Update: To be explicit, I’m not claiming that the correlation is causal. Rather, I’m pointing out that the explosion in porn use does not seem to have led to a concomitant explosion in sex crimes, which would have been the prediction by social conservatives and radical feminists if they could have known of the extent of penetration of pornography into culture and private lives over the next 20 years in 1990.
I am almost literally one of the last of the generation of young men for whom the quest for pornography was an adventure. One could say that I had the misfortune of my adolescence overlapping almost perfectly with the last few years prior to the ‘pornographic singularity.’ I speak here of the internet, circa 1995 and later. Prior to this era of the ‘pornographic explosion’ one often had to rely upon a lax or absentee father of a friend, from whom the porn was ‘borrowed,’ and then returned with the owner none the wiser. My youngest brother, who is 15 years my junior, would no doubt find my escapades as a 15 year old bizarre in the extreme (though I believe I did not view video pornography until I was 16). In fact, I recall realizing that something radical had occurred when visiting my family and observing my brother, who was 8 at the time, deleting porn spam from his Hotmail account. Porn as nuisance rather than treasure would have amazed my adolescent self.
It seems plausible that the generation after 1995 has witnessed levels of aggregate porn consumption orders of magnitude greater than that before 1995. This is a massive natural social experiment. As with any social experiment you have anecdata-driven ‘moral panic’ pieces in the press which don’t seem to align well with what you see in the world at large. Mo Costandi pointed me today to one such piece about porn ‘re-wiring’ the brains of young boys and making them sexually dysfunctional. Standard stuff. On Twitter I pointed out to Mo semi-seriously that actually crime had declined since widespread pornographic consumption in the mid-1990s. Quite reasonably Mo inquired specifically about sex crimes. Fair enough. As it happens the FBI has records of ‘forcible rapes’ reported to the police in the USA going back to 1960.
Here they are in absolute numbers:
One thing that people occasionally mention in the comments on this weblog is that it seems futile to be “conservative” because the arrow of history goes in one direction. Even many conservatives, including myself, have fallen into this assumption. But upon a closer inspection of history I think we need to be careful about this, as the truth can sometimes confound our coarse models. For example, I strongly suspect that when it comes to love and marriage the realized element of individual liberty has not had a monotonic trajectory over human history. More plainly, free choice declined over the past 10,000 years, and has reemerged in the past few centuries. Whether this is liberal or conservative is less relevant than that it shows that attitudes, beliefs, and practices, do not always change in magnitude in one direction, only at different rates. More recently, sexual mores in the West shifted to a more puritanical direction between 1750 and 1900, only to switch back to a more relaxed attitude over the 20th century (with a punctuated shift in the 1960s).
And these sorts of trends are evident even over a shorter time scale. So it may be with attitudes toward divorce. One could argue (I probably would) that “liberal” attitudes toward divorce in the 1970s was a correction from an unsustainable equilibrium leading up to the 1960s. But over the past few decades it does look as if college educated whites have had second thoughts about the “arrow of history.” At the very least they are now more likely to stand athwart history and yell “stop.”
Below are results limited to non-Hispanic whites with college educations. Note especially the change in those with “No religions.” They seem clearly to have had enough.
The post below on teachers elicited some strange responses. Its ultimate aim was to show that teachers are not as dull as the average education major may imply to you. Instead many people were highly offended at the idea that physical education teachers may not be the sharpest tools in the shed due to their weak standardized test scores. On average. It turns out that the idea of average, and the reality of variation, is so novel that unless you elaborate in exquisite detail all the common sense qualifications, people feel the need to emphasize exceptions to the rule. For example, over at Fark:
Apparently what had happened was this: He played college football. He majored in math, minored in education. When he went to go get a job, he took it as a math teacher. When the football coach retired/quit, he took over. When funding for an advance computer class was offered, he said he could teach it after he got the certs – he easily got them within a month.
So the anecdote here is a math teacher who also coached. Obviously the primary issue happens to be physical education teachers who become math teachers! (it happened to me, and it happened to other readers apparently) In the course of double checking the previous post I found some more interesting GRE numbers. You remember the post where I analyzed and reported on GRE scores by intended graduate school concentration? It was a very popular post (for example, philosophy departments like it because it highlights that people who want to study philosophy have very strong GRE scores).
As it happens the table which I reported on is relatively coarse. ETS has a much more fine-grained set of results. Want to know how aspiring geneticists stack up against aspiring ecologists? Look no further! There are a lot of disciplines. I wanted to focus on the ones of interest to me, and I limited them to cases where the N was 100 or greater (though many of these have N’s in the thousands).
A new paper in Nature, Stepwise evolution of stable sociality in primates, was written up in The New York Times with the provocative title, Genes Play Major Role in Primate Social Behavior, Study Finds. As noted in Joan Silk’s article on the paper it should really be phylogenetics play major role in primate social behavior. The model outlined in the paper indicates that phylogenetic relationships between major primate clades is a much better predictor of social organization and structure than simple adaptation to a specific environment, or a linear increase in social organization (group size) over time. Both of these latter dynamics would also be driven by genetic changes, and therefore tie “genes” to social behavior. In other words, genes always matter, it’s just how they matter that differs. Here’s the section of the abstract of the paper of major interest:
Over at Culture of Science Sheril Kirshenbaum posts a figure from the NSF displaying what proportion of those without high school educations and those with college educations accept the scientific status of astrology. It’s pretty clear to me that this is the ASTROSCI variable from the General Social Survey. It asks:
Would you say that astrology is very scientific, sort of scientific, or not at all scientific?
It’s also nice that this question was only asked in the latter half of the 2000s. So it’s timely in terms of demographic breakdowns. Speaking of which, here are a whole host of classes and their attitudes toward astrology’s scientific status:
A new paper in Science, Differences Between Tight and Loose Cultures: A 33-Nation Study, is making the media rounds. Here’s NPR:
…The idea for this study really dates to the 1960s. Back then, an anthropologist decided to evaluate a few dozen obscure cultures and see if he could rank them on a scale from “tight” to “loose.” He defined tight cultures as having a lot of rules, which people violate at their peril. Loose cultures are more relaxed in their expectations, and more forgiving of people who deviate.
The Tightness Scale
“So for example, you might have been asked, how appropriate is it to curse in the bank or kiss in a public park, or eat or read a newspaper in a classroom? And we were able to derive scores of how constrained, in general situations, they are, versus how much they have latitude in different countries.”
“Some of the cultures that are quite tight in our sample include places like Singapore, Japan, Pakistan,” Gelfand says. “Whereas many loose societies include countries like New Zealand, the Netherlands, the United States.”
The abstract from the paper is a little harder to parse:
Our single biggest concern when examining research is publication bias, broadly construed. We wonder both (a) how many studies are done, but never published because people don’t find the results interesting or in line with what they had hoped; (b) for a given paper, how many different interpretations of the data were assembled before picking the ones that make it into the final version.
The best antidote we can think of is pre-registration of studies along the lines ofClinicalTrials.gov, a service of the U.S. National Institutes of Health. On that site, medical researchers announce their questions, hypotheses, and plans for collecting and analyzing data, and these are published before the data is collected and analyzed. If the results come out differently from what the researchers hope for, there’s then no way to hide this from a motivated investigator.
As the example of the NIH illustrates this is not just a social science problem, it is rife in any science which utilizes statistics. Statistical methods have become metrics to attain by any means necessary, when in reality they should be guidelines to get a better grasp of reality. The only solution to the problem of conscious and unconscious bias in statistical sciences seems to me to be radical transparency of some sort. There’s a fair amount of science ethnography which suggests that how science is done departs greatly from the clean and rational enterprise which one might presume based on the final product. The only way to clean up some of the natural human bias in the enterprise is to shed some light on it.
One of the weird things I randomly noticed when querying the “TRUST” variable in the GSS was that men were more trusting than women. I didn’t think much of that, but take a look at this logistic regression:
|Trust in people, sample from after the year 2000|
|Pseduo R-square = 0.096||Pseduo R-square = 0.083|
The outcomes are “can trust people = 1″ and “cannot trust people = 0.” I removed “depends” (which is never more than 5-10% in a class anyway). For sex 1 = male and 2 = female, so you can immediately see that being a woman will reduce the odds of being trusting. WORDSUM, vocabulary score, and educational attainment go in the direction you’d expect. Interestingly controlling for education doesn’t remove the vocabulary effect. COHORT is the year you were born. Lower values indicate older individuals in the data set. Younger people are less trusting, so this makes sense. To my surprise on the individual level religion doesn’t seem that important.
Since the sample sizes for sex are huge I thought I’d compare sex differences in trust over the years by demographic variable.
The original robots
We are haunted by Hamilton. William D. Hamilton specifically, an evolutionary biologist who died before his time in 2000. We are haunted because debates about his ideas are still roiling the intellectual world over a decade after his passing. Last summer there was an enormous controversy over a paper which purported to refute the relevance of standard kin selection theory. You can find out more about the debate in this Boston Globe article, Where does good come from? If you peruse the blogosphere you’ll get a more one-sided treatment. So fair warning (I probably agree more with the loud side which dominates the blogosphere for what it’s worth on the science).
What was Hamilton’s big idea? In short he proposed to tackle the problem of altruism in social organisms. The biographical back story here is very rich. You can hear that story from the “horse’s mouth” in the autobiographical sketches which Hamilton wrote up for his series of books of collected papers, Narrow Roads of Gene Land: Evolution of Social Behaviour and Narrow Roads of Gene Land: Evolution of Sex. For the purposes of the issue at hand the first volume is obviously more important, but the second volume has an enormous amount of personally illuminating material because of Hamilton’s untimely passing in 2000 before it could be edited. In Ullica Segerstrale’s Defenders of the Truth and Oren Harman’s The Price of Altruism Hamilton looms large as a major secondary character in the narrative. The Altruism Equation, A Reason for Everything, and The Darwin Wars, all give him extensive treatment, both his scientific ideas and relevant biographical context. Hamilton’s scientific influence on Richard Dawkins was enormous. There are nearly fifty references to him in both The Selfish Gene and The Extended Phenotype. In writing his obituary Dawkins began: “W. D. Hamilton is a good candidate for the title of most distinguished Darwinian since Darwin.”
In terms of the details of his science, Hamilton proposed that genetic relatedness between individuals can explain altruism within groups. In this way Hamilton reduced a phenomenon which had often been explained as a group-level one (e.g., “for the good of the species”) to an individual-level one (e.g., “for the good of the individual/gene”). According to Hamilton when he was a young scientist in the early 1960s most people did not perceive this problem to be a problem at all, and he had difficulty finding support for this line of research, and was in fact warned off it by his superiors. The end culmination of those early years of lonely introspection were two dense, abstruse, and difficult papers (in part due to their peculiar notation), The genetical evolution of social behaviour – I and The genetical evolution of social behaviour – II. But the basic heuristic at the heart of these papers was condensed earlier in a short essay in The American Naturalist as Hamilton’s Rule:
rB > C or rB – C > 0
First, if it is clear that you haven’t read the post itself and leave a comment I won’t just not publish it, but I’ll ban you. Second, if you complain about this in the comments, I’ll ban you too. Now that you feel appropriately welcome, I want to explore some of the issues beneath Chris Mooney’s post, Vaccine Denial and the Left:
So I want to further explain my assertion that vaccine denial “largely occupies” the political left. It arises, basically, from my long familiarity with this issue, having read numerous books about it, etc.
First, it is certainly true that environmentalists and Hollywood celebrities have been the loudest proponents of anti-vaccine views. To me, that is evidence, although not necessarily definitive. So is the fact that we see dangerously large clusters of the unvaccinated in places like Ashland, Oregon, and Boulder, Colorado, which are very leftwing cities.
What’s tricky is, there’s not a standard left-right political ideology underlying this. Rather, it seems more associated with a Whole Foods and au natural lifestyle that, while certainly more prominent on the bicoastal left, isn’t the same as being outraged by inequality or abuses of the free market.
This is a tricky issue. There is a stereotype that liberals who reject religion tend to gravitate toward New Age/environmentalist spirituality. “The mind abhors a vacuum” model. I used to accept this, but if you poke around the General Social Survey the reality is more complicated. For example, you can look up attitudes toward genetically modified food and astrology. The results don’t fall neatly into a Left-Right dichotomy. Part of the issue is that there has been aggregation of distinct groups into on catchall category. Consider me. I identify as a conservative, which would indicate a far higher odds of me being a Creationist, but I’m clearly not.
There aren’t any questions about vaccination in the General Social Survey, but there are several about trust and faith in science, or lack thereof. First I pruned all of the questions which were before 1998. So the results below are for the 2000s by and large. After that I had a set of variables to play with, to serve as replicates in terms of observing trends. Below are three tables with my results.
Table #1 is just a set of results which shows how political ideology, party identification, and educational attainment, correlate with attitudes toward science. So in that table the columns add up to 100%. So below 4% of liberals strongly agree while the assertion that “we trust too much in science,” and 21% strongly disagree.
The second table is limited to self-identified liberals. I wanted to query how attitudes toward science vary by demographic among liberals. In this case the rows add up to 100% on the margin (rotated from the first table). So in terms of those who strongly agree that we trust too much in science, 29% are male and 71% female, among self-identified liberals. Remember that in some classes there won’t be a 50/50 breakdown, so look for the variation in relative trends.
Finally, for the third table I have a regression. I now divided the sample into liberal and conservative groups, and ran a set of variables to predict opinions on the questions which I’ve covered so far. The first row has the R-squared, the magnitude of which illustrates how much the listed variables predict variation on the question. Subsequent rows have beta values for the variables, which indicate the direction and magnitude of the effect from that given variable. The questions are all easily numerical, or recoded as numerical (e.g., atheist, agnostic…to total belief in God is 1, 2…6). To get an intuition as to what’s going on, just look at each variable and its value. Those which are bold are statistically significant at p = 0.05. For example, among liberals confidence in belief in god seems to decrease trust in science. Socioeconomic status seems to increase it.
Please note that I’ve omitted some categories for variables where the sample size is too small, so some rows/columns may be less than 100% (e.g., Jews in “religion”). Additionally I’ve removed some response classes where N < 25, as the noise can confuse the trend line.
In a rumination on the “Tiger mom” phenomenon, Andrew Gelman suggests:
…Back when I taught at Berkeley and it was considered the #1 statistics department, a lot of my tenured colleagues seemed to have the attitude that their highest achievement in live was becoming a Berkeley statistics professor. Some of them spent decades doing mediocre work, but it didn’t seem to matter to them. After all, they were Tenured at Berkeley. Now, I’m not saying Chua is like that–in writing this book, she’s certainly not coasting on her academic reputation–but I do think it’s natural for someone in her position to define her success based on where she stands in the academic pecking order (and, for that matter, a best-selling popular book will help here too) rather than on her accomplishments for their own sake.
That is an unfortunate, and frankly, scary side effect of the way meritocracy sometimes works. Some people fixate more on the proxy measures than the underlying variable which it is intended to measure. I immediately recall two close friends who were going to graduate school M.I.T. and Harvard at the same time, and by an unfortunate coincidence they made the same complaints about their advisors: that once these academics had reached their ultimate goal, they lost all sense of purpose, and simply decided to glide along after tenure. Status, not substantive contribution, turned out to be their ultimate motivation (one of my friends complained that his advisor had transformed himself into an extremely devoted family man after his reputation had reached its maximal value and there was no status return on labor investment!). No one could take away their positions as tenured faculty at M.I.T. and Harvard, and that was enough.
I think this is connected to this Slate piece, Mary Gates and Karen Zuckerberg Weren’t Tiger Moms: Is the Amy Chua approach bad for the American economy?:
A new article in The New York Times, Social Scientist Sees Bias Within, profiles Jonathan Haidt’s quest to get some political diversity within social psychology. This means my post Is the Academy liberal?, is getting some links again. The data within that post is just a quantitative take on what anyone knows: the academy is by and large a redoubt of political liberals. To the left you see the ratio of liberals to conservatives for selected disciplines. Haidt points out that in the American public the ratio is 1:2 in the other direction, so it would be 0.50. He goes on to say that: “Anywhere in the world that social psychologists see women or minorities underrepresented by a factor of two or three, our minds jump to discrimination as the explanation,” said Dr. Haidt, who called himself a longtime liberal turned centrist. “But when we find out that conservatives are underrepresented among us by a factor of more than 100, suddenly everyone finds it quite easy to generate alternate explanations.” Haidt now calls himself a “centrist,” but you define yourself in part by the distribution around you. In the general public he’d probably still be a liberal, as evidenced by the logic he’s using here. The proportionalist idea is so common the Left, that institutions and communities should reflect the broader society, that he’s now attempting to apply the framework to ideology. But there may be many reasons not having to do with crass discrimination why different groups are differently represented in different disciplines. Consider this case:
- Academics tend to be much smarter than average, and liberals may be overrepresented among the very bright. That to me could explain why education professors are more conservative, though I doubt political scientists are that much brighter than engineers!
- Liberals and conservatives have different values, so that people of similar aptitudes may choose different life paths. The standard assumption is that conservatives value the remuneration of the conventional private sector more than liberals, who may opt for the prestige and status of the academy.
- Studying social science may make you liberal, in that conservative ideas are just not correct.
- Finally, subcultures are probably subject to positive feedback loops where small initial differences may result in disproportionate attraction of various types of individuals to different groups. After the initial positive feedback loop is generated, i.e. bright liberal undergraduates know that graduate school is socially congenial to their values, while conservatives know that it is not, group conformity effects can make the politically “out” reminder more liberal or conservative than they would otherwise be (as an inverse case is Wall Street, where may people from conventional liberal backgrounds may still identify as relatively liberal, but on many issues their environment has shifted their absolute viewpoints to a more right-wing position).
Not only do I think there are reasons not having to do with straightforward discrimination as to the skewed ratios, but, I think that barring a Ministry of Conservative Representation enforcing quotas from on high it’s pretty much impossible to change the basic statistics. You could, for example, simply mandate that conservatives get paid 50% more to incentivize them to becoming academics. But why stop here? How about more liberals in the military and corporate boardrooms?
Does this matter? I think it does. “Positive” Results Increase Down the Hierarchy of the Sciences:
One of the major parameters which shape individual success, and macroeconomic growth in the aggregate, is time preference. Time preference basically measures an individual’s future-time orientation. Would you for example take $1,000 in the present, or wait 30 days and accept $1,500 dollars? It doesn’t need to be money, children can exhibit time preference as well. Would you like one candy bar now? Or two candy bars in an hour? I also think time preference permeates our lives more concretely. Would you like to eat some greasy food now, or would you forgo epicurean pleasures in the present for a sleeker frame in the future?
Here’s an illustration of the correlates of time preference:
In one of the most amazing developmental studies ever conducted, Walter Michel of Stanford created a simple test of the ability of four year old children to control impulses and delay gratification. Children were taken one at a time into a room with a one-way mirror. They were shown a marshmallow. The experimenter told them he had to leave and that they could have the marshmallow right then, but if they waited for the experimenter to return from an errand, they could have two marshmallows. One marshmallow was left on a table in front of them. Some children grabbed the available marshmallow within seconds of the experimenter leaving. Others waited up to twenty minutes for the experimenter to return. In a follow-up study (Shoda, Mischel, & Peake, 1990), children were tested at 18 years of age and comparisons were made between the third of the children who grabbed the marshmallow (the “impulsive”) and the third who delayed gratification in order to receive the enhanced reward (“impulse controlled”).
The third of the children who were most impulsive at four years of age scored an average of 524 verbal and 528 math. The impulse controlled students who scored 610 verbal and 652 math! This astounding 210 point total score difference on the SAT was predicted on the basis of a single observation at four years of age! The 210 point difference is as large as the average differences between that of economically advantaged versus disadvantaged children and is larger than the difference between children from families with graduate degrees versus children whose parents did not finish high school! At four years of age gobbling a marshmallow now v. waiting for two later is twice as good a predictor of later SAT scores than is IQ.
The issue of causality is probably one which you will immediately bring up. There is a correlation between higher IQ and low time preference (consuming less in the present to have a potential for more consumption in the future), but who knows how the feedback loops here work? For example, unlike many males my age I gave up playing video games around the age of 16. I calculated that I was substituting video games for reading, and that that would have long term consequences which I was not pleased with. Video games were very pleasurable in the short term, addictive even. But I decided that there simply were not enough hours in the day that I could do everything I needed to do, so I stopped playing them (I am aware that many, many, very smart people are avid video game enthusiasts. I’m just using it to illustrate the trade offs one might make). How much less erudite, as Dr. Dan MacArthur might say, would I be if I did continue to expend many hours per week on video games?
A new working paper on the SSRN website has some interesting data on time preference cross-culturally. How Time Preferences Differ: Evidence from 45 Countries:
About six months ago I read a history of modern Italy and was struck by a passage which observed that during the early years of the Italian state none of the prominent political leaders were practicing Roman Catholics. Part of this was specific to the history of the rise of modern Italy, Umberto I fought the Papacy, and so alienated the institution of the Church from the royal house and the state over which it ruled. But more generally many of the nationalists of the 19th century in Catholic Europe were of an anti-clerical bent. Only with the reconciliation of the Roman Catholic Church with the modern liberal democratic nation-state in the 20th century, and universal suffrage, have the political elites come to resemble the populace more in their religious sensibilities in these nations. And before you dismiss this as a European matter, observe that Andrew Jackson, our sixth president, was the first to have personal religious views in line with the American majority. As late as William Howard Taft in the early 20th century the United States had a head of state who rejected orthodox Christianity (he was a Unitarian Christian). Can we imagine that such a thing would come to pass without much controversy today? Mitt Romney has famously had to elide the yawning chasm between Mormonism and Nicene Christianity to be a viable candidate.
The point I’m trying to make here is that the paths of the arrows of history are more complex than we perceive them in our own moment in time. It is ironic that we in the United States are living through a period of secularization at the grassroots, while at the same time having to deal with the fact that all high level politicians have to pass through a de facto religious litmus test of relatively stringent orthodoxy. The complexity of this sort of social phenomenon makes it exceedingly difficult to analyze and characterize in a pithy fashion. Too often when scholars and intellectuals speak of the history of religion they impose their own visions on the flux of human belief and behavior. Eric Kaufmann’s Shall the Religious Inherit the Earth is not such an argument. Rather, it is a cautious work which makes recourse to both robust theoretical models as well as a wide and rich set of empirical data. Kaufmann casts a very wide net in his attempt to retrieve a useful catch in terms of plausible and robust predictions. The central idea of the book is derived from the fact that the endogenous growth rates of religious segments of developed societies can often be rather high. The broader implication is that history moves in cycles, and that the current age of secularism is nearing its peak, and inevitable demographic forces will see the tide retreat.
A quick follow-up to my previous post which points to the data that women tend to be more race-conscious in dating than men. There’s a variable in the GSS which asks if you support a ban on interracial marriage, RACMAR. Here’s the question itself:
Do you think there should be laws against marriages between (Negroes/Blacks/African-Americans) and whites?
There isn’t much surprising in the results for this variable. It was asked between 1972 and 2002, and support for a ban on interracial marriages dropped over time. Whites, old people, conservatives, and less educated people, tended to support these bans, as well as Southerners. But what about men vs. women? I’ve never actually looked at that. I limited the sample to whites; the number of blacks in the sample is small and wouldn’t alter the result, but I figured I’d control for race anyway. Support for such laws is in the 35-40% range for whites in 1972, before dropping off to 5-15% in 2002.
Here’s the trendline broken down by sex:
The results are striking. An African-American man would have to earn $154,000 more than a white man in order for a white woman to prefer him. A Hispanic man would need to earn $77,000 more than a white man, and Asian man would need, remarkably, an additional $247,000 in additional annual income.
So do women value ethnicity over income in a mate? They certainly seem too. If income was the more important factor in mate choice these numbers would be small; it would take very little additional income to entice a woman to date a man of a different race. The fact that the numbers are so large suggests that a man’s race is significantly more important that his income.
And men? Well the problem is that men don’t seem to care about income at all. So even though their behaviour suggests they care less about their partner’s race than women do, the income needed to encourage them to make the trade-off between races is incalculably large. To really estimate how much men care about race you would have to find a different measure, like perhaps physical beauty.
First, there has been research controlling for physical beauty. So the white male disinclination toward black females can be accounted for mostly by the fact that they aren’t as physically attracted to them. When you limit the sample of black women to those which they are physically attracted to the discrepancy mostly disappears. In contrast, when you similarly constrain the samples of black men which white women judge as attractive the discrepancy in dating preference remains (the same when you do so for Asian men).
All this is not new. I blogged this two years ago, and have gotten bored with the topic (there a regular series of papers which confirm the finding in different circumstances). The sex difference in race preference in the dating literature seems relatively robust. Women care about the race of their partners far more than men, all things equal (in fact, much of the literature suggests men are not concerned about race very much when you control for other background variables). If a site brands itself as “Big Think”, it would be nice to add some value.
Interesting post by Gretchen Reynolds reviewing the evidence on exercise and intelligence. The title is “Phys Ed: Can Exercise Make Kids Smarter?”, so this is definitely seen as something which is “actionable” in a public policy sense, especially in light of the increases in obesity among young people. Intuitively I think most people are going to agree with this in the United States. In fact, when you’re down with the flu or some other illness you are generally less productive (most of the films I’ve watched over the past three years have been when I’m ill since I can’t focus on difficult material), so there’s probably going to be a natural connection made between greater cognitive function with greater health.
First, Reynolds points to a study which shows that:
1) The most fit children are more intelligent than the least fit as adduced from psychometric tests
2) The most fit children ‘had significantly larger basal ganglia, a key part of the brain that aids in maintaining attention and “executive control,” or the ability to coordinate actions and thoughts crisply.’ The researchers controlled for socioeconomic status and body mass index,
A second study indicated that the fit children had better working memory and greater hippocampal volume. Finally, an earlier study using data from Swedish conscripts showed that even among identical twins the fitter ones were more intelligent. Note that the primary author was the same on the first two studies. Before commenting further how about looking at some tables and/or figures from the papers?
Update: The title is way too strong as a reflection of my opinion. I’ve added a question mark.
A friend once observed that you can’t have engineering without science, making the whole concept of “social engineering” somewhat farcical. Jim Manzi has an article in City Journal which reviews the checkered history of scientific methods as applied to humanity, What Social Science Does—and Doesn’t—Know: Our scientific ignorance of the human condition remains profound.
Poking around the GSS for another reason I stumbled onto something weird. Something which I’d seen hints of, or seen referred to before, but never followed up myself. It seems that support for abortion-on-demand and the death penalty peaked concurrently in the span between 1980-2000. This is evident in two GSS variables, ABANY and CAPPUN, which ask if you support a woman’s right to an abortion for any reason and the death penalty for murder. Additionally, I decided to look at attitudes toward homosexuality using HOMOSEX as a reference as a point of contrast. Unlike abortion or the death penalty attitudes toward homosexuality have been changing in the same direction for the past 30 years. Additionally, the magnitude of the change seems to be much greater than in regards to the other two controversial social issues, and especially abortion, which has exhibited notable stability.
I was particularly interested in differences by religion, so I limited the sample to whites and broke it down by Protestant, Catholic, Jew and None. To reduce sample size volatility I clustered by decade, so that “1970s” is inclusive of every year in the 1970s that the GSS asked the question for that variable.