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John von Neumann

About a month back a researcher at Yale published survey results which showed that Tea Party members exhibited more science knowledge than the general public, somewhat to his chagrin. I wasn’t particularly surprised, because the knowledge of science as it relates to political ideology is somewhat complex. Often the right-leaning get lower marks because of strong reactions to questions perceived to be ideological. It’s a rather robust finding that the more intelligent are more ideological, so it is no surprise that a group like the Tea Party would do better on tests which measure underlying cognitive orientation.

This was brought back to my mind by a new piece in The Atlantic which had a “Slate-pitch” sort of title: The Republican Party Isn’t Really the Anti-Science Party. There was some comment on Creationism in the piece, so I wanted to review the data on this mostly ideologically freighted of the standard science questions asked of the public. To do this I used the General Social Survey. To limit demographic confounds I constrained the samples to non-Hispanic whites who responded 2006-2012 (“Selection Filter(s): Race1(1) Hispanic(1)”). Additionally, I partitioned the data into two classes, non-college and college-educated (“Degree(r:0-2;3-4)”). Then I looked at political party identification and ideology (“Partyid” and “Polviews(r:1-2;3;4;5;6-7)”).

 

Agree: “Human beings, as we know them today, developed from earlier species of animals.”
Non-college College-educated
Strong Dem 56 88
Dem 54 79
Lean Dem 60 86
Independent 55 70
Lean Repub 44 56
Repub 37 56
Strong Repub 27 41
Liberal 69 94
Slightly Liberal 61 83
Moderate 52 71
Slightly Conserv. 47 65
Conservative 25 35

As someone with a professional fixation upon evolution and a lean toward conservative political viewpoints, obviously these results are disturbing to me. But they are what they are. The typical run of the mill Ph.D. scientist disagrees with the Right here rather strongly. I think the attitude toward evolution specifically is a major symbolic marker which alienates scientists as a demographic from anything to do with Republicans or conservatism, and vice versa. Though there are presumably normative implication in evolutionary, the primary disagreement here is basically on very long established and orthodox science.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: General Social Survey, Social Science 
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Less than even two! Image credit: Yoshi Canopus

A few years ago Greg Cochran mentioned to me how he perceives the two child family to be the new bourgeois normal, enforced by the professional class and blue-haired ladies alike (this impression is informed by the fact that he has more than two children). This seems to align with my own general sense, but then again how normal is my socioeconomic milieu? So I decided to look at the General Social Survey. I limited the sample to non-Hispanics whites age 45 and over, constrained to the interval 2000-2012,* and broke the data into male and female classes. I crossed the number of children, binned 0, 1, 2, 3, 4, and 5+, with the highest educational attainment of the individual.** In other words I limited the data set, and looked at how the number of children of individuals varied as a function of education.


For males the sample sizes were ~432 with no high school degree, ~1,592 high school degree, ~226 junior college, ~618 bachelor’s degree, and ~461 with graduate educations, for a total of ~3,329.*** The equivalent numbers for females were ~452, ~2,124, ~300, ~628, ~434, and ~3,939.

The results below:

Nothing too surprising. It seems that non-Hispanic white women without high school educations are particularly fecund (or perhaps they don’t have high school educations because of their fecundity?)

 

* Selection Filter(s): age(45-*) year(2000-*) race(1) hispanic(1)

** Row, childs(r:0;1;2;3;4;5-*), column, degree

*** The ~ is due to the fact that they’re weighted N’s.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Fertility, Social Science 
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The food equivalent of a Malcolm Gladwell book, credit, Larry A. Moore

Several years ago I had an email exchange with Christopher Chabris, the author of The Invisible Gorilla. I half-joked that it should have been retitled “Why Malcolm Gladwell Is Wrong.” Chabris replied with a “no comment.” That was probably politic; Chabris is a serious academic, while Gladwell runs a vast pop-social science empire of sorts. But in a new piece in The Wall Street Journal reviewing Gladwell’s new book, David and Goliath: Underdogs, Misfits, and the Art of Battling Giants, Chabris pretty much goes for it in terms of saying what many academics think privately.

You can get an ungated version if you go through Google News.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Social Science 
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Google’s Ngrams viewer yields some interesting results when you query the mentions of various fields within genetics over the past century or so. Nothing too surprising, though I would have thought that molecular genetics would have surpassed population genetics even earlier than it did.

Click To Enlarge

Note that the default settings go to 2000. But I was curious about genomics’ trajectory, and I pushed it to the max (2008). The qualitative result was not a surprise to me, but the magnitude did take me aback:

Click To Enlarge

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Genetics, Social Science 
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Credit: Plp

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:


And now standardized by the populations of the decennial Census (and per 1,000,000):

The problem, from what I can see, is that the only young males who talk at length about their porn consumption to professionals and the media are those who have problems with that consumption. In contrast, for most men the consumption of porn isn’t a major issue, it’s just part of their life, or not, depending on the situation, and at most it comes up in a humorous manner. Additionally, my own suspicion is that the perversity of online pornography is driven by the fact that perverts are disproportionately represented among the small minority of men who pay for porn in this day and age.

On a more scientific note, some of the fears of porn destroying the male ability and inclination to have sex with women* could be alleviated if people were more aware of the concept of an alief. One can illustrate the relationship of an alief to sex rather easily. Imagine that you, a heterosexual male (if you aren’t a heterosexual male, just put yourself in that individual’s position), meet a very attractive woman at a party, and kiss her and touch her breasts. You are likely rather aroused and excited at this point. You then reach down and feel a penis. Now you are probably quite turned off. Can you appreciate that you were excited literally the moment before? Would you wish to repeat the experience of initial pleasure, and then shock?

The key takeaway is that a major part of the pleasure of an experience is the broader contextual framework in which the pleasure is occurring. Kissing a woman is preferable for a heterosexual man not just because a woman has smooth skin, and attractive facial features, but because the target of their affections is a woman. If that woman turns out to be a very feminine “ladyboy,” then all the pleasure disappears, even if in an objective and reductionist sense nothing has changed about the previous experiences (if you want a deeper exploration of this topic, I recommend Paul Bloom’s How Pleasure Works: The New Science of Why We Like What We Like).

Obviously sex is a somewhat mechanical operation for many males. Ergo, the ease with which males can relieve themselves with masturbation. But you can’t just transpose the mechanics of consuming pornography to the mechanics of sex with a real woman. Porn exists to facilitate masturbation, but so does your hand. Ultimately a woman is preferable to your hand because a woman is a woman, and your hand is just your hand.**

In other words, the modern male, porn-consuming though he might be, still generally prefers sex with real live women. We’re born that way.

* From what I can tell pornography has more mainstream acceptance in the gay male community. And yet to my knowledge gay males are no less interested in sex than straight males.

** I’m stripping away the reality that sex within a relationship is more than arousal and climax, but an essential part of the relationship being more than just a friendship.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Pornography, Social Science, Sociology 
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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.


Attitudes toward divorce laws:

1970s 1980s 1990s 2000s
Born before 1946 Easier 35 19 18 15
More Difficult 40 52 54 50
Stay Same 25 28 28 35
Born 1946-1964 Easier 43 22 20 18
More Difficult 31 48 50 47
Stay Same 26 31 30 35
Born after 1965 Easier * * 16 17
More Difficult * * 53 52
Stay Same * * 32 31
Liberals Easier 49 27 26 26
More Difficult 26 40 35 32
Stay Same 26 33 39 42
Moderates Easier 36 23 19 17
More Difficult 33 51 51 47
Stay Same 30 27 30 36
Conservatives Easier 26 16 14 9
More Difficult 52 57 65 65
Stay Same 21 27 21 26
Protestant Easier 32 18 14 11
More Difficult 42 56 60 58
Stay Same 26 26 26 31
Catholic Easier 29 19 18 15
More Difficult 45 54 55 53
Stay Same 26 27 27 32
No Religion Easier 63 35 32 28
More Difficult 14 18 26 28
Stay Same 22 47 42 44
1986 index income <$20,000 Easier 36 18 20 16
More Difficult 40 56 51 46
Stay Same 24 26 29 38
1986 index income $20,000-$50,000 Easier 37 21 19 16
More Difficult 37 49 54 55
Stay Same 26 30 28 29
1986 index income $50,000> Easier 39 22 20 18
More Difficult 36 47 49 46
Stay Same 25 31 32 36

All results computed from the GSS

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Divorce, Social Science 
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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).

You’re going to have to click the image to make out where the different disciplines are. But wait! First I need to tell you what I did. I looked at the average verbal and mathematical score for each discipline. Then I converted them to standard deviation units away from the mean. This is useful because there’s an unfortunate compression and inflation on the mathematical scores. Disciplines which are stronger in math are going to have a greater average because the math averages are higher all around. You can see that I divided the chart into quadrants. There are no great surprises. People who want to pursue a doctorate in physical education are in the bottom left quadrant. Sorry. As in my previous post physicists, economists, and philosophers do rather well. But there were some surprises at the more detailed scale. Historians of science, and those graduate students who wish to pursue classics or classical languages are very bright. Budding historians of science have a relatively balanced intellectual profile, and the strongest writing scores of any group except for philosophers. I think I know why: many of these individuals have a science background, but later became interested in history. They are by nature relatively broad generalists. I have no idea why people drawn to traditionally classical fields are bright, but I wonder if it is because these are not “sexy” domains, to the point where you have to have a proactive interest in the intellectual enterprise.

I also wanted to compare aggregate smarts to intellectual balance. In the plot to the right on the x-axis you have the combined value of math and verbal scores in standard deviation units. A negative value indicates lower values combined, and a positive value higher. Obviously though you can have a case where two disciplines have the same average, but the individual scores differ a lot. So I wanted to compare that with the difference between the two scores. You can see then in the plot that disciplines like classics are much more verbal, while engineering is more mathematical. Physical scientists tend to be more balanced and brighter than engineers. Interestingly linguists have a different profile than other social scientists, and cognitive psych people don’t cluster with others in their broader field. Economists are rather like duller physicists. Which makes sense since many economists are washed out or bored physicists. And political science and international relations people don’t stack up very well against the economists. Perhaps this is the source of the problem whereby economists think they’re smarter than they are? Some humility might be instilled if economics was always put in the same building as physics.

In regards to my own field of interest, the biological sciences, not too many surprises. As you should expect biologists are not as smart as physicists or chemists, but there seems to be two clusters, with a quant and verbal bias. This somewhat surprised me. I didn’t expect ecology to be more verbal than genetics! And much respect to the neuroscience people, they’re definitely the smartest biologists in this data set (unless you count biophysicists!). I think that points to the fact that neuroscience is sucking up a lot of talent right now.

The main caution I would offer is that converting to standard deviation units probably means that I underweighted the mathematical fields in their aptitudes, because such a large fraction max out at a perfect 800. That means you can’t get the full range of the distribution and impose an artificial ceiling. In any case, the raw data in the table below. SDU = standard deviation units.

 

Field V-mean M-mean V-SDU M-SDU Average-SDU Difference-SDU
Anatomy 443 568 -0.16 -0.11 -0.13 -0.05
Biochemistry 486 669 0.20 0.56 0.38 -0.36
Biology 477 606 0.13 0.15 0.14 -0.02
Biophysics 523 727 0.51 0.95 0.73 -0.43
Botany 513 626 0.43 0.28 0.35 0.15
Cell & Mol Bio 497 658 0.29 0.49 0.39 -0.20
Ecology 535 638 0.61 0.36 0.49 0.26
Develop Bio 490 623 0.24 0.26 0.25 -0.02
Entomology 505 606 0.36 0.15 0.25 0.22
Genetics 496 651 0.29 0.44 0.36 -0.16
Marine Biology 499 611 0.31 0.18 0.24 0.13
Microbiology 482 615 0.17 0.21 0.19 -0.04
Neuroscience 533 665 0.60 0.54 0.57 0.06
Nutrition 432 542 -0.25 -0.28 -0.27 0.03
Pathology 468 594 0.05 0.07 0.06 -0.02
Pharmacology 429 634 -0.28 0.33 0.03 -0.61
Physiology 464 606 0.02 0.15 0.08 -0.13
Toxicology 465 610 0.03 0.17 0.10 -0.15
Zoology 505 609 0.36 0.17 0.26 0.20
Other Biology 473 626 0.09 0.28 0.19 -0.19
Chemistry, Gen 483 681 0.18 0.64 0.41 -0.47
Chemistry, Analytical 464 652 0.02 0.45 0.23 -0.43
Chemistry, Inorganic 502 690 0.34 0.70 0.52 -0.37
Chemistry, Organic 490 683 0.24 0.66 0.45 -0.42
Chemistry, Pharm 429 647 -0.28 0.42 0.07 -0.69
Chemistry, Physical 513 708 0.43 0.82 0.62 -0.39
Chemistry, Other 477 659 0.13 0.50 0.31 -0.37
Computer Programming 407 681 -0.46 0.64 0.09 -1.10
Computer Science 453 702 -0.08 0.78 0.35 -0.86
Information Science 446 621 -0.13 0.25 0.06 -0.38
Atmospheric Science 490 673 0.24 0.59 0.41 -0.35
Environ Science 493 615 0.26 0.21 0.23 0.06
Geochemistry 514 657 0.44 0.48 0.46 -0.05
Geology 495 625 0.28 0.27 0.27 0.01
Geophysics 487 676 0.21 0.61 0.41 -0.40
Paleontology 531 621 0.58 0.25 0.41 0.33
Meteology 470 663 0.07 0.52 0.30 -0.46
Epidemiology 485 610 0.19 0.17 0.18 0.02
Immunology 492 662 0.25 0.52 0.38 -0.26
Nursing 452 531 -0.08 -0.35 -0.22 0.27
Actuarial Science 460 726 -0.02 0.94 0.46 -0.96
Applied Math 487 730 0.21 0.97 0.59 -0.76
Mathematics 523 740 0.51 1.03 0.77 -0.52
Probability & Stats 486 728 0.20 0.95 0.58 -0.75
Math, Other 474 715 0.10 0.87 0.48 -0.77
Astronomy 525 706 0.53 0.81 0.67 -0.28
Astrophysics 540 727 0.66 0.95 0.80 -0.29
Atomic Physics 522 739 0.50 1.03 0.77 -0.52
Nuclear Physicsl 506 715 0.37 0.87 0.62 -0.50
Optics 495 729 0.28 0.96 0.62 -0.68
Physics 540 743 0.66 1.05 0.85 -0.40
Planetary Science 545 694 0.70 0.73 0.71 -0.03
Solid State Physics 514 743 0.44 1.05 0.74 -0.62
Physics, Other 519 723 0.48 0.92 0.70 -0.44
Chemical Engineering 490 729 0.24 0.96 0.60 -0.72
Civil Engineering 456 705 -0.05 0.80 0.38 -0.85
Computer Engineering 465 716 0.03 0.87 0.45 -0.85
Electrical Engineering 465 722 0.03 0.91 0.47 -0.89
Industrial Engineering 426 699 -0.30 0.76 0.23 -1.06
Operations Research 483 743 0.18 1.05 0.61 -0.88
Materials Science 509 728 0.39 0.95 0.67 -0.56
Mechanical Engineering 471 721 0.08 0.91 0.49 -0.83
Aerospace Engineering 498 725 0.30 0.93 0.62 -0.63
Biomedical Engineering 504 717 0.35 0.88 0.62 -0.53
Nuclear Engineering 500 720 0.32 0.90 0.61 -0.58
Petroleum Engineering 414 676 -0.40 0.61 0.10 -1.01
Anthropology 532 562 0.59 -0.15 0.22 0.73
Economics 508 707 0.39 0.81 0.60 -0.43
International Relations 531 588 0.58 0.03 0.30 0.55
Political Science 523 574 0.51 -0.07 0.22 0.58
Clinical Psychology 484 554 0.18 -0.20 -0.01 0.38
Cognitive Psychology 532 627 0.59 0.28 0.44 0.30
Community Psychology 441 493 -0.18 -0.60 -0.39 0.43
Counseling Psychology 444 500 -0.15 -0.56 -0.35 0.41
Developmental Psychology 476 563 0.12 -0.14 -0.01 0.26
Psychology 476 546 0.12 -0.25 -0.07 0.37
Quantitative Psychology 515 629 0.45 0.30 0.37 0.15
Social Psychology 518 594 0.47 0.07 0.27 0.40
Sociology 490 541 0.24 -0.28 -0.02 0.52
Criminal Justice/Criminology 418 477 -0.37 -0.71 -0.54 0.34
Art history 536 549 0.62 -0.23 0.20 0.85
Music History 536 596 0.62 0.08 0.35 0.54
Drama 514 541 0.44 -0.28 0.08 0.72
Music History 490 559 0.24 -0.17 0.03 0.40
Creative Writing 553 540 0.76 -0.29 0.24 1.06
Classical Language 619 633 1.32 0.32 0.82 0.99
Russian 584 611 1.03 0.18 0.60 0.85
American History 533 541 0.60 -0.28 0.16 0.88
European History 554 555 0.77 -0.19 0.29 0.97
History of Science 596 661 1.13 0.51 0.82 0.62
Philosophy 591 630 1.08 0.30 0.69 0.78
Classics 609 616 1.24 0.21 0.72 1.02
Comp Lit 591 588 1.08 0.03 0.56 1.06
Linguistics 566 630 0.87 0.30 0.59 0.57
Elementary Education 438 520 -0.20 -0.42 -0.31 0.22
Early Childhood Education 420 497 -0.35 -0.58 -0.46 0.22
Secondary Education 484 576 0.18 -0.05 0.07 0.24
Special Education 424 497 -0.32 -0.58 -0.45 0.26
Physical Education 389 487 -0.61 -0.64 -0.63 0.03
Finance 466 721 0.03 0.91 0.47 -0.87
Business Adminstraiton 434 570 -0.24 -0.09 -0.16 -0.14
Communication 458 517 -0.03 -0.44 -0.24 0.41
Theology 537 583 0.63 -0.01 0.31 0.64
Social Work 428 463 -0.29 -0.80 -0.54 0.52
(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data Analysis, GRE, Intelligence, Social Science 
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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:

… Here we present a model of primate social evolution, whereby sociality progresses from solitary foraging individuals directly to large multi-male/multi-female aggregations (approximately 52 million years (Myr) ago), with pair-living (approximately 16 Myr ago) or single-male harem systems (approximately 16 Myr ago) derivative from this second stage. This model fits the data significantly better than the two widely accepted alternatives (an unstructured model implied by the socioecological hypothesis or a model that allows linear stepwise changes in social complexity through time). We also find strong support for the co-evolution of social living with a change from nocturnal to diurnal activity patterns, but not with sex-biased dispersal….

I read the “letter,” but the reality is that this is one of those papers where you have to read the supplements to get a real sense of what is going on. I haven’t as of this moment, though I invite readers to browse through them and get back with their own assessment of the model. Broadly, I don’t object to the inference generated here…but I do wonder if the transition between the human-chimp ancestor and later hominins is to some extent sui generis. I have suggested that modern humans were “inevitable” after ~2 million years before the present, but I don’t think there was anything inevitable before that period. The overall point of the paper is that history and contingency matter a great deal, which to me implies that we should be cautious about making specific judgments of positions along the phylogenetic tree derived from what we gather from the whole….

(Republished from Discover/GNXP by permission of author or representative)
 
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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:


Very scientific Sort of scientific Not at all scientific
Male 5 26 69
Female 5 30 65
Age 18-34 8 34 58
Age 35-64 4 26 70
Age 65- 4 24 72
White 4 25 72
Black 11 38 51
Hispanic 8 40 51
Extreme liberal 7 31 62
Liberal 5 30 65
Slightly iberal 4 28 68
Moderate 5 34 61
Slightly conservative 5 25 70
Conservative 6 19 75
Extreme conservative 6 18 76
No high school diploma 9 41 50
High school diploma 7 32 62
Junior college 4 28 68
Bachelor 2 17 80
Graduate degree 1 13 85
Atheist and agnostic 6 23 71
Higher power 4 28 68
Believes in god sometimes 7 24 70
Believe in god, but with doubts 4 27 69
Know god exists 6 30 65
Protestant 5 27 68
Catholic 5 31 64
Jewish 6 16 78
No religion 7 28 65
Bible word of god 6 31 64
Bible inspired word of god 5 28 67
Bible book of fables 6 25 70
Human beings developed from animals 6 28 66
Human beings don’t develop from animals 5 26 69

But what about intelligence? To look at that I used the WORDSUM variable, which is a 10-question vocabulary test which has a 0.70 correlation with IQ. Below are the attitudes toward astrology by WORDSUM score (0 = 0 out of 10 score, 10 = 10 out of 10 score):


WORDSUM Very scientific Sort of scientific Not at all scientific
0 13 37 50
1 14 35 51
2 14 47 39
3 8 43 49
4 5 43 52
5 4 31 65
6 7 28 65
7 4 20 76
8 4 18 79
9 1 19 80
10 14 86

It’s pretty straightforward, the more intelligent are more skeptical of astrology. I wanted to display this in a graphical format. So I created an “astrology is scientific score” like so:

Score = % very scientific X 2 + % sort of scientific X 1 + % not at all scientific X 0

In other words, the higher the score for a class, the more accepting that class is of astrology’s scientific status. Here are the results:

There’s a pretty clear relationship between being dumb, and being more susceptible to the idea that astrology is a real science. Why? I think it’s because astrology is an eminently intuitive, plausible, and seductive, concept. Modern astronomy grew out of astrology, which is a cross-cultural enterprise which emerges in distinctive and unrelated civilizations. And why not? Most humans experience awe and wonderment when they see the stars. On first blush the idea that they may have something to do with the fates doesn’t seem ludicrous. The less reflective and dull are possibly less susceptible by modernist conditioning toward skepticism of these intuitive concepts which have been banished to the outer darkness of superstition by science.*

* Organized religion has also played a role in this skepticism. In particular, the Abrahamic religions, which evolved in an environment of competition with late antique ‘astral religion.’ But this is obviously not always t he case. Most forms of Hinduism are steeped in astrology as very much a valid and utilitarian enterprise. And in any case the campaigns by Christianity and Islam against astrology has often been fitful and futile.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Astrology, GSS, Social Science 
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ResearchBlogging.org 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:

With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ecological and historical threats (e.g., high population density, resource scarcity, a history of territorial conflict, and disease and environmental threats), broad versus narrow socialization in societal institutions (e.g., autocracy, media regulations), the strength of everyday recurring situations, and micro-level psychological affordances (e.g., prevention self-guides, high regulatory strength, need for structure). This research advances knowledge that can foster cross-cultural understanding in a world of increasing global interdependence and has implications for modeling cultural change.

This schematic from the paper illustrates the general model of how differences in “tightness” emerge:

Like many social science studies the authors relied a lot on survey data and conversion of rank ordered categorical responses into dependent variables. That’s a problem insofar as you need to take the quantities that are generated out of their statistical analyses with a grain of salt. They aren’t measuring someone’s height or temperature. Rather, they’re generating an aggregate measure from a range of concrete subcomponents. Granted, this measure has been shown to correlate well with individual questions in terms of how they vary cross-culturally. This is the “tightness,” the higher the score, the more tight the society. I do have some issues with this usage of a summary for a range of characters, but first let’s hit the raw results.

They are displayed in tabular format in the paper. That’s fine, but I decided to change it up a little for the purposes of presentation here. I took their table and focused on the “tightness” score, and added my own column which placed each national sample into a subjective broader region-cultural category.


Language Group Nation Tightness
Urdu South Asian Pakistan 12.3
Malay East Asian Malaysia 11.8
Hindi South Asian India 11
English East Asian Singapore 10.4
Korean East Asian South Korea 10
Norwegian West European Norway 9.5
Turkish Mediterranean Turkey 9.2
Japanese East Asian Japan 8.6
Chinese East Asian China 7.9
Portuguese Mediterranean Portugal 7.8
West European West European Germany (East) 7.5
Spanish Latin American Mexico 7.2
English Anglosphere United Kingdom 6.9
West European West European Austria 6.8
Italian Mediterranean Italy 6.8
West European West European Germany (West) 6.5
Icelandic West European Iceland 6.4
English West European France 6.3
Chinese East Asian Hong Kong 6.3
Polish Eastern Bloc Poland 6
Dutch West European Belgium 5.6
Spanish Mediterranean Spain 5.4
English Anglosphere United States 5.1
English Anglosphere Australia 4.4
Greek Mediterranean Greece 3.9
English Anglosphere New Zealand 3.9
Spanish Latin American Venezuela 3.7
Portuguese Latin American Brazil 3.5
Dutch West European Netherlands 3.3
Hebrew Mediterranean Israel 3.1
Hungarian Eastern Bloc Hungary 2.9
Estonian Eastern Bloc Estonia 2.6
Ukrainian Eastern Bloc Ukraine 1.6

Tables leave something to be desired in gaining a gestalt understanding of relationships, so here’s a bar plot rank ordered by tightness score, with colors corresponding to region-culture. A lot of this is presumably not too surprising. Pakistan is the “tightest” nation which they sampled. But is Norway much tighter than Estonia? I picked this pair because Estonia is the most Nordic of the ex-Soviet Baltic nations, it traditionally being a Lutheran society due to German and Scandinavian influence and hegemony until absorption into the Russian Empire. Those who have visited both nations are probably the best to ask how this comports with their own experiences.

Backing up a bit, in the introduction to the paper they take a very broad historical view. They seem to imply that there is a gap between “small scale” hunter-gatherer societies and more dense agricultural ones in terms of the importance of social norms and conformity. There’s a plausible ecological rational for this: there are many more opportunities for “free riding” in dense and large scale societies. In contrast, inter-personal relationships are probably sufficient for cultures which exist mostly at the band level. The Code of Hammurabi is only necessary in cultures where personal relationships have diffused to the point where impersonal rules and heuristics need to be interposed between parties which are literally or de facto strangers. This is probably the difference between survival and extinction in a world which was predominantly at subsistence.

In the supplements there is a table of correlations between “tightness” and predictor variables, controlling for per capita GNP. I’ve selected out the most interesting (to me):


Variable N Correlation P-value Effect size
Population density in 1500 (Log) 11 0.77 0.01 0.59
Population density (Log) 32 0.31 0.10 0.10
Rural Population density (Log) 30 0.59 0.01 0.35
Food deprivation 30 0.52 0.01 0.27
Fat supply 30 -0.46 0.01 0.21
Natural disaster vulnerability 30 0.47 0.01 0.22
Historical prevalence of pathogens 32 0.36 0.05 0.13
Death due to communicable diseases (Log) 31 0.59 0.01 0.35
Prevalence of tuberculosis (Log) 31 0.61 0.01 0.37
Infant mortality rate (Log) 32 0.42 0.02 0.18
Openness of media 29 -0.53 0.01 0.28
Murder rate 31 -0.45 0.01 0.20
% attending religious services 31 0.54 0.01 0.29

Notice the difference between population density in 1500 vs. population density today in terms of prediction! This may point us to the possibility that the long arm of cultural memory still reigns supreme to some extent. The effect size is the square of the correlation, and gives us a sense of how much of the variation in the dependent variable is predicted by the independent variable when you hold GNP per capita content. Of course it is important to observe that the N has dropped when you go back to 1500, probably because the individual data points are nations, and nations can’t always be projected back in time. All that being said I like predictor variables like population density and death due to communicable diseases best, because they’re a lot less clear and distinct than something like openness of media. Openness of media is a valid measure in my opinion, but since the statistic we’re predicting only comes out via a process of human directed calculation, having both ends of the line be open to disputation is not optimal.

As for the tightness measure itself, there’s some strangeness here. On the one hand, some if it makes sense. But scores for other nations surprising, as noted by the authors. For example, Israel. But that just leads to ad hoc explanations:

…Gelfand was surprised to find that Israel — which is under threat from its neighbors and its desert environment — is still culturally loose. Gelfand suspects that’s in part because lots of Israelis came from relatively loose cultures in Eastern Europe.

“It’s also a culture of argumentation, debate, dissent, that really is very much consistent with Judaism. And these things all promote looseness,” she says.

There are two points here. I’ll address the second first: the time depth of the culture of disputation in Judaism is something I’ll actually dispute. One can make the case that as a generality this is very much a feature of modern Ashkenazi Jewish culture, with the opening of the public debate to all sectors of society. Of course I grant that disputation between eminent rabbis occurred in the past, but pre-modern Jewry was run like most pre-modern societies, there were authorities on on high who dictated what was, and wasn’t, permissible. European Jewish communities were run as corporate subnational entities before their liberation in the wake of the Enlightenment. The expulsion of Baruch Spinoza from the Sephardic Jewish community of the Netherlands illustrates the nature of pre-modern Jewish, and gentile, society on the cusp (by this, I mean that the religiously plural Netherlands of the period exhibited a cohabitation between pre-modern exclusiveness and parochialism, and post-modern pluralism). Modern day stereotypes and generalizations are often very much the result of modern day conditions.

But the first point is of more concern to me: the aggregation of genuinely different societies into one sample. The idea that the European Jewry shared something with its Eastern European milieu is a questionable assertion. European Jews for much of the pre-modern era were in the West, but not of it. More accurately, Jews in the world of Islam and Christianity were suffered to exist, but lived in a parallel world unless they converted to the majority religion and left the Jewish community. The Yiddish (and later standard German) speaking Eastern European Jew had a strained and complex relationship with the nation-states of Eastern Europe which arose in the wake of the collapse of the old empires (Austria-Hungary, the Second Reich, the Ottoman Empire, and the Russian Empire). Can we speak of Hungarian or Romanian Jews who were distinctive from each other because of their association with the Hungarian or Romanian majority? As an illustration, Paul Erdos’ family had changed their name from Englander, as part of the process of de-Germanization and indigenization of Hungarian Jews.

This issue of the “nations” which were evaluated crops up elsewhere. The Indian sample was from west-central India, on the margins of the Hindi-Punjabi-Gujarati “cow belt.” It was very similar in “tightness” to Pakistan. But what would the “tightness” be in southern India? It may be very different. Additionally, comparing Iceland to China, as if they are comparable units, is obviously ridiculous (something the authors acknowledge). Despite my qualms with the “tightness ” statistic I would be very interested to see how this varies on a subnational scale. If it is measuring something informative and useful the correlations should start going up as you proceed down to a finer grain (“tightness” may be representative of only one region, while GNP per capita and the independent variables are drawn from the whole nation).

Though the top line of the research is focused on inter-cultural differences, the authors argue for the importance of cultural context to individual response and expectation. This is actually pretty obvious on the internet, and even among Americans. There are lots of cryptic subcultures and cultures which bubble up out of the woodwork when something of dispute comes to the fore. Prior to the issue which highlights the differences, one may not have been aware of implicit or background variation in norms.

The future direction of this sort of research will be in the direction of gene-culture coevolution and pathogen-culture coevolution, and their combinations. Pathogens are critical covariates of any shift toward dense living, and in the modern world tend to hit those from historic low density backgrounds much worse. The difference between high conformity and low conformity to me is well illustrated by the varied paths toward Christianization of the peoples of Oceania. In Polynesia the missionaries generally converted the chiefs, who then brought their people to the new faith en masse. Apparently this was just not feasible among Australian Aborigines, who were only predominantly Christianized by the 1970s. This development had to occur one individual at a time, because the “big men” in these societies simply had no ability or will to enforce conformity of religious belief.

Citation: Gelfand MJ, Raver JL, Nishii L, Leslie LM, Lun J, Lim BC, Duan L, Almaliach A, Ang S, Arnadottir J, Aycan Z, Boehnke K, Boski P, Cabecinhas R, Chan D, Chhokar J, D’Amato A, Ferrer M, Fischlmayr IC, Fischer R, Fülöp M, Georgas J, Kashima ES, Kashima Y, Kim K, Lempereur A, Marquez P, Othman R, Overlaet B, Panagiotopoulou P, Peltzer K, Perez-Florizno LR, Ponomarenko L, Realo A, Schei V, Schmitt M, Smith PB, Soomro N, Szabo E, Taveesin N, Toyama M, Van de Vliert E, Vohra N, Ward C, & Yamaguchi S (2011). Differences between tight and loose cultures: a 33-nation study. Science (New York, N.Y.), 332 (6033), 1100-4 PMID: 21617077

(Republished from Discover/GNXP by permission of author or representative)
 
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The GiveWell Blog has some suggestions for “Suggestions for the Social Sciences”. Here is the big one:

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 of ClinicalTrials.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.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Philosophy, Psychology, Social Science 
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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
Logistic regression
Variable All Non-Hispanic white
B Probability B Probability
SEX -0.340 0.000 -0.485 0.000
WORDSUM 0.176 0.000 0.201 0.000
DEGREE 0.343 0.000 0.274 0.000
COHORT -0.018 0.000 -0.013 0.001
SEI 0.002 0.393 0.003 0.394
POLVIEWS -0.105 0.011 -0.121 0.018
PARTYID 0.073 0.019 0.011 0.777
GOD -0.035 0.438 0.015 0.765
ATTEND 0.023 0.261 0.038 0.105
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.


(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data Analysis, GSS, Social Science, Trust 
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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.”

ResearchBlogging.org 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


Where in the context of an altruistic act across two individuals:

r = genetic relatedness between them
C = cost to the individual performing the act
B = benefit to another individual who is the recipient of the act

What the above equation is stating is that when the benefit multiplied by the genetic relatedness exceeds the cost, that is, it is greater than zero, the behavior will spread through natural selection. In contrast, when the cost is greater than the benefit multiplied by the genetic relatedness the behavior will be disfavored.

Here’s a “toy” illustration. Imagine a gene, G, in two variants, G1 and G2. The “ancestral” “wild type” is G1, while G2 is an allele which induces altruistic behavior toward nearby con-specifics. Assume that nearby con-specifics are likely to be genetically close, perhaps siblings. The altruistic behavior induces a cost at no benefit to the individual which is engaging in altruism, but it results in a benefit at no cost to the individual which is a recipient of the act. But here’s the key: nearby kin are much more likely to have the altruistim conferring allele, so G2 is likely increasing its own fitness because recipients of the altruistic behavior may also carry G2. Obviously the details matter here in evaluating exactly whether altruism spreads. What is the magnitude of the cost? What is the magnitude of the benefit? What is the extent of relatedness measured against a basal expectation?

There are also some presuppositions within the original theoretical framework of altruism evolving because of gains to inclusive fitness. Hamilton assumed weak selection, additivity of costs and benefits of fitness components, as well as a specific way to frame genetic relatedness. It has long been a question how robust the Hamiltonian framework is to deviations from its assumptions, deviations which are likely to occur empirically. But empirically measuring fitness in the wild as well as genetic relatedness was either impossible or difficult.

So how to get around this? A new paper was published in PLoS Biology does just that with literal a toy model of robots controlled by a simple neural network. The robots seem to mimic foraging behavior, which impacts their fitness in relation to how they replicate their digital genome to the next generation. Remember, Hamilton’s model was very theoretical, so even if there are literal artificialities here it is still an interesting empirical example which moves us closer to concrete reality. A Quantitative Test of Hamilton’s Rule for the Evolution of Altruism:

One of the enduring puzzles in biology and the social sciences is the origin and persistence of altruism, whereby a behavior benefiting another individual incurs a direct cost for the individual performing the altruistic action. This apparent paradox was resolved by Hamilton’s theory, known as kin selection, which states that individuals can transmit copies of their own genes not only directly through their own reproduction but also indirectly by favoring the reproduction of kin, such as siblings or cousins. While many studies have provided qualitative support for kin selection theory, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. In this study, we conduct simulations with the help of a simulated system of foraging robots to manipulate the costs and benefits of altruism and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different costs and benefits of altruistic behavior, we show that kin selection theory always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects, as well as mutations with strong effects on behavior and fitness. In addition to providing a quantitative test of kin selection theory in a system with a complex mapping between genotype and phenotype, this study reveals that a fundamental principle of natural selection also applies to synthetic organisms when these have heritable properties.

The science at the heart of this paper isn’t too knotty. There wasn’t a complicated novel derivation or forbidding statistical model. Rather, the authors ingeniously managed to test experimentally the simple insights of the Hamiltonian framework. The results were surprisingly unsurprising.

I reedited the panels below, but they show the consistency of the basic results. Keep in mind that the replicates varied r, B, and C.

Not to be too cute, but the robots followed Hamilton’s Rule in a robotic fashion! When the cost was too great altruism was disfavored and when the benefit was great enough altruism was favored. In a situation of balance there was the sort of stochastic fluctuation about the initial condition you’d expect. One thing to remember is that the authors simulated mutation and recombination, so selection wasn’t the only evolutionary parameter at work. The panel to the left shows how the level of altruism varied as a function of relatedness, with the ratio between cost and benefit held constant. The top left panel shows a situation where c/b = 0.01. That means that the benefit to the recipient is 100 times greater than the cost to the altruist. Even at low levels of relatedness the altruism spreads. As the ratio between cost and benefit converges upon 1, where the cost now equals the benefit, the relatedness threshold for a given level of mean altruism across these groups increases. This is all as you’d expect, boringly thrilling to see a simple model validated.

The authors also tested the impact of switching to a mutation of large effect (so not weak selection) as well as epistatic gene-gene interactions (so introducing nonlinearities which deviate from the assumption of additivity). Basically they seem to have found that both of these impacted behavior and fitness, but not the ultimate outcome. I’ll quote, because honestly I’d have liked to see more of this in the paper, but that’s probably for the future:

To determine whether mutations in our neural network had pleiotropic and epistatic effects and whether there were departures from weak mutations effects , we conducted additional experiments at the last generation in two treatments with intermediate r and c/b values (treatment 1: r = 0.25, c/b = 0.75; treatment 2: r = 0.75, c/b = 0.25). First, for each treatment, we subjected 4,000 individuals (one in each group) to a single mutation of moderate effect…In the first experiment, performance was significantly affected by a much higher proportion of the mutations than the level of altruism…1.36% of the mutations affecting the level of altruism also translated into a significant change in performance, indicating widespread pleiotropic effects. Similar results were obtained in the second experiment with 4.91% of the mutations affecting the level of altruism also significantly affecting performance. Second, we tested for epistatic effects by comparing the effect of a single mutation in 4,000 individuals with two allelic variants at another locus…genetic background significantly influenced the effect of the mutation in 2,371 (59.3%) of the cases in the first treatment and 2,336 (58.4%) of the cases in the second treatment. These results demonstrate that epistatic interactions are also widespread. Finally, our experiments showed frequent departures from weak effects on behavior and fitness. Performance changed by more than 25% for 1,616 (40.4%) of the mutations in the first treatment and 1,776 (44.4%) of the mutations in the second treatment, and the level of altruism changed by more than 25% for 552 (13.8%) and 1,808 (45.2%) of the mutations in the first and second treatment, respectively.

But in the discussion, they note:

Despite the fact that the assumptions mentioned above were not fulfilled, Hamilton’s original 1964 rule always accurately predicted the conditions under which altruism evolved in our system. Whatever the c/b value used, altruism always evolved in populations where r was greater than c/b. This finding is important given that the assumption of weak selection, additivity of costs and benefits of fitness components and absence of pleiotropic and epistatic gene interactions are also likely to be violated in real organisms that also have a complex mapping between genomes and phenotypes.

The likely power of this sort of inclusive fitness does not in my book invalidate other forces which shape social behavior such as reciprocal altruism. Nature is one, how we carve it at its joints is our business. Hopefully we’ll see a lot more tests of social behavior using robots in the future. And, with the rise of cheap typing of individual identity with genotyping there is the possibility for better assessments of relatedness and fitness across generations in nature itself.

Citation: Waibel M, Floreano D, & Keller L (2011). A Quantitative Test of Hamilton’s Rule for the Evolution of Altruism PLoS Biology : 10.1371/journal.pbio.1000615

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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.


TRUSTCI We trust too much in science
POLVIEWS Lib Mod Cons
Strongly agree 4 8 10
Agree 16 23 28
Neither 22 30 25
Disagree 37 28 29
Strongly disagree 21 11 8
PARTYID Dem Ind Rep
Strongly agree 7 8 9
Agree 22 23 26
Neither 24 31 27
Disagree 32 24 30
Strongly disagree 14 14 9
DEGREE Non-college College
Strongly agree 9 3
Agree 26 16
Neither 27 23
Disagree 29 34
Strongly disagree 8 24
NEXTGEN Science & tech. give more opportunities to next generation
POLVIEWS Lib Mod Cons
Strongly agree 42 35 40
Agree 48 57 53
Disagree 8 8 6
Strongly disagree 2 1 1
PARTYID Dem Ind Rep
Strongly agree 38 34 41
Agree 54 56 52
Disagree 7 10 6
Strongly disagree 1 1 1
DEGREE Non-college College
Strongly agree 36 45
Agree 55 50
Disagree 8 5
Strongly disagree 1 0
SCIFAITH Believe too much in science, not enough in faith
POLVIEWS Lib Mod Cons
Strongly agree 10 9 15
Agree 32 40 37
Neither 23 28 25
Disagree 24 18 20
Strongly disagree 11 5 3
PARTYID Dem Ind Rep
Strongly agree 11 10 12
Agree 38 38 37
Neither 23 29 27
Disagree 21 18 20
Strongly disagree 7 5 4
DEGREE Non-college College
Strongly agree 13 5
Agree 41 27
Neither 25 27
Disagree 17 29
Strongly disagree 4 11
TOOFAST Science makes our way of life change too fast
POLVIEWS Lib Mod Cons
Strongly agree 10 8 9
Agree 31 42 38
Disagree 48 43 45
Strongly disagree 12 7 8
PARTYID Dem Ind Rep
Strongly agree 10 10 7
Agree 38 42 36
Disagree 43 41 48
Strongly disagree 9 7 8
DEGREE Non-college College
Strongly agree 11 5
Agree 40 31
Disagree 43 50
Strongly disagree 6 14
SCISPEC Science is too concerned with theory and speculation
POLVIEWS Lib Mod Cons
Strongly agree 4 7 6
Agree 23 33 36
Disagree 50 53 52
Strongly disagree 23 7 6
PARTYID Dem Ind Rep
Strongly agree 6 7 5
Agree 29 34 33
Disagree 50 52 53
Strongly disagree 15 7 7
DEGREE Non-college College
Strongly agree 7 3
Agree 35 23
Disagree 51 54
Strongly disagree 7 20

Opinions of science of self-identified liberals. Rows = 100% or less
We trust too much in science
Male Female
Strongly agree 29 71
Agree 42 58
Neither 43 57
Disagree 46 54
Strongly disagree 49 51
White Black
Strongly agree 40 47
Agree 59 28
Neither 77 13
Disagree 80 11
Strongly disagree 86 1
Non-college College
Strongly agree 86 14
Agree 81 19
Neither 72 28
Disagree 64 36
Strongly disagree 40 60
Protestant Catholic None
Strongly agree 65 21 6
Agree 58 25 9
Neither 36 32 22
Disagree 38 27 23
Strongly disagree 30 18 39
Science & tech. Give more opportunities to next generation
Male Female
Strongly agree 41 59
Agree 43 57
Disagree 55 45
White Black
Strongly agree 73 13
Agree 72 18
Disagree 69 20
Non-college College
Strongly agree 59 41
Agree 66 34
Disagree 67 33
Protestant Catholic None
Strongly agree 33 24 29
Agree 40 25 25
Disagree 54 16 27
Believe too much in science, not enough in faith
Male Female
Strongly agree 33 67
Agree 40 60
Neither 39 61
Disagree 39 61
Strongly disagree 53 47
White Black
Strongly agree 52 37
Agree 60 26
Neither 74 16
Disagree 84 7
Strongly disagree 91 2
Non-college College
Strongly agree 84 16
Agree 81 19
Neither 70 30
Disagree 54 46
Strongly disagree 39 61
Protestant Catholic None
Strongly agree 52 21 14
Agree 47 31 10
Neither 34 30 29
Disagree 37 21 28
Strongly disagree 15 6 60

Regression results
TRUSTSCI NEXTGEN SCIFAITH TOOFAST SCISPEC
Liberals
R-squared 0.207 0.026 0.178 0.088 0.149
Age 0.014 -0.004 0.04 -0.05 -0.037
Socioeconomic index 0.279 0.048 0.04 0.159 0.13
Educational attainment -0.047 -0.212 0.107 0.062 -0.019
Vocab score 0.155 0.086 0.112 0.12 0.306
Confidence in belief in God -0.275 0.069 -0.314 -0.083 -0.135
Conservatives
R-squared 0.096 0.02 0.13 0.06 0.087
Age -0.052 0.029 -0.071 -0.11 -0.06
Socioeconomic index -0.017 -0.034 0.032 0.007 0.072
Educational attainment 0.05 -0.036 0.141 0.115 -0.031
Vocab score -0.057 -0.026 0.109 0.145 0.245
Confidence in belief in God -0.327 0.044 -0.266 -0.091 -0.18

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Anti-Vaccination, Social Science, Vaccination 
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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?:

This point was picked up by Larry Summers—hardly known as lackadaisical in personality or parenting style—who pointed out in a debate with Chua at Davos that if Karen Zuckerberg and Mary Gates had been tiger moms, they never would have let young Mark or Bill leave Harvard to pursue their entrepreneurial dreams, and we might not have Facebook or Microsoft (though America would probably have two more very competent dentists or lawyers).

Of course, it’s hard to invent Facebook or design the iPhone without developing sound foundations in math and science, the kind of preparation that Gates, Zuckerberg, and others born to privilege receive in America’s elite private schools. The dismal showing of American students in international tests implies that we’re limiting the pool of possible innovators by failing to provide this training to most children.

It also doesn’t mean that tiger moms should be any more forgiving in strict violin practice schedules or demands for A+’s in everything (except gym and art): That depends on whether they’re willing to give up stronger prospects of Ivy League acceptance for the long shot of producing the next Bill Gates. But for the American economy to exploit its relative advantages fully, we may in fact be better off with a few more easygoing parents and fewer tiger moms.

The scary thing about the “Tiger mom” idea is that it will spread among the intellectually gifted elite, and grind away the spirits of the innovation generators. A mechanical fixation on outcome and lack of deep understanding is actually probably better for the average future worker bee. By analogy, I do not have the mathematical talents to actually do original mathematics research, so someone like me sees math as a purely instrumental (or sometimes fun) enterprise. I use it. I learn it. I memorize and get comfortable with useful tricks and techniques. And that’s OK, because I’ll never see the forest. I lack the capacity.

People differ, and have varied strengths and weaknesses. There isn’t a one-size-fits-all “method.” Specialization is one way that aggregate economic productivity can rise. We should remember that.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Amy Chua, Social Science 
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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:

The hypothesis of a Hierarchy of the Sciences with physical sciences at the top, social sciences at the bottom, and biological sciences in-between is nearly 200 years old. This order is intuitive and reflected in many features of academic life, but whether it reflects the “hardness” of scientific research—i.e., the extent to which research questions and results are determined by data and theories as opposed to non-cognitive factors—is controversial. This study analysed 2434 papers published in all disciplines and that declared to have tested a hypothesis. It was determined how many papers reported a “positive” (full or partial) or “negative” support for the tested hypothesis. If the hierarchy hypothesis is correct, then researchers in “softer” sciences should have fewer constraints to their conscious and unconscious biases, and therefore report more positive outcomes. Results confirmed the predictions at all levels considered: discipline, domain and methodology broadly defined. Controlling for observed differences between pure and applied disciplines, and between papers testing one or several hypotheses, the odds of reporting a positive result were around 5 times higher among papers in the disciplines of Psychology and Psychiatry and Economics and Business compared to Space Science, 2.3 times higher in the domain of social sciences compared to the physical sciences, and 3.4 times higher in studies applying behavioural and social methodologies on people compared to physical and chemical studies on non-biological material. In all comparisons, biological studies had intermediate values. These results suggest that the nature of hypotheses tested and the logical and methodological rigour employed to test them vary systematically across disciplines and fields, depending on the complexity of the subject matter and possibly other factors (e.g., a field’s level of historical and/or intellectual development). On the other hand, these results support the scientific status of the social sciences against claims that they are completely subjective, by showing that, when they adopt a scientific approach to discovery, they differ from the natural sciences only by a matter of degree.

The cult of p-values is such that “sexy” results often get published which are not replicated. Additionally, scientists have biases in terms of what they should find. This occurs in a non-political context in the natural sciences. In Jonah Lehrer’s widely circulated piece on the “decline effect” there were plenty of examples from biology. I assume that the assumed political liberalism in social science labs across the country has a strong effect on what gets studied, how it gets studied, and what gets submitted.

Consider the work on gay parenting. This is an aspect of the “Culture War” where conservatives are slowly and inexorably losing, with gay marriage assumed to be inevitable within the decade. Much of the recent work shows that there is no difference in outcomes of children from gay parents, or that these children even fare better. Now, imagine if a pro-gay rights researcher find a marginally statistically significant effect of having gay parents being correlated with adult psychopathology. Social science being what it is the researcher could plausibly argue to themselves that this isn’t a robust result which would be validated by replication, especially in light of the previous research in this area. Additionally, what if you add in the possibility that there is a gay marriage ballot measure in the state where this researcher lives, and where their research university is prominent? Should they present their findings at conference and so allow it to get reported at such a critical juncture?

I’m giving you a pretty stark and bald example, but I think more subtle forms of bias are just part of the bubbling epiphenomenon of science. Especially in light of the psychological discipline’s tacking with the cultural winds when it comes to homosexuality I don’t think that it is likley that there isn’t a level of political cheerleading going on here. I actually accept the behavior genetic finding that parents matter a lot less than we assume, so as a matter of fact I assume that having gay or straight parents doesn’t have a large effect. But, I don’t believe that researchers in this area, which is at the heart of the culture wars, are dispassionate. And, I think that effects their outcomes somewhat in the aggregate.

Where does this leave us? Buyer beware! I’ve identified myself as conservative several times on this weblog. I’m pretty skeptical of the findings of social science in a lot of cases because I assume there’s bias which creeps in because there’s so much unanimity of thought in labs. I’ve heard plenty of stories on the ideological pressures which are get reinforced as a matter of course. Not only that, but many social sciences have normative biases baked into the cake of their disciplines. Economics is one where many on the far Left complain that “orthodox” “positive” economics is actually ideology pretending to be science. As a conservative, and not a libertarian, I think they have a point. In particular, the materialistic methodological individualism of modern economic models of utility do miss something I believe when it comes to Eudaimonia.

But as a conservative, I believe in muddling on. I’m skeptical of social engineering generally, and I’m skeptical of social engineering in this case. Just how the die rolls.

Addendum: One thing about ideas is that quality, not quantity, matters. So I don’t think you need proportionate number of conservatives or liberals in a discipline of culture to make ideas heard. The Federalist Society for example has changed the legal world, despite the likelihood that most elite lawyers remain conventional liberals.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Ideology, Science • Tags: Politics, Social Science 
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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:

We present results from the first large-scale international survey on time discounting, conducted in 45 countries. Cross-country variation cannot simply be explained by economic variables such as interest or inflation rates. In particular, we find strong evidence for cultural differences, as measured by the Hofstede cultural dimensions. For example, large levels of Uncertainty Avoidance are associated with strong hyperbolic discounting. We also find relations between time preferences and risk preferences, like loss aversion. For instance, subjects with high loss aversion tend to show larger time discounting. Moreover, our analysis shows an impact of time preferences on the capability of technological innovations in a country and on environmental protection.

To get published in orthodox economics you need to do a lot of mathematical modeling, but I’m not too interested in that. Rather, let’s look at some of the descriptive results. The first two figures shows the percentage of participants who chose the $3800 option when they were asked to choose between $3400 this month or $3800 next month. The last figure has on the x-axis “time pace.” This is an overall-pace measure is calculated out of three measures: walking speed, postal speed, and clock accuracy.
timep1timep2timep3

Some of the text is very illuminating as to cross-cultural differences:

Even for the students from Princeton University, the percentage choosing the patient option is lower than the percentage of German students (80% vs. 89%). Actually some students from our Norway survey even complained that the question was ridiculous because everybody would choose to wait for one month given the high implicit interest rate.

Other results were not surprising:

This result suggests that although the wealth level (and hence a general level of a country’s economy) is crucial to stimulate innovation, the attitude towards future also plays an important role. For example, while 69% of Taiwanese participants prefer to wait in the one-month question, only 44% of our Italian students prefer to wait. The two countries have the same GDP per capita in 2007, but Taiwan scored much higher in the innovation factor than Italy (5.26 vs. 4.19). It is worthwhile to investigate further to what extent and under what mechanism a general attitude towards future is related to the innovation activity.

And yet some were (at least to me):

After controlling the macro-economic variables (GDP per capita, growth rate, inflation rate), participants from countries with higher degree of Individualism and Long Term Orientation are more likely to wait. In contrast, for the present bias and long-term discount factor, the country with higher Uncertainty Avoidance score tend to discount the next year more.

In other words, societies and individuals who were more individualistic tended to have low time preference (more future-time orientation). It would be interesting to further decouple confounding variables. I assume that more intelligent people are more individualistic as well, so that might be the source of the correlation.

I didn’t focus on the formal model too much here because this seems highly exploratory, and there were many non-significant results. But I think this paragraph is of some interest:

In summary, it seems that we need different models for waiting tendency and medium/long-term discount factor. The waiting tendency depends more on the fundamental economic variables such as the country’s wealth level, and on general attitudes in a society such as individualism and the mentality towards past and future. In comparison, the medium/long-term discount factor depends more on the dynamic factors such as growth rate, and the attitudes toward uncertainty.

(Republished from Discover/GNXP by permission of author or representative)
 
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shallrelig1

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.


As indicated above Eric Kaufmann does not simply present one with qualitative verbal arguments, he actually goes over the projections of quantitative models which his research team generated! In this area this is gold, for pure conjecture and speculation tend to abound. But Shall the Religious Inherit the Earth is not purely a theoretical treatise, it is rich with thick empirical data and references the broader literature. Eric Kaufmann is not sloppy with detail, and tends to couch assertions carefully. Unlike many who have a thesis he does not ignore or mitigate trends which go in the opposite direction of his broader argument. He admits, for example, that secularization continues in some regions of the world; in particular the United States, Southern Europe, and southern Latin America. There may even be some juice left in secularization in Northern Europe as the older generations which fill the pews die off to be replaced by the cresting wave of irreligious born since 1960. He also admits that societies which have gone through secularization have not swung back to irrevocable religiosity. For example, France in the early 19th century was characterized by a situation of highly fecund Catholic immigrants arriving to reinforce the conservative Catholic faction among the native-born. And yet nearly two centuries later France is as secular as ever, and in fact getting more secular.

These caveats aside, the demographic parameters of growth and decline do significantly shape the destiny of the future. In regions such as Bosnia, Northern Ireland and the Netherlands the religious makeup of a society has slowly shifted purely through differences of fertility. This has had long term social-political consequences of varying degrees. This is not speculation or prediction, rather, we know the present conditions, and can see the hand of demography shaping the path of the past. His attention to specific details and their nuance is where Kaufmann wins my respect. He notes that the seemingly inevitable Catholic ascendancy in the Netherlands was never to be, because that sect experienced the same collapse in popular support which the mainstream Reformed Church did a generation before. The parameters of demographic destiny can be quite variable, so the details must always been approached with caution. Similarly, the fertility gap between Catholics and Protestants in Northern Ireland has closed, so the likely inevitable shift to a Catholic majority has slowed to a crawl and is only proceeding by demographic inertia. The long-term winners of the demographic game may not always be who we perceive to be most salient in the present, as engines of activity bubble underneath the radar.

The outline of Shall the Religious Inherit the Earth is simple. A few initial general chapters lay out the parameters, probabilities, and projections. Then a series of specific sections focus on particular regions; the USA, the Islamic world, Europe, and Israel. Finally Eric Kaufmann reviews the general outline of his thesis, its implications for secular people, of whom he is one, and the caveats that must be made.

In a nutshell, here’s the power of endogenous growth.

changegrowthrates

Russia currently has a -0.50% growth rate, while Afghanistan has a 3.85% growth rate. Projecting outward on a yearly basis and you see the power of compounding. Assuming current rates of growth (or shrinkage) the two nations will cross paths sometime in the year 2050. Do I believe that that will come to pass? No. There’s no reason that these growth rates have to stay constant. I believe Afghanistan’s will decrease, while Russia’s will increase. In the former case I don’t think Afghanistan’s Human Development Index could get any lower, so I think fertility is going to go down almost as an iron law of modern existence. For Russia, fertility collapsed relatively recently, so it may bounce back with a cultural change. Also, there are likely more fertile minorities within Russia would will bring back median fertility.

Let’s use a toy example to illustrate what I’m alluding to here. Imagine that 10% of Russian citizens are very fertile. If a nation of their own they’d have growth rates of 5% per year. In contrast 90% of Russians have a negative population growth rate of -0.6% per year. This produces about -0.50% per year when you weight by population for Russia as a whole, what we have right now. Let’s take the projections from the first chart, and add a new value for Russia which consists of the total population assuming these two sub-Russias are viewed as distinct populations. In other words, they don’t intermarry, and continue at their current pace of population growth.

changegrowthrates2

So what happened? The new scenario for Russia still has population decline for the next 20 years, but eventually it stops and reverses. That’s because of the subsegment within the Russian population which is fertile keeps increase its proportion, and the aggregate rate of change shifts along with that. In fact, projecting outwards, in 2109 the fertile Russian group will be 94% of the population of Russia, as opposed to 10% in 2009. Because they’re the preponderance of Russia’s population in this toy model Russia they’re actually outpacing Afghanistan by then.

I wanted to show you a very simple toy model to give a good sense of the power of endogenous population growth and projection. This is the core axiom at the heart of Shall the Religious Inherit the Earth. Demography influences destiny. I say influence because as Kaufmann himself will admit, and I always want to emphasize, fertility differences between populations can invert. In the 19th century in Rumelia, the Balkan regions under Ottoman rule, Christians had higher fertility than Muslims. Today the situation is very different. Some historical scholarship indicates that until very recently what we know of as Bosnia actually consisted of two populations, Muslims and Catholics, whose dialect of South Slav was more similar to Croatia than Serbia. The rise of Bosnian Serbs may then have been a function of migration due to population growth in Serbia proper. The subsequent conflict in the Balkans can be traced to Serb fears of Muslim hegemony in a nation in which that element became a larger and larger fraction due to higher fertility.

Before we move to specifics, a few general trends highlighted in Shall the Religious Inherit the Earth. First, the simple one: the highly fertile religious nations are waxing in population, while secular regions are stagnant, or even in decline. In general Europe and European dominated societies are in the second class, along with East Asia. Basically the two regions of the world which most people reading this weblog would consider at an advanced state of modernity. In contrast, in the Islamic world, and in the more religious nations of Latin America (exclude the southern cone), Africa, and South Asia, secularism is weak as a mass phenomenon (though it has some purchase among elites in Latin America and India), and fertility is still high. Even in nations which are now sub-replacement, such as Iran, will grow in population because of demographic inertia. The young have not entered their peak childbearing years. Here are some examples:

Of course one can imagine that secularization will kick in in these societies at some point. But generally there needs to be a particular level of development, and in many of these nations it will be a very long haul indeed. If we’re taking about the scale of 2-3 generations it seems plausible that the proportion of atheists and agnostics in the world will decline as East Asia and Europe become a smaller and smaller fraction, and secularization does not immediately initiate in developing world. Examples of “snap secularization,” where societies go from being very religious to very secular in a decade or so, like Quebec, seem to have a bit of affluence under their belt (Spain today may be an example of this).

Eric Kaufmann has a specific thesis as to how modern secularization occurs: as societies develop nominal believers in religious societies eventually fall away. In Saudi Arabia, or Thailand, the connection between religion, culture, and nationality, is such that there are vast numbers of people who are affiliated and religious, but who don’t have any strong individual drive to be so. Rather, in their particular social environment some level of religiosity is the only option. Also, in the high fertility fraction of these societies there does not seem to be much fertility difference between the more and less religious. Rather, the fertility difference becomes stark once a society goes through demographic transition, and having children becomes a discretionary choice, rather than an expectation. The choice seems to be made in particular by individuals affiliated with strongly communitarian religious groups.

In the United States the fertility differences between religious groups can be stark. Muslims have a TFR of 2.84, while Jews have one of 1.43. The long term consequences of these between group differences are obviously interesting, but I believe that the more important data in Shall the Religious Inherit the Earth is the documentation of within group differences. Aggregate Jewish fertility is low, below the 2.08 natural average. But Orthodox Jews are above the national average, while “ultra-Orthodox” (haredi) Jews are two to three times the national average! While the generic conservative white Protestant TFR is 2.13, there is a core group of radical conservative Protestants who have a TFR of above 2.5. Small sects such as Foursquare Gospel have Mormon-like rates of fertility. While the average American Catholic is around the same fertility as the non-Catholic, conservative traditionalist Catholics are much more fertile. Antonin Scalia has nine children.

Because of the relatively advanced state of the world Ashkenazi Jewry some of Eric Kaufmann’s predictions seem to be especially born out in them. Haredi Jews are the most ‘conservative’ of Orthodox Jews. We gentiles would probably recognize them as the Jews who ‘dress weird.’ The Hasidic communities are famous, but there are also non-Hasidic Haredi Jewish groups. In Britain the Haredim are 17 percent of the Jewish community. But shockingly they’re currently 75% of the births currently in Britain to Jews! Kaufmann also claims that the Haredi are now ~10% of American Jews in 2010, which would mean that the Orthodox as a whole are now gaining. The patterns in Israel are also striking, though more complex.

Israel is on of the world’s most ethnically diverse societies, with broad ethno-national categories of Ashkenazim, Mizrahim, and Sephardim, though even within these categories there is variation. In addition to this, there are divisions between secular Jews, religious, but not strictly Orthodox Jews, Orthodox Jews of a modern bent, and finally, the Haredi. In this framework arguably the Ashkenazi are bimodal, concentrated among the secular and Haredi segments, while the non-Ashkenazi Jews tend to be religious, but not hyper-observant. On top of this there are also hyper-secular Russian Jews, many of whom are only partly Jewish in origin, as well as the non-Jewish minorities, mostly Arabs. In 1960 15 percent of elementary age students in Israel were Arab or Haredi. In 2010 ~50% are. It is because of the Haredi that Israel does not face an immediate demographic crisis as a Jewish state:

…In 2001, there were around 95,000 Jewish births in Israel and 41,000 Arab births. Just seven years later, in 2008, Jewish births had risen to over 117,000, but Arab births had declined to less than 40,000. In a period that constitutes barely a quarter of a generation, Arab births had fallen from around 30 percent of the total to around 25 percent. This has been a steady trend and, should it continue, it will only be a very short time before Jewish and Arab births each year are broadly proportionate to the overall balance of Jews and Arabs in the population as whole – that is, 4:1, or 80 percent and 20 percent, respectively.

The Haredi fertility is stable, somewhere in the 6-10 TFR range depending on the community, while Arab TFR has dropped to 4 or below. Interestingly the secular Jewish TFR has also increased in the past generation, from 2.1 to 2.6. This is a reminder to be very careful of average values of fertility for a group. It seems that for ideological or cultural reasons the Haredi in Israel remain fertile, even after allowances for children were cut back, which had an immediate effect on Arab fertility. The lower Jewish aggregate fertility ignores the motive force of the Haredi within the larger community. Assuming current trends the Haredi will likely become the majority within Israel by about 2050.

Shifting to Europe, the same dynamic may be at play. It is well known that much of Europe has a Muslim minority, though perhaps less well known that Russia has a larger proportion than any Western European nation, at ~10-15%. In the European Union as a whole the total number of Muslims is on the order of ~5%, and this includes traditionally Muslim groups in the Balkans (Slavs, Albanians, and Turks). But the key is the future. Kaufmann assembled data from nations where there was information on fertility changes by religion, migration rates, etc. Here are some numbers for Western European nations:

euroslam1

Some of this is not too surprising. The problem in the area of statistics about Muslims in Europe is that ignorance, fear, and stupidity is rife. As someone with an aversion and dislike for Islam in particular of all the higher religions I have been known to be susceptible to that tendency. But the reality is that Islamic populations are modest, but very concentrated, in much of Europe. So, for example the fact that in Rotterdam the majority of births may be to Muslims is conflated with the fact that the majority of births in the Netherlands will be to Muslims! Americans who travel to Europe and visit Amsterdam, London, and Paris, may get a very skewed view as to the ethnic diversity of Europe. Even then, London, that most diverse of cities, is actually about as white as the United States as a whole.

There are several parameters which will influence Islam in the future. Primarily, intermarriage, conversion & defection, immigration, and fertility. Outside of the French Muslim community intermarriage with non-Muslims is low in Western Europe. This is in contrast to traditionally Christian groups; more than 50% of second generation black Britons intermarry, vs. less than 10% of Muslims (though the number for South Asian non-Muslims is nearly as low). Though there are prominent instances of conversion, the reality is that numerically they are few and far between. Though outright defection to Christianity or other religions seems uncommon, in part because of social ostracism from the community, in some regions secularization is common (e.g., France). Finally, there is immigration and fertility. Some of the source nations of Muslims to Europe, such as Turkey and Algeria, are near replacement or sub-replacement in fertility. Additionally, even though European social benefits are generous, one could assert that Turkey presents a more favorable medium-to-long-term prospect in terms of labor opportunities than Germany for a Turk. With the likely curtailment of the most generous aspects of the European welfare state in the age of austerity one presumes that that magnet for immigration will be less powerful. Finally, there is the issue of fertility. Here there is wide variance, with very fertile South Asians and Somalis, and far less fertile North Africans and Turks. The source nation of the ethnic group seems to matter quite a bit. Nevertheless, there are two factors to highlight here. First, there is almost always a gap in fertility between Muslims and non-Muslims. In the German-speaking world and Italy the fertility of non-Muslim populations (excluding Roma) is so low that even modestly fecund Muslim minorities have a great advantage. Second, Muslim fertility rates do tend to converge with non-Muslim ones after a few generations.

euroslam2

The assumptions in the model:

- Convergence between Muslim and non-Muslim fertility by 2050

- The same rates of immigration between now and 2050

- No secularization for Muslims between now and 2050

None of these are realistic assumptions, but the deviation from reality of the first would have the opposite effect as the latter ones. That is, fertility will probably not totally converge, but it is also likely that some secularization will occur, and that immigration rates may decrease because of the global demographic transition. Taking the projections further the models indicate that the Muslim proportion of Europe will stabilize at around ~20% by the second half the 21st century. I find it interesting that Sweden may have the highest fractions of Muslims in Europe in my lifetime, excluding areas with traditional Muslim majorities (Albania), or large minorities (Macedonia, Bulgaria, etc.). Perhaps by 2050 a “Swedish Burqa Team” will be more appropriate than a “Swedish Bikini Team.”?

euroslam3The exception in Europe in regards to the Muslim vs. non-Muslim gap is France. This has long been evident to me in the survey data. French “Muslims” are more religious and fertile than French non-Muslims, but the gap is far smaller than between British Muslims and non-Muslims. The figure to the left is from The Gallup Coexist Index 2009. It’s immediately evident that though French Muslims are far less gay friendly than the French public as a whole, the gap between them and the broader society is far smaller than between British Muslims and the British in general. Literally 0% of British Muslims believe that homosexuality is morally acceptable. I guess the British can take pride in their multicultural society, which has allowed for diverse values to flourish.

In any case Eric Kaufmann argues that there’s a relatively understandable reason why French Muslims are more integrated than their co-religionists in Britain and Germany. It isn’t because of France’s ideological demand that immigrants assimilate to “French culture.” Rather, he points out that a disproportionate number of French Muslims, the majority, are of North African origin, and that North Africa has a relatively large secular population in relation to the rest of the Muslim world. Additionally, a disproportionate number of North Africans in France are of Kabyle Berber stock. This non-Arab minority in Algeria has long been subject to discrimination from the Arab majority, especially in the nationalistic era. In response Kabyle intellectuals have espoused an aggressive separatist identity, which has pushed Islam somewhat to the side because of its association with the Arab conquest and the Arab majority. Though Muslims, I believe one would see the same trend with the Alevi Turkish Muslims in Germany, who are reputedly more open to assimilating into German society. A group which has been persecuted and marginalized in Turkey itself by the Sunni majority, it seems plausible that the Alevi Turks have a less strong attachment to a separate identity as Turks because of their fraught history.

But what about the presumed Christian majority? European societies have been traditionally Christian, and today are nominally so. In nations like Finland most people are members of the national church, but it is an expression of their national identity, not their belief in the truth claims around which the institution was built. In other words state-sponsored Scandinavian Lutheranism is rather like a facade, with all the trappings of outward religion, but generally lacking in substantive dynamism. But there are exceptions to this in all European societies where a lax and nominal majority is ascendant. In Finland there is a branch of the sectarian Laestadian Lutherans. Their fertility is awesome. In the 1980s while the TFR of the majority Finnish Lutherans was 1.5, that of the Laestadians was 5.5. I met an individual whose family was from the Laestadian tradition last spring. Though he himself is not a religious believer at all, I was struck by the fact that he and his wife (also irreligious) were enthusiastic about the prospect of having a rather large family, definitely above replacement. In the United States such a sanguine attitude toward family planning, and pro-natalist enthusiasm, is pretty much unknown among secular professionals of my acquaintance. In contrast, in Italy the whole society is strongly skeptical of the sustainability of large families in terms of maintaining levels of individual affluence, though they are rather ill-at-ease with the importation of West African, Filipino, and Bangaldeshi servitor castes.

These sorts of within society fissures and divisions lead us to consider the wide gap in fertility and religiosity which has now emerged in Western developed societies. Eric Kaufmann points out that it is precisely in these secularized developed nations that the correlation between religiosity and fertility is strongest. The religious invest their surplus economic productivity in children in a classic Malthusian manner. Secular and moderately religious folk tend to practice family planning, and many have delayed child-bearing so long that they will not replace themselves (being childless or only having one child). It is in the wake of the first demographic transition that Eric Kaufmann believes a second demographic transition will emerge. The cultural and social realities which enjoined high fertility in the pre-modern world no longer hold. Now that people may choose when to have children, many choose not to. Those who choose to have children do so for ideological and normative reasons. The natural inference then is that the correlation between values and fertility is driving rapid cultural evolution in these societies.

From all the data surveyed it seems that Israel is the nation which is closest to the second demographic transition.

In many ways it is a peculiar nation. Though the Haredi are the primary vehicles of the Jewish demographic renaissance, they are also famously less economically productive on a per unit basis than non-Haredi Israelis. They also tend to avoid national military service at much higher rates than the rest of the Jewish population. It is clear that in some ways Israel is facing a crisis of national identity because of the demographic decline of its core Zionist ethnos, the secular Ashkenazi Jew. These are the intellectuals, politicians, and military officers of the Israel state. But if current trends pan out, by 2050 Haredi Jews will be a majority of Israel’s population. If that is so then without a massive gain in per capita human economic productivity the Israeli state will not be able to subsidize the scholarly pursuits of many Haredi men. Between then and now a social revolution of some sort is inevitable. Details to be worked out.

But 2050 is a long way away. How much of 2010 could you predict from 1970? In general I have to admit that I skip over projections of the year 2100. On the other hand, projections of the year 2030 are of great interest, as a 20 year window seems small enough that trends would be robust enough to absorb any shocks. 2050 is a gray point for me, I’m generally skeptical, but don’t think that such projections can be dismissed out of hand. But the details matter. Kaufmann quotes some scholars who assert that ~20% of Americans will be of mixed racial heritage heritage by then as defined by the Census. Depending on how these individuals classify themselves, and how society views them, will turn the answer to the question of whether the USA will be majority non-white in 2050. Trends can change very quickly, as can their interpretations.

The author admits that an “optimistic” scenario, from his perspective as a liberal secular Westerner, is of equilibration. That the fecund religious will birth the future generations of secularists. In some ways this has been occurring for a few centuries now, starting with the first explicit and public anti-clericalists who came to the fore during the French Revolutionary regime. In Kaufmann’s own data set he shows that secular Dutch women were below replacement before World War II. And yet Dutch society as a whole went through massive secularization after World War II. The point here is that even though religion is heritable, it is not purely so.

But the current regime is different from the previous one. Before World War II secularists were a rather small minority. In Germany in the mid-1930s around 96% of the population still had affiliation with the Protestant or Catholic confession. Some of the remaining 4% were Jews. Today 35% of Germans register “no confession.” Secularism in Europe today is a robust cultural phenomenon, and in its Northern and Western European cores it seems to have peaked among the youth. There is still some secularization to be had as older generations pass on, but over time the fertile religious will trigger the second demographic transition. And here Kaufmann argues that conservative anti-worldly religious groups have become better and better at inoculating their offspring from the temptations of the secular world. Retention is now much higher than it was in the past. Though he doesn’t quite come out and say it in such a manner what is being alluded to here is cultural evolution, so that fundamentalist groups are much better prepared in the ideological battle with mainstream secular culture. God lost the initial battles, but he may still win the war.

If so Kaufmann sees a dark future from what I can gather. At least dark as judged by what secular liberals think is right, true, and good. The precedents in Israel are not heartening to secularists. Demographically robust Haredi have been marginalizing non-religious Jews across much of the country. Though Tel Aviv remains a European Mediterranean city, in many ways Jerusalem has become distinctively Oriental-Haredi in flavor. The fusion between religion and nationalism can lead to explosions of violence, such as that of Yigal Amir. I don’t need to elaborate on the specifics, as that ground has been fruitfully covered elsewhere. The question Shall the Religious Inherit the Earth poses is whether this century will be the great glorious age of secular liberal democracy; the century when history stood still and the gods slumbered. If the religious become numerically preponderant it may be that the atavistic battles of the past will come back to life. Already there have been accusations that American foreign policy in the aughts was driven by evangelical Christian fervor. Though I find Robert Pape’s arguments as to the secular origins of religious terror persuasive, I also believe that the supernatural-communal aspect of the acts makes them all the more powerful in their impact, and the enterprise more sustainable.

Eric Kaufmann ends Shall the Religious Inherit the Earth on a wistful, almost existential, note. He observes that the religious believe they have a reason to be, and to procreate so as to produce the next generation of humans. In contrast many non-religious folk lack such a drive or inclination, and are satisfied with consuming and enjoying the present. Secular ideologies have by and large disappeared as major animating forces in our culture. There is no Marxian dialectic driving us to some end point, rather, it seems that modern secular man yearns for a future with successively more flashy and functional iPods and iPads. But in nations such as Israel the secular population is still the primary engine of economic growth; like Atlas it holds both the Haredi and Arab sector up with its subsidy derived from its industry. What will the future hold if the worldly folk are shunted aside by their own self-indulgence? Can a technological civilization persist if the world is dominated by stark sectarian cultural commonwealths? Though the demographic answers are provisional, and I only have a modest confidence in their validity, these more philosophical questions which Eric Kaufmann poses leave me uncomfortable.

Nevertheless, Shall the Religious Inherit the Earth is a book that every data-driven culture-nerd should pick up. It requires a few read throughs, and a great deal of rumination.

Image Credit: Ricardo630

(Republished from Discover/GNXP by permission of author or representative)
 
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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:


antimisclaw

There is a small but consistent difference until the last year. The difference is within 95% intervals within a given year of course. But the consistency of the greater female support for interracial marriage bans made me want to perform a logistic regression. I decided to look at the total sample, and also limit it to the 1970s. The pseudo r-square for both is ~0.20. Italics means lack of statistical significance. The other values were all p = 0.000 in the GSS interface.

Full Sample 1972-1980
B B
Sex -0.282 -0.428
Degree 0.467 0.430
Intelligence 0.296 0.329
Political Ideology -0.147 -0.178
Year of Survey 0.054 0.041
Age 0.036 -0.041

These results confirm that being female predicts a greater likelihood of supporting laws against interracial marriage. Having more education and being intelligent reduced the probability. Surprisingly year and age don’t matter much when you’re taking other variables into account.

As a final note, let’s compare sex differences on another issue: homosexuality. The HOMOSEX variable asks about “sexual relations between adults of the same sex.” There are four responses:

1 = Always wrong

2 = Almost always wrong

3 = Sometimes wrong

4 = Not wrong at all

Using the GSS I computed the mean value year by year. So if in 1974 50% said homosexual sex was always wrong, and 50% not wrong at all, you’d have a mean value of 2.5. Here is the trendline by year by sex:

homsexsex

As with interracial marriage, there is a small, but consistent, sex difference. On the margins the sex difference will disappear, so one can think of it as one sex “lagging” the other on social change.

(Republished from Discover/GNXP by permission of author or representative)
 
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Big Think has a post, Do Women Value Ethnicity Over Income in a Mate?:

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.

I’ll offer a hypothesis in keeping with Ann Althouse’s rule-of-thumb in regards to discussing sex differences in polite company: make sure to make it seem as if women are superior in some fashion. Perhaps women simply have a lower time preference? That is, they’re thinking of long-term consequences. Interracial divorce rates are higher, so women may be making implicit calculations as to the probable success of a relationship as opposed to the short-term benefits of a pairing which men fixate upon. Additionally they may be more liable to “think of the children.” Though I’m generally skeptical of the social science research in this area which indicate that mixed-race children experience stress because of their background, there are plenty of high profile media accounts of people of mixed-race and their “struggles” with their identity. This may shape perceptions of the quality of life of the children. In other words, women aren’t being shallow at all, race is an excellent proxy for all sorts of social-cultural variates which might effect the outcomes of a relationship success, and also the fullness of life which their offspring may experience. Women are then in this model being prudent by using a coarse variate, race, as a proxy for the multi-textured reality of how race is lived in America, and how it matters deeply in the lives of human beings.

To test this sort of model we need data from other societies. There are confounds in this analysis in the USA because Asians, for example, are a small minority who as a matter of necessity can’t really limit their dating pool as much as whites. Additionally, it would be useful to take a fine-grained look at Hispanic dating patterns. About ~50% of Hispanic/Latino Americans identify as white, ~40% as “other”, while ~10% a mix with a substantial number of blacks. The race preference may be mostly a function of perception of cultural values, in which case you’d see that Hispanics don’t exhibit any sex bias in race at all. Then it would not be a matter of women being more racist, but being far less cosmopolitan! Oops, I mean that the low time preference is not operating through a racial proxy but a cultural proxy which is correlated with race. In other words, women are culturally sensitive, while men are culturally insensitive.

(Republished from Discover/GNXP by permission of author or representative)
 
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