Rod Dreher at The American Conservative, White Working-Class ‘Seculars’:

What’s interesting to think about is that these working-class non-churchgoers are probably not secular in the same way white intellectual elites are secular. I bet if you polled them, 999 out of 1,000 would say they believed in God and considered themselves to be Christians. It’s just that they don’t go to church. Where I live, during deer hunting season, to be a white male is to be seasonally “secular” in this way.

One way to answer this question is look at the GSS. I used the ATTEND (attend church that is) variable to ascertain secularity. Those who never attended church or did so less than once a year (in other words, some years they did attend, in other years they did not), are “secular.” Those who attend nearly weekly, or more, are “religious.” To assess class I simply divided the non-Hispanic white population into those who had a college degree or higher (middle class), and those who did not (working class).

Below are some responses to a selection of questions.

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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).

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You may not have noticed, but Google has been spiffing up its Data Explorer. Poking around you see nice illustrations of phenomena which you otherwise may just read about. For example, Argentina has been one of the classic illustrations in economic history of stagnation. To a great extent it peaked around 1900, and development has been erratic since then. This is clear when you see how much its neighbors and other Latin American nations have caught up:

This bar graph illustrates it better:

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Prompted by Andrea Mitchell’s complaint that Iowa is not representative of America in racial terms the Audacious Epigone probed an American state’s typicality in terms of racial demographics, using the overall American population as a measure. One of the major issues with judging the typicality of a given state is that there is a great deal of residential segregation in even “diverse” regions. This comes up in our personal choices too. In 2008 ~10 percent of non-Hispanic whites married someone who was not a non-Hispanic white. Obviously more than ~10 percent of the population, particularly in the prime marrying demographic, are non-Hispanic whites, so you’re seeing a fair amount of homogamy. In some ways the homogamy is even more striking for minorities. ~31 percent of Asian Americans in this period married a non-Asian American. But, one has to keep in mind that using the American population as representative over 90 percent of the potential marriage partners are not Asian American!

The quest for a state that “looks like America” is understandable, but the reality of lived life is more complex. And not just in racial terms (e.g., the division in politics between the white suburbs of Maryland vs. Virginia on either side of D.C.). But keeping race in mind, one consistent finding in social science is that Americans actually tend to overestimate the number of minorities. Iowa is actually more typical than we think, despite the fact that it is not typical. In the year 2000 the General Social Survey asked respondents to estimate the number of various groups in the USA. The finding of a tendency to overestimate minorities, and underestimate non-Hispanic whites, was confirmed. But, I decided to break this down by demographic. The results are below in a table.

The first row are real counts from the 2000 Census. All the following rows are average estimates of a set of respondents in the year 2000.

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You probably know that the USA has officially withdrawn from Iraq. And you probably also know that in many ways Iraq became the de facto 51st American state for nearly a decade (I remember that my phone’s news app had an “Iraq” section back in 2007). Looking back 10 years ago I recall my attitude being “how bad could we mess this up?” I had expected a “Mouse that Roared” scenario, American investments would leave Iraq in a better position. In a general impressionistic sense I got the sense that I was drastically wrong, but over the past few years poking around Google Data Explorer it’s clear that you can make this case quantitatively too. Iraq just jumps out as a shockingly messed up country (the World Values Survey will also confirm that Iran is a much more enlightened country when measured by the yardstick of post-materialist values!).

Below is a taste of what I often see (I’ll keep life expectancy on the x-axis):

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With the collapse various North African regimes there has been a great concern about the migration of people from the southern shore of the Mediterranean to the northern. The of the reasons for this concern is that there is an imbalance in population growth. So I thought I’d review some of the data on Mediterranean nations over time using Google Data Explorer.

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A questioner below was curious if vocabulary test differences by ethnic and region persist across income. There’s a problem with this. First, the INCOME variable isn’t very fine-grained (there is a catchall $30,000 or greater category). Second, it doesn’t seem to control for inflation. But, there is a variable, DEGREE, which asks the highest level of education attained. I used this to create a “college” and “non-college” category (i.e., do you have a bachelor’s degree or not). Because of sample size considerations I removed some of the ethnic groups, but replicated the earlier analysis.

Below are two tables. One shows the mean vocab score for region and ethnicity (for whites) for those without college educations, and another shows those with college educations. I decided to generate a correlation over the two rows, even though it sure isn’t useful as a quantitative statistical measure because of the small number of data points. Rather, I just wanted a summary of the qualitative result. The short answer is that the average vocabulary difference seems to persist across educational levels (the exception here is the “German” ethnicity).

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Mike the Mad Biologist has a post up, A Modest Proposal: Alabama Whites Are Genetically Inferior to Massachusetts Whites (FOR REALZ!). The post is obviously tongue-in-cheek, but it’s actually an interesting question: what’s the difference between whites in various regions of the United States? I’ve looked at this before, but I thought I’d revisit it for new readers.

First, I use the General Social Survey. Second, I use the WORDSUM variable, a 10 question vocabulary test which has a correlation of 0.70 with general intelligence. My curiosity is about differences across white ethnic groups by region. To do this I use the ETHNIC variable, which asks respondents where their ancestors came from by nation. I omitted some nations because of small sample size, and amalgamated others.

Here are my amalgamations:

German = Austria, Germany, Switzerland

French = French Canada, France

Eastern Europe = Lithuania, Poland, Hungary, Yugoslavia, Russia, Czechaslovakia (many were asked before 1992), Romania

Scandinavian = Denmark, Norway, Sweden, Finland (yes, I know that Finland is not part of Scandinavia, Jaakkeli!)

British = England, Wales, Scotland

Next we need to break it down by region. The REGION variable uses the Census divisions. You can see them to the left. I combined a few of these to create the following classes:

Northeast = New England, Middle Atlantic

Midwest = E North Central, W North Central

South = W S Central, E S Central, South Atlantic

West = Pacific, Mountain

The key method I used is to look for mean vocabulary test scores by ethnicity and religion. I also later broke down some of these ethnic groups by religion. Finally, all bar plots have 95 percent confidence intervals. This should give you a sense of the sample sizes for each combination.

First let’s break it down by race/ethnicity and compare it by region to get a reference:

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The above results are from an Ipsos MORI from last summer. Please note, the opinions above are restricted only to those who asserted a religious affiliation. Obviously in Saudi Arabia this is irrelevant, as nearly the whole population has a religious affiliation. But it is important in Japan, because there nearly 2 out of 3 individuals in the survey reported no religion, so these are results from the minority who reported having an affiliation (mostly Buddhist). As they say, read the whole thing. Here are some conclusions I drew from these data:

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We’ll be talking about Iran a lot in the near future in the United States. I doubt we’ll invade the country (thank god). But one thing I think needs to be emphasized: on social issues Iran is more “progressive” than many of our close allies in the region, like Saudi Arabia, and one of the more progressive nations in the region. This is neither here nor there in the domain of geopolitics, but to convince a public about something it is often necessary to make a cartoon or caricature the enemy. I think it is important to remember though that aside from Israel our closest allies in the region are techno-feudal monarchies like Saudi Arabia, not those nations, like Iran, which have made a more thorough accommodation with modernity out of necessity (because oil can’t support the whole economy). It also reminds us that labels like “Islamic Republic” may not be totally useful.

As a gauge of modern outlook, as understood in the West, I poked around the World Values Survey. The results are for wave 4, around ~2000. The question asked was: A wife must always obey her husband. Possible answers:
- Agree strongly
- Agree
- Neither agree or disagree
- Disagree
- Strongly disagree

Below are two tables with nations which responded to this question. I stratified by sex and educational level of respondents. The sample sizes are in the “Total” column. The other numbers are percentages, summed along the rows to 100%. There are some surprises, but I’ll let the data speak for itself….

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In the post below I stumbled upon a weird datum. Kuwait’s total fertility is now below 3. The average estimates seem to be ~2.5 or so. This surprised me, as my impression was that Gulf Arab petroleum based states tended to encourage pro-natalism. This was both a matter of ideology, and also because the small and wealthy native populations lived off rents, and had not had to modify their neo-medieval ideologies to foster productivity driven economic growth. But perhaps Kuwait is an anomaly? Well, it turns out that the Saudi fertility rate is now below 3 as well. Again, depending on which numbers you trust a value of ~2.5 seems plausible. In 1980, at the peak of OPEC’s power and a period when Saudi Arabia was flush with incredible per capita wealth the fertility rate was north of 7.0. But even in the mid-1990s Saudi Arabia’s fertility remained a robust 5.0. Obviously one has to account for the fact that some of the “Arab” nations are not very Arab. The UAE has huge South Asian and Persian populations, not to mention all other sorts. So its fertility of 1.80 can be chalked up to its unique demographics. But would you have guessed that Lebanon’s fertility rate is now the same as Finland’s?

Below the fold is a chart which shows the trends among Arab nations and Finland over the past 40 years. The shading of the bars is proportional to life expectancy.

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Argentina has famously gone from being the 10th wealthiest to the 60th wealthiest nation in the world over the past 100 years. But I was curious about the trends for its neighbors as well in a world context.

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I wanted to clarify a few issues with the Census’ American Community Survey. These data come from the interval of 2006-2008, and they allowed me to query the proportional of various Latino/Hispanic groups who identified as white. I knew in the aggregate that the majority of America’s Latinos identified as white, but I was curious about two things:

1) The variation in white identification by group (by national origin)

2) The variation in white identification of Mexican Americans by selected states

Results below. There are stories in these data….

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With the current economic malaise in the developed economies and the rise of the “B.R.I.C.s” you hear a lot about “China” and “India.” There is often a tacit acknowledge that China and India are large diverse nations, but nevertheless in a few paragraphs they often get reduced to some very coarse generalizations. What’s worse is when you compare China and India to nations which simply aren’t on their scale. For example, over at Brown Pundits there is sometimes talk about India vs. Bangaldesh/Pakistan/Nepal/Sri Lanka. The problem is that the appropriate comparison are specific Indian states, not the whole nation. Uttar Pradesh, the largest Indian state in population, is actually in the same range as Bangladesh and Pakistan. Similarly, when comparing social metrics in Bangaldesh vs. India, one should focus on culturally similar regions, such as the state of West Bengal, not the sum average of India as a nation.

Similarly, we look at frenetic Chinese growth and worry about how they are “leaving us behind” (from an American perspective). But do take a step back to wonder how much the Chinese are leaving the Chinese behind?

Below are two charts which show the yawning chasm within these mega-nations on the scale of states (at a finer grain the variation is even greater). First a rank order of Chinese provinces by GDP PPP, with comparable nations interspersed within. PPP values shouldn’t be taken too literally, and the Chinese data seem to overestimate the values on a province level basis by 10-15%. But you get the general picture.

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I recently noted that the SDA Archive has an American Community Survey interface. The ACS has huge sample sizes because the US government can afford to do extensive surveys. And naturally you find some really interesting facts. For example, there’s a variable which tells you about the presence of grandchildren in the household. In some nations this wouldn’t be a big deal, but in the USA it is not too common. You can also look at this by state, which is what I did. Then I compared the total proportion to those limited with college degrees or higher. No surprise, those with college degrees tended to be less likely to have grandchildren living at home…. But can you guess which state has the highest proportion of grandchildren living at home? And which states deviate from the trendline? Surprises to me….

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