There’s no shortage of notes in Jordan B Peterson’s book 12 Rules for Life but that doesn’t mean every assertion related to facts is referenced. Also, when references are used they aren’t always tightly associated with the argument. Take this for example from chapter 2:
“This is perhaps because the primary hierarchical structure of human society is masculine, as it is among most animals, including the chimpanzees who are our closest genetic and, arguably, behavioural match. It is because men are and throughout history have been the builders of towns and cities, the engineers, stonemasons, bricklayers, and lumberjacks, the operators of heavy machinery.” – Peterson, Jordan B.. 12 Rules for Life: An Antidote to Chaos (p. 40). Penguin Books Ltd. Kindle Edition.
Now there is a lot wrong with that statement factually but the right reference here, if this was an academic essay, would be to a source discussing historical patterns of employment. Peterson instead links to some modern labour statistics here https://www.dol.gov/wb/stats/occ_gender_share_em_1020_txt.htm The tables do use the term ‘traditional occupations’ and ‘non-traditional’ based on proportions of women involves but this is ‘traditional’ in a very loose sense and includes “Meeting, convention, and event planners”. My point here isn’t that the table is wrong of even questioning gendered-roles in employment – just that a lot of references are weak in this fashion. It is vaguely related but not neatly tied to Peterson’s argument.
(This is quite long – so more after the fold)
Now in the copy I have, it is also just prior to this reference that the numbering has gone awry with the references. The list of figures given above is #37 which appears at the end of this chunk of text:
“Our categories are far older than our species. Our most basic category— as old, in some sense, as the sexual act itself— appears to be that of sex, male and female. We appear to have taken that primordial knowledge of structured, creative opposition and begun to interpret everything through its lens.”- Peterson, Jordan B.. 12 Rules for Life: An Antidote to Chaos (p. 40). Penguin Books Ltd. Kindle Edition.
yet it is the next paragraph that (I think) it applies to. That’s not Peterson’s fault – looks like a copy-editing issue but it makes some of the referencing even harder to follow his argument.
Back to his argument…
A lot of the references that are not just references to a book’s he likes or people expressing related ideas are like the one above – connected to measured differences in gender outcomes. Perhaps by design, perhaps due to his writing style, perhaps due to sloppy thinking or perhaps due to a magical combination of all of those, Peterson fails to pose the competing hypothesis well and connect them to actual facts.
For his benefit I’ll do that:
Peterson is (sort of) arguing that prior to very recent times (he doesn’t give a time frame but let’s assume prior to the 1970s) gender roles and differences in outcomes for different genders have been primarily determined by biological differences that are innate and immutable. I have to say “sort of” because their aspects of what he writes that contradict that and if I were to state that as a hypothesis to him I don’t know if he’d agree or disagree. However, that really, really does seem to be the theme he keeps returning to. I’ll call this the gender-determinism hypothesis – and I’ll concede a non-zero probability that it might be a strawman (erm strawperson?).
In opposition to that is a different hypothesis. This would be that that prior to very recent times (again let’s assume prior to the 1970s) gender roles and differences in outcomes for different genders have been determined by the interplay of biological differences and changing social structures – where the social structures have tended to favour men and that when technology (or other factors) have changed the nature of the relationship between biology and gender roles, those gender roles have often been slow to change because of preconceived notions of gender roles from the past. I’ll call this the sociological-hypothesis i.e. society and biology interact but they aren’t the same and change doesn’t happen all at once, and social change itself is regulated by social forces (including relative power of individuals and groups).
So an example of the second hypothesis: machinery has reduced the importance of physical strength in many aspects of society, enabling people with less overall physical on average to engage in such roles. However, some of those roles are still seen as gendered for historical reasons and change has been slow as a consequence.
Now look back at that table of numbers – which one of the two hypotheses does it support? If you say “maybe both” then you would be correct. The sociological hypothesis would imply that we’d see gendered employment roles – even for professions that have really only become recognised recently. The gender-determinism hypothesis would also imply that we’d see gendered employment roles.
Let’s add another hypothesis. I’ll call this one ‘straw-feminism’. It goes like this: biology is irrelevant, men are just shits and have conspired to control society, we are all the same and any differences in gender outcomes in society are due to a male plot against women. I don’t know anybody who really believes that and parts of it actually run in direct opposition to some branches of feminist thought. It’s very much a strawman argument but look at that set of figures again. Does it support the ‘straw-feminism’ argument? Yes! straw-feminism would ALSO imply that we’d such outcomes!
How come! Because people aren’t ignorant – each of these hypotheses is trying to EXPLAIN why we see different outcomes for different genders. Consequently, pointing to broad data that shows different outcomes for different genders doesn’t help us evaluate which one of these hypotheses is true.
This is a very subtle form of circular reasoning or begging-the-question. It is subtle because the specific data was not used to construct the hypothesis (so it isn’t literally already accounted for), so if you are already looking at things through the lens of the hypothesis it appears to confirm your belief. So stats like these reinforce the belief in the hypothesis you favour.
This why it is important to focus on what kind of evidence would distinguish the competing hypotheses and you can’t do that unless you’ve properly managed to articulate them. Peterson can’t do either of those things and I doubt he would want to if he could.
Here’s a non-Peterson example. A study was recently done of different earnings for Uber drivers that examined gender differences. The study found that women were earning less than men. There’s a relatively balanced look at it by Freakonomics here and poorly argued account at The Federalist here. The Federalist piece says that the study disproves ‘the pay discrimination myth’ which is like a special treasure for a student of the pathology of informal reasoning like myself. The study literally found a gender pay difference, therefore, it can only CONFIRM pay discrimination (depending on your definition of ‘discrimination’).
What the study does do (and why The Federalist sees it as disproving something) is eliminate a PARTICULAR hypothesis for why you might see pay differences between gender. In this case, the hypothesis that differences in pay must because of active and intentional malice – i.e. something close to the ‘straw-feminist’ hypothesis I mentioned above. What the study doesn’t do is disprove that systemic biases impact pay, it just removes (for one example) active managerial malice as an explanation.
We can see this in other references Peterson uses. For example, he discusses personality differences between men and women and cites studies that use the Big Five measures that confirm differences.
171 “Gender differences in personality across the ten aspects of the Big Five.” Frontiers in Psychology, 2, 178; Schmitt, D. P., Realo, A., Voracek, M., & Allik, J. (2008).
(I picked that one because it is easy to access but it starts with a weird Bill Cosby quote that the authors must regret now – it’s from 2008)
This study looked at sub-factors of the Big Five and finds gender differences in personality that aren’t observable when looking at the Big Five at a higher level. It finds more differences and that some of those differences are also moderated by ethnicity. It also reports that some differences found in other studies are bigger in some modern Western nations than in some more traditional societies (a point Peterson comes back to also).
However, those differences are still small and the overlap is substantial:
“All of the mean differences we found (and all of the differences that have been found in the past – e.g., Feingold, 1994; Costa et al., 2001) are small to moderate. This means that the distributions of traits for men and women are largely overlapping. To illustrate this fact, in Figure 10we present the male and female distributions from our sample for the trait which showed the largest gender difference, Agreeableness. One can see that both men and women can be found across a similar range of Agreeableness scores, such that, despite the fact that women score higher than men on average, there are many men who are more agreeable than many women, and many women who are less agreeable than many men. Given that Agreeableness showed the largest gender difference in our study, all other traits for which we reported significant gender differences would show even greater overlap in men’s and women’s distributions.”
Even if we assume a strict biological account for these differences, we still can’t get to Peterson’s sharp archetypal division between humans. Imagine, for a moment (and I’m not claiming this is a serious hypothesis) that this difference in Agreeableness was 100% due to the hormone testosterone. It’s famously a ‘male’ hormone but important to the biology of all humans and we all have it – but where would that get us in terms of our two hypotheses for accounting for different gender outcomes? If anything, these small overlapping differences between males and females suggest that we should see small differences in gender outcomes in society.
Look back at that table of professions. The difference in gender proportions for some professions are huge – they are much bigger than the distribution differences in traits like agreeableness. They are bigger than the difference we see as far as height and weight go for gender. That doesn’t disprove Peterson’s hypothesis but it does make it harder to sustain but we knew that already.
Hey, but maybe I am straw-manning Peterson. Maybe he too accepts that its a complex interaction between social and biological forces. I mean, in some ways he MUST believe that – after he thinks your position in a perceived dominance hierarchy can impact levels of a hormone and those hormone levels impact you physically and emotionally AND that you can change your behaviour to impact ALL of those things…but then…why’s that not true for gender differences? All Peterson can do is hand wave at archetypes.
Again, whether by design or by incompetence, Peterson can’t address questions of social change only individual change. So when change is occurring he must attribute this to people trying to change society – even though, if that’s possible it necessarily undermines his own views about how society works.
Changing gender outcomes in higher education is something Peterson keeps coming back to. Of course, he now needs to park his previous claims that differences in outcomes by gender must be due to biology+meritocracy because now men don’t do so well. Again he cites figures but he fails to connect those figures to his argument meaningfully.
177. See, for example, Hango. D. (2015). “Gender differences in science, technology, engineering, mathematics and computer science (STEM) programs at university.”
(Peterson’s link didn’t work for me but this does http://www.statcan.gc.ca/pub/75-006-x/2013001/article/11874-eng.pdf – probably site changes since publication)
This study shows that maths proficiency is the major driver in choosing to study STEM courses at university and that women choose STEM courses less often than men. In addition that in high school, based on some measures, men were better at maths than women. Aha! If men are biologically a bit better than women at maths, then even if that overlap is big, then this would explain the difference! Biology wins! Woah, hold on there – NOTHING is that simple.
The study looked at mathematical ability AND perceived mathematical ability and looked at ways of controlling for those. Guess what? The gender imbalance was still there. The report when on to say:
As a result, if more men are found in STEM programs, it is not because they have better PISA scores than women. In fact, even when all measures of mathematical ability are combined in a model, gender differences remain significant. This suggests that the gender difference in the selection of a STEM program at university is due to other, unobserved, factors that go beyond academic achievement, parental interactions and influence, and immigration status. – Gender differences in science, technology, engineering, mathematics and computer science (STEM) programs at university
“Girls can win by winning in their own hierarchy— by being good at what girls value, as girls. They can add to this victory by winning in the boys’ hierarchy. Boys, however, can only win by winning in the male hierarchy. They will lose status, among girls and boys, by being good at what girls value. It costs them in reputation among the boys, and in attractiveness among the girls. Girls aren’t attracted to boys who are their friends, even though they might like them, whatever that means. They are attracted to boys who win status contests with other boys. If you’re male, however, you just can’t hammer a female as hard as you would a male. Boys can’t (won’t) play truly competitive games with girls. It isn’t clear how they can win. As the game turns into a girls’ game, therefore, the boys leave. Are the universities— particularly the humanities— about to become a girls’ game? Is this what we want?” – Peterson, Jordan B.. 12 Rules for Life: An Antidote to Chaos (pp. 298-299). Penguin Books Ltd. Kindle Edition.
Yeah, whatever happened to that old meritocracy argument? I think Peterson is close to the truth here – it’s just that he can’t follow through to where that truth points and instead diverts into obnoxious cliches (in the real world women are attracted to friends**). Society is changing but changes in gender roles are assymetric because ‘male’ cultural attitudes haven’t changed as quickly as ‘female’ ones. But that’s not change Peterson likes and therefore that’s bad change rather than just ‘nature’.
Next time: The Conclusion!
**[ And possibly there is a social shift towards ‘friendship’ as a key element in heterosexual relationships:
I say ‘heterosexual relationships not because such things aren’t important in non-heterosexual relationships but purely because Peterson is talking about heterosexual ones (as as we saw in Part 10 doesn’t talk about other kinds)]