In the early 2000s I recall Joel Grus telling me how reality television would become a pretty powerful exploratory tool for social science. I’m not quite sure of that now (there here’s a game-theoretic analysis of Survivor!). For example, consider The Bachelor and The Bachelorette. If you watched this series you might think that we’re still living in the same country where a episode of Star Trek was not shown in the South because of an interracial kiss. In some ways “appointment television” has become a lagging indicator.
Rather, it looks like firms whose bread & butter is “the social web” are where the gold in social science is. Consider the OkTrends blog, which is affiliated with and has access to OkCupid. These companies have sample sizes not in the thousands, but in the millions! The Financial Times has a fascinating piece on the “secret sauce” of Match.com, Inside Match.com: It’s all about the algorithm:
I just finished reading My Fertility Crisis, which is excerpted from a longer piece you can get on for $1.99. The author is a single woman in her early 40s who is going through IVF treatments, without success so far. She outlines the choices she made over her life which may have influenced her current situation.
After reading the piece I came back to an issue I’ve wrestled with before: it’s often really hard to find information on probability of pregnancy online in the form of charts. The reason is that there’s so much information, and much of it is skewed toward people who are undergoing treatment for infertility. But why look when you can generate your own visualization? I found a pregnancy probability calculator online which I cross-validated with some of the literature. Here is the best case scenario for probability of pregnancy if you are trying in the natural fashion (the probabilities exclude women who are clinically infertile, which is a rather slippery category strongly dependent on age, so the older cohorts are probably much larger overestimates than the younger ones):
The main focus is really the decade of the 30s for women. Here is a figure from Ovarian Aging: Mechanisms and Clinical Consequences which shows a finer-grain decline in fertility:
The figure to the left is from a new paper in Science, When the World’s Population Took Off: The Springboard of the Neolithic Demographic Transition. It reports the findings from 133 cemeteries in the northern hemisphere in regards to the proportion of 5-19 year old individuals. When calibrated to period when agriculture was introduced into a specific region there seems to be a clear alignment in terms of a demographic transition toward a “youth bulge.” Why? A standard model of land surplus explains part of it surely. When farmers settle “virgin land” there is often a rapid “catch up” phase toward the Malthusian limit, the carrying capacity. Another possibility though is that sedentary populations did not need to space their offspring nearly as much as mobile hunter-gatherers. Whatever the details, the facts remain that the data do point to a shift in the age pyramid during this period. The author wonders as to the possible cultural implications of this. There is an a priori assumption that a young vs. old age profile in a society constrains its choices and channels its energies (e.g., think the “baby boom” generation in the USA). A final interesting point is that the authors note that today we are seeing the last gasp of this transition toward large numbers of children, as fertility drops toward replacement all across the world. That too may have some cultural consequences.
Here’s a podcast with the author. Link via Dienekes.
Chris Mooney pointed me to a report on a study which finds that white males are the most sanguine in relation to climate change. Unfortunately there wasn’t a link to the full report that I could see. But no worries, the GSS added a variable, TEMPGEN1, which asks: “In general, do you think that a rise in the world’s temperature caused by climate change is….”
1 – Extremely dangerous for the environment
2 – Very dangerous
3 – Somewhat dangerous
4 – Not very dangerous, or
5 – Not dangerous at all for the environment?
Below is a bar plot which illustrates the result by demographic:
I would like to throw out the word that I am looking for a person with Malagasy ancestry for the African Ancestry Project. To my knowledge there are no thick marker autosomal analyses of the Malagasy people. After my recent exploration of Southeast Asian genetics I think even one individual would be highly informative.
As usual I would guarantee that these data are entirely private, and I do not share it with anyone. But in this case I would like to make an exception and stipulate that Joseph K. Pickrell, a graduate student at the University of Chicago, would also be very interested in access to a Malagasy genotype for the purposes of research. Since this is an undersampled population the marginal returns to a Malagasy genotype would be enormous for science, a public good rather than just a private gain.
Also, I am still looking for a Tutsi genotype so that I can ascertain the origin of this population.
Please contact me at .
Lots of commentary below on my post about extramarital sex. I guess that’s fine, but I’m really not too interested your theories, I can do basic logic after introspection too. In fact, I can go down the street and ask a random person and I’m sure they could offer up after the fact rationales for the results I reported (people are always interested in sex and sharp about models to explain it). Instead, here’s the variable you need to use in the GSS: XMARSEX. I assume forms and graphical user interfaces worthy of 1997 are not too intimidating to readers of this weblog even if they perplex Matt Yglesias?
In any case, here’s some more results. First, I wanted to double check that there was in fact decreased tolerance of extramarital sex over the years. Let’s break it down by sex:
Some of you were curious about the demographic correlates of this behavior. Please note that all the following charts are limited to the year 2000 and later. The sample sizes for XMARSEX were rather large, so I saw no reason not to make it relevant to contemporary attitudes.
Representatives of Szechuan and Shangdong cuisine
The Pith: The Han Chinese are genetically diverse, due to geographic scale of range, hybridization with other populations, and possibly local adaptation.
In the USA we often speak of “Chinese food.” This is rather peculiar because there isn’t any generic “Chinese cuisine.” Rather, there are regional cuisines, which share a broad family similarity. Similarly, American “Mexican food” and “Indian food” also have no true equivalent in Mexico or India (naturally the novel American culinary concoctions often exhibit biases in the regions from which they sample due to our preferences and connections; non-vegetarian Punjabi elements dominate over Udupi, while much authentic Mexican American food has a bias toward the northern states of that nation). But to a first approximation there is some sense in speaking of a general class of cuisine which exhibits a lot of internal structure and variation, so long as one understands that there is an important finer grain of categorization.
Some of the same applies to genetic categorizations. Consider two of the populations in the original HapMap, the Yoruba from Nigeria, and the Chinese from Beijing. There are ~30 million Yoruba, but over 1 billion Han Chinese! Even granting that the Yoruba seem excellent representatives of Sub-Saharan African genetic variation (not Bantu, but not far from the Bantu), there are still more Han Chinese than Sub-Saharan Africans (including the African Diaspora). So it’s nice that over the past few years there’s been a deep-dive into Han genetics. A new paper in the European Journal of Human Genetics focuses on the north-south difference among Han Chinese, using groups flanking them to their north and south as references, Natural positive selection and north–south genetic diversity in East Asia.
Are Empowered Women Driving Reduced Tolerance Of Extramarital Affairs?:
My girlfriend’s theory about this, which makes sense to me, is that as women’s labor market opportunities have improved their dependency on husbands for economic security has declined and, in turn, their willingness to put up with misbehavior has gone down. Looking at a gender breakdown of responses might shed some light on this, but I can’t figure out how to work the General Social Survey website.
He’s talking about a chart which shows decline in tolerance of extramarital sex by education:
I just replicated but broke it down by male and female:
Dienekes Pontikos has just released DIY Dodecad, a DIY admixture analysis program. You can . It runs on both Linux and Windows. Since I already have tools in Linux I decided to try out the Windows version, and it seems to work fine. It is somewhat limited in that you start out with the parameters which Dienekes has set for you, but if you don’t want to write your own scripts and get familiar with all the scientific programs out there, I think this is a very good option. Additionally, it seems to run rather fast, so you won’t spend days experimenting with different parameters.
Dienekes has already run me, but I put my parents’ genotype files through the system. Here are the results: