Intelligence is increasingly a political cleavage, thanks to the phenomenon of skill-biased technological change.
If your income is earned through competition on an open market, intelligence is an unambiguous good. You need it, you want it, possessing it makes you succeed and lacking it makes you fail. The continued development and maximization of artificial intelligence is an obvious and mundane reality of business development.
If your income is earned through a bureaucratic office of any kind, success in that office increasingly requires opposition to intelligence as such. Unions were always essentially anti-intelligence structures, defending humans from innovative insights that threatened to displace them. But unions were defeated by the information revolution, which was a kind of global unleashing of distributed intelligence. Now, atomized individuals within bureaucratic structures spontaneously converge on anti-intelligence strategies, in a shared sub-conscious realization that their income and status will not survive any further rationalization.
How else do you explain the recent co-occurrence of the following?
Mass political opposition to mundane psychology research on intelligence
Evangelical public moralizing against competence as an increasingly visible career track (in journalism, some academic disciplines, the non-profit sector, etc.)
Social justice culture in general as a kind of diffuse “cognitive tax.” It is a distributed campaign to decrease the returns to thinking while increasing the returns to arbitrary dicta.
The popularity of pseudoscientific concepts serving as supposed alternatives to intelligence, e.g. “emotional intelligence,” “learning styles,” etc.
Finally, it is no surprise that many of these symptoms are rooted in academia. This is predicted by the theory. The authority and legitimacy of the Professor is predicated on their superior intelligence, and yet their income and status is predicated on anti-intelligent cartel structures (like all bureaucratic professions). It is no wonder, then, that increasing intelligence pressures are short-circuiting academic contexts first and foremost.
Once upon a time, professors could enjoy the privilege of merely slacking on competitive intelligence application. These were the good old days, before digitalization. Professors could be slackers and eccentrics: a low-level and benign form of anti-intelligenic intellectualism. They didn’t have to actively attack and mitigate intelligence as such. Today, given the advancement of digital economic rationalization, humanities professors work around the clock to stave off ever-encroaching intelligence threats.
The difficult irony is that anti-intelligence humanity professors are acting intelligently. It is perfectly rational for them to play the game they are playing. Not unlike CEOs, they are applying their cognition to maximize the profit of the ship they are stuck on.
In a recent post, I encountered an interesting empirical fact about the college wage premium accruing to low-ability college grads over the period 1979-1994. Looking at a 2003 article by Tobias, I wrote: "There is a lot of temporal volatility for the class of low-ability individuals. In fact, for low-ability individuals there is not even a consistent wage premium enjoyed by the college-educated until 1990."
I have begun to wonder if this pattern has anything to do with the non-linear relationship between GPA and PC. If the low-ability college entrants feel they are much less certain to enjoy a wage premium over the "townie losers" they left behind, what better strategy than to invest their college-specific word games with extreme moral significance? That way, even the dumbest college grad can be confident that they will remaindistinguished from the more able among the non-college-grads.
[Hat tip to a few high-quality comments on this blog recently, I don't recall exactly but I think someone may have made a point similar to this; the seed of this post might have been planted there, thank you.]
Although this last point is only conjecture, it is curious that right when the wage premium for low-ability college grads arrives is right when the first wave of campus political correctness kicks off — the early 1990s. Especially if you buy Caplan's signaling theory of education, it's not at all implausible that for low-ability college grads their wage-premium is secured primarily through a specialization in moral signaling.
A reader/watcher/listener has brought to my attention another paper, which shows that, for college-educated individuals, earnings are a non-linear function of cognitive ability or g — at least in the National Longitudinal Survey of Youth from 1979-1994. The paper is a 2003 article by Justin Tobias in the Oxford Bulletin of Economics and Statistics.
There may be other studies on this question, but a selling point of this article is that it tries to use the least restrictive assumptions possible. Namely, allowing for non-linearities. In the social sciences, there is a huge bias toward finding linear effects, because most of the workhorse models everyone learns in grad school are linear models. Non-linear models are trickier and harder to interpret and so they're just used much less, even in contexts where non-linearities are very plausible.
A common motif in "accelerationist" social/political theories is the exponential curve. Many of us have priors suggesting that, at least for most of the non-trivial tendenices characterizing modern polities, there are likely to be non-linear processes at work. If the contemporary social scientist using workhorse regression models is biased toward finding linear effects, accelerationists tend to go looking for non-linear processes at the individual, group, nation, or global level. So for those of us who think the accelerationist frame is the one best fit to parsing the politics of modernity, studies allowing for non-linearity can be especially revealing.
The first main finding of Tobias is visually summarized in the figure below. Tobias has more complicated arguments about the relationship between ability, education, and earnings, but we'll ignore those here. Considering college-educated individuals only, the graph below plots on the y-axis the percentage change in wages associated with a one-standard-deviation increase in ability, across a range of abilities. Note that whereas many graphs will show you how some change in X is associated with some change in Y, this plot is different: It shows the marginal effect of X on Y, but for different values of X.
The implication of the above graph is pretty clear. It just means that the earnings gain from any unit increase in g is greater at higher levels of g. An easy way to summarize this is to say that the effect of X on Y is exponential or multiplicative. Note also there's nothing obvious about this effect; contrast this graph to the diminishing marginal utility of money. Gaining $1000 when you're a millionaire has less of an effect on your happiness than if you're at the median wealth level. But when it comes to earnings, gaining a little bit of extra ability when you're already able is worth even more than if you were starting at a low level of ability.
The paper has a lot of nuances, which I'm blithely steamrolling. My last paragraph is only true for the college educated, and there are a few other interesting wrinkles. But this is a blog, and so I mostly collect what is of interest to me personally. Thus I'll skip to the end of the paper, where Tobias estimates separate models for each year. The graph below shows the size of the wage gap between the college-educated and the non-college-educated, for three different ability types, in each year. The solid line is one standard deviation above the mean ability, the solid line with dots is mean ability, and the dotted line is one standard deviation below the mean ability.
An obvious implication is that the wage gap increases over this period, more or less for each ability level. But what's interesting is that the slope looks a bit steeper, and is less volatile, for high-ability than for average and low-ability. There is a lot of temporal volatility for the class of low-ability individuals. In fact, for low-ability individuals there is not even a consistent wage premium enjoyed by the college-educated until 1990.
Anyway, file under runaway intelligence takeoff...
Following on my post from yesterday, I've been thinking about how the widespread and often racist views of "welfare" in the United States — especially among poor whites — fester on top of the educated-progressive party line that heritable IQ differences are bunk.
An interesting wrinkle from the study I cited yesterday (Papageorge and Thom 2018) is that the genetics-earnings link is conditioned by family SES. In other words, children with strong genetic endowments for abstract intelligence will not reach their full earnings potential if they are hampered by a poor family environment.
This is consistent with the left-hereditarian position that the normalization and de-stigmatization of IQ differences and IQ testing would, on net, help poor and stereotyped minorities the most. There are highly gifted children in poor and/or minority communities who are not meeting their potential, and we should do everything we can to support them, including the use of IQ tests to fast-track their selection into new opportunities. One could also argue on this basis that redistributive support for such communities is more necessary and/or more "deserved." I'm not personally interested in gradations of desert as a framing for the ethical necessity of egalitarian arrangements, but others might be.
Some of the anti-welfare and anti-black political sentiment of whites is based on the belief that poor black communities should be written off as hopeless in general. This impression is at least partially due to the fact that a lot of government redistribution over the past few decades has been based on truly naïve and false blank-slate ideology, so people now infer that no amount of redistribution could possibly help poor black communities, if it hasn't yet. They come to think we should stop "throwing good money after bad," when they might well be open to throwing good, smarter money after all the bad, dumb money of past efforts. Understanding the reality of how genetic endowments affect economic outcomes, and how those endowments are distributed, promises more than one way to shake up the whole reactionary, conventional framing of welfare politics in general.
Someone sent me a recent NBER working paper by Nicholas W. Papageorge and Kevin Thom on polygenic scores and educational attainment/earnings. Most pertinent to my theoretical interests is that the link between genes and income appears to increase over recent decades.
In my lectures on the politics of media (really about the politics of technology more generally), I dedicate a session to the topic of skill-biased technical change (SBTC). While the econometrics and specific interpretations are debated, there is a literature in Economics that suggests certain technological innovations (i.e. computing) increase the earnings of the highly skilled relative to the less skilled. I would sometimes wonder to what degree "skills," which sound like primarily acquired things, in fact reflect heritable traits. Or if one could separate these out...
Papageorge and Thom provide one of the first efforts to study this question explicitly. "This is the first study to estimate the returns to genetic factors associated with education using micro genetic data and disaggregated measures of earnings and job tasks across cohorts."
Here is their summary of the genetic effect, conditional on time period:
The returns to these genetic endowments appear to rise over time, coinciding with the rise in income inequality after 1980. Accounting for degree and years of schooling, a one standard deviation increase in the score is associated with a 4.5 percent increase in earnings after 1980. These results are consistent with recent literature on income inequality showing not only an increase in the college premium, but also a rise in the residual wage variance within educational groups (Lemieux, 2006). We also find a positive association between the score and the kinds of non-routine job tasks that benefited from computerization and the development of more advanced information technologies (Autor, Levy, and Murnane, 2003). This provides suggestive evidence that the endowments linked to more educational attainment may allow individuals to either better adapt to new technologies, or specialize in tasks that more strongly complement these new technologies.
Basically, they observe what you would expect to observe if the computerization that begins around 1980 allowed the escape and takeoff of "non-routine analytic" power or abstract intelligence by those most genetically blessed with it. Implicitly, individuals less genetically blessed with "non-routine analytic" powers begin to be left behind around 1980.
Their findings cannot explain the entire postwar dynamic of increasing inequality and relative stagnation of the lower classes, however, because the flatlining of median wages begins around 1973 if I recall correctly. The study seems somewhat coy about naming or even labeling the polygenic score; but my non-expert intuition is that it would have to be something quite akin to what is called the "g-factor" or general intelligence, right?
One limitation of the study is that they use a dummy variable for the period after 1980. I would be curious to see what happens if one re-runs their models with a continuous variable for year. My intuition is that individual-level economic outcomes are more skill-biased/g-loaded today than in the 1980s, but I'm not yet up on any studies this precise on that question in particular.
In my current book project, one of my goals is to provide the fullest possible empirical accounting of the strange new persona sometimes derisively called the "social justice warrior."
Although the main contours of my argument are pretty well developed, there are various sub-hypotheses that I've had for a while — but no data to test them.
Just last week, I was offered access to a goldmine of data collected by College Pulse. They told me I'm allowed to share my analyses, but not the data. They have an app that gives students various rewards in exchange for taking surveys. They've taken dozens and dozens of surveys including the widest variety of questions, with consistent respondent IDs for each survey. This means all of their surveys can be merged for all the individuals who took each survey.
The major drawback of these surveys is that they are not representative samples — so we can't really know the degree to which patterns identified in them generalize to university students as a whole. But the lack of representativeness is somewhat offset by the sheer size of the sample. Think about it this way: If you could survey 100% of the people in some population, you wouldn't much care how the sample was drawn, right? Many of the College Pulse surveys have quite impressive sample sizes, with quite a lot of them including 20,000 or more students. While this hardly approaches 100% of university students, it's more than enough to be quite interested in what these data reveal. All datasets are partial and limited, and need to be checked against other datasets with different virtues.
The wide variety of fascinating questions, and the large samples, make this an ideal, first-stab testing ground for any number of hypotheses.
The GPA of the SJW
I've long wondered if there is a relationship between attitudes toward political correctness and academic performance in the student body. In other words, are "SJWs" more or less likely to be high-performing or low-performing students? Or perhaps there is some curvilinear relationship? One could generate a few different hypotheses on this question, but for this post I will simply introduce the data (check) and share some basic descriptive statistics approaching this question. This is likely just the first of many hypotheses I hope to explore with this data over the coming weeks and months.
First, the univariate distributions require some comment. First, students in the sample seem to report questionably high GPAs. Or perhaps students are disproportionately drawn from schools with rampant grade inflation. Either way, there's something going on, because Figure 1 shows that the sample has a lot of students claiming to be nearly perfect students.
Figure 2 shows that students in this sample are quite strongly opposed to the idea of physical no-platforming. The survey item says: "A student group opposed to a controversial speaker uses physical force to prevent the speaker from speaking. In your view, the students group's actions are…" Most find it very unacceptable. Note that this is just one particular way of tapping what we might very roughly call, for shorthand, SJWism. What's great about the College Pulse survey data is that they ask a variety of different questions revolving around moralistic, speech-focused political activism, so we'll be able to triangulate with multiple variables.
Aside: One thing I'd like to do soon is a factor analysis of a few of these SJW attitudes. It would be good if we could extract the latent variable underlying, for instance, opinions toward physical no-platforming, "call outs," disinvitations, and the other related but different tendencies associated with SJWism.
One of the arguments in my book is that the hyper-moralistic political activity of the "SJW" is, in many cases, a kind of thinly veiled economic activity. But there are a few different ways this might manifest, so we need to delineate different observable implications to make specific hypotheses falsifiable.
The omni-directionality of the following hypotheses merely reflects how little we understand the SJW phenomenon.
The angry runner-up hypothesis. Because today's political economy is increasingly a "winner take all" situation, individuals who once upon a time could enjoy relatively high income and status from a "second place" finish in the capitalist game, are now looking at prospects quite beneath their relative expectations. But the types of people who land in "second place" positions are still smarter and more capable than average — so they're not just going to accept outcomes beneath their expectations, rather some of them will seek to alter the rules of the game. "If you can't beat 'em, turn over the table!" If this is the logic behind SJWism, then perhaps we would expect SJWism to be most likely in the middle of the academic performance distribution.
The shrewd winner hypothesis. Another possibility is that SJWism is a new kind of game, with emergent rules related to novel and complex socio-economic factors. Seen from this angle, SJWism might be more likely among the most intelligent and the best academic performers. If SJWism is the way to win cultural games today, and higher education is largely about signaling one's ability to win games, the best students might be most likely to become SJWs.
The brute force hypothesis. It might be the case that SJWism represents the vengeance of the intellectually dominated against the more intelligent. Seen from this angle, SJWism might be a way for the dumbest or most disorganized students to promote themselves through a kind of morally glorified brute force.
Figure 3 below shows a curvilinear relationship in which the lowest and highest levels of academic performance are associated with a slightly greater acceptance of physical no-platforming, and students in the middle of the range are least accepting. So it's not second-place students adopting SJWism to claw their way into top jobs or some such model as that (hypothesis 1). [By the way, I spoke too soon in one of my livestreams the other night; I reported this based on a too-quick look at this data, which I accidentally had backward — that will be the last time I foreshadow data-analytic findings live on Youtube before I'm actually done, sorry!] The differences here are pretty tiny, but that's in part because most students are strongly opposed to physical no-platforming, with the average level of acceptance quite low.
I was curious if Figure 3 might be a fluke related to that particular question, so I took another item tapping political correctness/SJWism to see if the same pattern holds. Figure 2 below shows that, yes, it does. The inflection point is lower on the GPA scale and the students on the bottom are not quite as PC as the best students, but again it's clearly non-linear: the best and worst students are less likely to think there's any problem with sensitivity, while the middling students are more likely to think students are too sensitive.
These could maybe represent evidence for H2 and H3, in a kind of mixed effects model: Maybe the best students adopt SJWism out of their shrewd awareness that that's indeed how to win the game of institutionalized culture, and maybe the worst students adopt SJWism to turn over the table in a game they are unlikely to succeed in. Or none of these interpretations is accurate, which is very possible.
I was also curious if the curvilinear relationship is conditional on major. In retrospect there's probably a better way to do Figure 4, but it does the trick. I restricted the data to majors that had at least 200 observations. You have to be careful to not go fishing for patterns here, because of the multiple comparisons problem. Here's one thing that seems true, though: Most of the major/gpa-level combos that contain big outliers toward SJWism are on the lower half of the GPA scale (Nursing, Law/Crim, Econ, Education, Poli Sci, Chemistry). Whereas the positive gradient toward SJWism on the high-end of the GPA scale in Figures 3 and 4 appears to reflect a slight but more steady pattern in a number of majors (Comm, CS, Econ, Engineering, Pre-Med).
I wouldn't make too much of this but it's perhaps consistent with the "mixed effects" idea above. Better students veer toward SJWism because better students perceive that PC is part of winning in education and beyond, and so they slightly and gradually report higher levels of PC moving from 3.0 to 4.0. Then the really zealous SJWs are rare occurrences drawn mostly from the lower end of academic performers, perhaps as a kind of brute force strategy. But like I said, this was just a cursory exploration to dig into some new data. Let's see what else I find in future posts before I make any big claims.