many lectures at universities for ACM, and %s varied wildly.
    So, I haven’t studied this lately, but The Current State of Women in Computer Science says:
    “Much attention has been devoted to studying the reason for this drop in female computer science majors. The central conclusion is that the first personal computers were essentially early gaming systems that firmly catered to males. While early word processing tools were also available, the marketing narrative told the story of a new device that met the needs of men. As more males began purchasing computers for personal use, the “nerdy programmer” classification began to take hold in the professional world of computer science. By the mid-nineties, the percentage of women studying computer science at the postsecondary level had fallen to 28%.”
    I think there may be some truth to that, but other factors might be relevant.
    1) 1957 Sputnik stirred the US to up its education for math/science talent, and I think some of that emphasis attracted more girls into STEM for a while. It certainly did at my high school,
    2) Women often studied as mathematicians and then got into computing for one reason or another. See HIdden Figures for example, or Margaret Hamilton, to pick several NASA-related women.
    3) The first actual CMPSC degree program was at Purdue in 1962, but it took years for departments to form in any widespread fashion. When I started programming ~1967, CMPSC was more like something one happened to stray into, rather than something you thought about as a career in high school. (I was in physics+Math when I took 1st programming course). Few professors actually had degrees in CMPSC.
    At PSU, when I was teaching, we had quite a few folks start in math and then transfer to CMPSC, where we had ~400 undergrads & ~150 grad students.
    Anyway, I wouldn’t claim strong belief, I think there have been multiple factors, but the comments above about gaming may be one, if CMPSC image became firmly entrenched as gamer/hacker, as seen in various movies.
    On the other hand, at least we had this classic scene from the movie version of Jurassic Park.

  36. #51 MarkH Yes, that’s why I asked first about spam filters! I often include a lot of links,, run into this. I’d suggest deleting #32 & #33, leaving #48, but that would likely renumber things, a pain.

  37. Mark
    It’s awful what your mother had to endure. I have heaard stories like that from women in other professions too. But it’s good to remember that women today have many more opportunities since Title IX went into effect more than forty years ago. Women have been the majority of college students since 1980 and are the majority of students in most university departments.
    I agree with your statement: “I actually affirm one of the central points to Damore’s argument, the literature cited is consistent in demonstrating a difference in behaviors by gender, this may affect choices in vocation.”
    That was all Damore was saying. He really doesn’t say that “the 80:20 difference is immutable.” Nor does he say that “math and engineering are for boys.” I think you’re reading more into his statement than is there. His statements about women were about their preferences, not their abilities.
    If you believe, as you said, that “there is a difference in behavior by gender that may affect choices in vocation,” than it would follow that any attempt to increase the female participation in engineering should take that into account and make those differences part of the discussion. I believe that is what he was asking for. Not an end to diversity efforts but a change in the way it is done.

  38. #47 John F. Bramfeld “How long have you lived and worked in the rest of the country?”
    Not relevant to Silicon Valley familiarity, but since asked, and perhasps relevant to broader context.
    a) 18 years N of Pittsburgh, which is intersection of Appalachia, MidWest farm country, and Rust Belt.
    b) 9 years at Penn State, surrounded by Appalachia, but working vacations at Pittsburgh Mining Research Center, writing code to run at CMU & Pitt. Also, business trips to SHARE meetings and other universities.
    c) 10 years at Bell Labs in NJ, which included visiting various other sites around Bell System, esp. Boston, Chicago, St. Louis, Denver, but also while I was a Supervisor:
    ACM National Lecturer 1979-1983, 4 years, typically did ~30 talks/year around country, somewhat prolific, although this indefatigable little old lady (GMH) with a nanosecond cable did a few more.:-) This was 3-4 weeks/yr, where each day was hosted by local computing groups, usually a professional group in eve, a student ACM chapter in afternoon, and maybe class lecture, interspersed with meetings with faculty, show-and-tell with grad students, etc.
    The talks were “UNIX and the Programmer’s Workbench”, “Small is Beautiful & Other Thoughts on Programming Straegies” (think “Agile” ~1976) and “Software Army on the March.” USENIX has slides for the last 2.
    This wasn’t vacation, but work encouraged by management. University visits were often arranged by Bell Labs recruiters (i.e., technical managers who had long relationships with CMPSC/EE depts) at schools we recruited from, or that were doing interesting research we’d want to know about. Some visits were to schools we didn’t, to help assess whether we might recruit there. Non-university visits were for information gathering (like at XEROX PARC) or public relations, as well as professional society service for ACM.
    d) 1983-2001 Convergent Technologies, MIPS & SGI. I was an engineering manager or executive, sometimes an evangelist/troubleshooter when I wasn’t working on software strategy, interviewing candidates, or designing chips/systems. That took me all over the world, but also around US & Canada. I’ve done ~500 public talks & ~1000 sales pitches. SGI in particular had very technical customers, who wanted to see Chief Scientist/Enginner/VP folks, not just salespeople. So that might mean flying up to Seattle & spending all day with Boeing advanced technology folks or going down to Burbank and doing that for Disney Animation (or flying to Paris to have lunch at Maxim’s with our CEO & senior French execs. That was nice.)
    Anyway, between b), c) and d), I’ve worked professionally in ~40 states, all except (AK, DE, HI (too bad), ID, KY, ME, MT, ND, SD, VT. I’ve only lived in 3: PA, NJ and CA, the latter for 34 years within a few miles of Stanford. Being semi-retired, I only give occasional computer talks at Stanford, or for IEEE or meetup groups here, or a few universities back East or in UK.
    I have no connection with Google, other than knowing a few people, especially as there are a bunch of ex-SGI & ex-Bell Labs folks there, but of course, Google employs so many people it would be hard to live here without knowing some. 🙂

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