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Last week the GSS was down. I was very sad. The SDA team explains the situation:

Part of the popularity of our demonstration archive is that it is free for end users. We are happy to provide this service. It is a valuable resource for the academic community and it also publicizes the value of our SDA software. However, the flip side of providing this free service is that it does not generate any income to offset the cost of providing the infrastructure required. We receive no funding from GSS for hosting their datasets — which is often a surprise to our users. Almost all of our income comes from the fees provided by licensing the SDA software to other data archives (like ICPSR and IPUMS), and virtually all of that income goes to support the programming and technical support that we provide them. We obviously need some additional sources of revenue.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, GSS 
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Long time readers know that it’s trivially easy to extract information from the GSS that political moderates and independents are not as intelligent as partisans and ideologues. New readers are not always familiar. A comment:

#8 Do you have something to back up the idea that independents are less intelligent? If anything, I would’ve expected the opposite- that independents are capable of thinking for themselves instead of following the party line.

First, a quick review of the data. I used two GSS variables, PARTYID and POLVIEWS, and limited the sample to non-Hispanic whites after the year 2000. I removed those of “Other party” as well. Finally, I crossed that against vocab score results, which correlates with intelligence with a value of 0.70. It is rather obvious that middle-of-the-roaders are not as bright:

0-2 3 4 5 6 7 8 9 10
Strong Dem 15 8 13 9 10 12 14 15 20
Dem 17 24 14 15 15 13 14 15 15
Lean Dem 11 9 8 11 11 11 10 18 14
Independent 26 23 23 21 18 16 14 11 11
Lean Repub 10 8 12 10 8 12 13 10 12
Repub 15 21 18 21 21 20 18 16 13
Strong Repub 6 8 11 13 18 16 16 16 15
Extreme Liberal 5 3 2 2 1 4 3 4 7
Liberal 5 11 6 6 8 12 10 16 20
Lean Liberal 6 10 13 7 10 11 12 17 14
Moderate 44 45 44 43 39 33 30 28 24
Lean Conservative 21 12 13 18 16 18 18 14 16
Conservative 14 16 16 20 22 17 22 19 15
Extreme Conservative 5 4 5 3 4 6 3 2 3

As you can see the proportion in the middle decreases as you go up in intelligence. Why? A straightforward explanation is that independents and moderates are “low information” political actors. And therefore they are likely to be less intelligent in the first place. But there is I think another dynamic going on: the smart know where to go to reinforce their biases. That is, they’re far better at motivated reasoning, and become progressively more polarized and ideological.

My point is that the reality is on many topics very few of us ‘reason for ourselves.’ Rather, we trust certain people who know better. On economics smart liberals trust Paul Krugman, and smart conservatives trust Greg Mankiw. Not only are these individuals gifted with a specialized knowledge of economics in relation to the typical smart person, but they’re much smarter than average. That’s one reason I’m usually not interested in talking politics in detail with people: why not just go to the source that they’re garbling?

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: GSS 
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In the post below I took the time out to link to the GSS, as well as posting my exact queries. As payment for this consideration the first comment was absolute drivel. I understand people have political opinions, but I’m not too interested in your opinions. You may be interested in your opinions, but I’d rather have more data. Most people don’t know enough for me to have interest in their opinions (most != all, many readers do have opinions in their specialties which I seek out).

I was trying to make a point that anger and even violence in reaction to actions which offend are actually comprehensible as the modal human response. The community reacts to punish those who violate taboos. The taboos may differ, but the response to the action of violation is normal and natural. A primary issue that needs to be considered is that taboos differ from society to society, so one is often not conscious of the act of violation (e.g., if you show the bottom of your shoes to people when you sit down, that’s an offensive act in some societies).

An implication here is that American norms of free speech near absolutism, enforced through the fiat of the courts because of their interpretation of the applicability of the Bill of Rights, are radically non-intuitive to most people. The only reason that they are intuitive to many Americans is that we are acculturated over time. This is clear when you look at differences of intelligence and education. In short, less intelligent and educated Americans are much more skeptical of allowing social deviants to speak. This is true even in cases where they are more likely to agree with the deviant in question (e.g., these groups have a more pro-military bent, and yet are more accepting of the concept of censure of pro-military opinions).

I have limited all the results to the year 2000 and later. Additionally, I classify those who score 0-4 on the WORDSUM vocab test as stupid, those who score 5-8 as average, and those who score 9-10 as smart. WORDSUM has been reported to have a 0.7 correlation with general intelligence. In this data set 20% of individuals scored 0-4, 69% 5-8, and 12% 9-10.

Stupid Average Smart
Allow racist to speak 52 60 84
Allow homosexual to speak 74 86 98
Allow militarist to speak 51 67 93
Allow communist to speak 51 68 95
Allow atheist to speak 64 79 97
Allow Muslim to preach hatred of America 25 41 74

I wanted to repeat the logistic regression I did earlier, this time with more variables. If you care, they are: SPKRAC, SPKHOMO, SPKMIL, SPKCOM, SPKATH

Allow group to speak
Communist Racist Homo Militarist Atheist
B Prob B Prob B Prob B Prob B Prob
SEX 0.279 0.01 0.331 0.00 -0.209 0.11 -0.062 0.53 0.282 0.01
AGE 0.012 0.00 0.008 0.00 0.019 0.00 0.021 0.00 0.017 0.00
SEI -0.004 0.18 -0.003 0.29 -0.009 0.05 -0.013 0.00 -0.011 0.00
DEGREE -0.366 0.00 -0.119 0.02 -0.267 0.00 -0.108 0.06 -0.138 0.04
WORDSUM -0.229 0.00 -0.139 0.00 -0.276 0.00 -0.204 0.00 -0.228 0.00
RACE(Recoded) 0.068 0.58 0.021 0.86 -0.096 0.54 0.29 0.02 0.078 0.55
HISPANIC(Recoded) 0.419 0.01 0.876 0.00 0.173 0.36 0.49 0.00 0.463 0.00
GOD 0.194 0.00 0.176 0.00 0.233 0.00 0.149 0.00 0.228 0.00
POLVIEWS 0.025 0.50 0.07 0.04 0.227 0.00 0.079 0.03 0.103 0.01

Most of you may not know the GSS codes for variables, but I do, so I will tell you what the above means. For sex 1 = male and 2 = female. And 1 = allow speech, and 2 = disallow. Therefore, you see that women are more skeptical of free speech for communists, racists, and atheists. Additionally, this skepticism is statistically significant. In contrast, they more supportive of free speech for homosexuals and militarists than men. These results are on the border of significance, but in general women support gay rights more robustly than men, so I think we can accept that.

For age the values are straightforward. Older people have higher values. There isn’t a strong trend. Similarly with socieconomic index. The magnitudes for the beta are not high because intelligence and education probably is what is really driving the socioeconomic differences. And as you can see in every case people with more education or a higher intelligence are more supportive of free speech. These are the people who run American society. I’m intrigued that when accounting for background variables non-whites don’t seem particularly supportive of restraints on the speech of racists. In contrast, Hispanics seem definitely much more skeptical of free speech. Finally, being more religious and more conservative also tends to result in more support for censorship. Note that this is the case even in the situation where the very religious and conservative are more likely to support the outlined deviant position, militarism.

On a deep philosophical level what this is asking is whether the community has the right to restrain the speech of individuals. Historically, and to a great extent internationally, the answer is yes. Particular universal ideals of individual liberty which have expanded in scope since the 18th century have started to challenge this assumption, but even within Western societies there are substantial minorities who hew with the older ways.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, GSS, Speech 
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Obviously the news over the past week has been filled with the events in the Middle East, and the broader Muslim world, in reaction to an anti-Muslim film. I think the most eloquent commentary is from The Onion (NSFW!!!), No One Murdered Because Of This Image. That being said, there are some serious broader issues here. A friend of mine who lives in India (he is Indian American, though raised for several years in India, so not totally unfamiliar with the culture) has expressed to me his frustration with having to defend American liberalism in a society where American liberalism is an abstraction, rather than concrete. The frustration has to do with the fundamental divergence in basic values. For example, his interlocutors have argued to him (he is a practicing Christian of libertarian political orientation) that if someone committed an act of blasphemy against his faith of course he would react in anger and violence. And yet of course the clause “and” is false, though he is greeted with skepticism when he asserts he wouldn’t react violently. As a matter of fact I can attest to the reality that he wouldn’t react angrily necessarily, because in interactions where I’ve made casually blasphemous comments he’s only rolled his eyes. Just as Americans have a vague, even misleading, understanding of the broader historical forces which engender resentment of American hegemony in the broader world, so many non-Americans lack a proper awareness of the broader historical forces, and cultural reality, of the particular American radicalism and extremism in the domain of free expression.

I say radicalism and extremism because that is exactly what free speech near absolutism is. Over the course of human history blasphemy has been understood to be unacceptable in most human societies, and often entails extreme sanction. The American, and to a lesser extent Western, elevation of liberty of speech over the sacred values of the community is a peculiar counter-cultural trend which has become normative. But that doesn’t mean that it’s normal or natural. I stipulate here the term “sacred values of the community,” because though blasphemy connotes violations of religious norms, obviously outrage can be triggered by violations of sacred communal norms more generally. Imagine, for example, if someone violated Lenin’s Tomb during the 1950s in the Soviet Union. Jonathan Haidt has alluded to this issue. Someone who reacts calmly to “Piss Christ” might not react so calmly to “Piss Martin Luther King.”

This points to the second issue. Not only is there is a human universal of offense at violation of sacred norms, but those sacred norms vary from culture to culture. So, for example, I have pointed out to followers of the Abrahamic religions that the core documents of their own faiths and the dominant interpretations are often gravely offensive and hostile toward those of other religious traditions. There is a certain incommensurability of offense across cultures. What may be sacred to one culture may be offensive and blasphemous to another. To give an example, the institutions of sacred prostitution has cropped up repeatedly over human history. Many religious people would consider prostitution in the service of gods or God blasphemous, whereas others might consider it an exalted act. Similarly, blood sacrifice, whether of humans or animals, has been central to many religions, and taboo and blasphemy in the context of others. In contrast to this there are acts and violations which seem relatively universal in interpretation. This is clear when offended people make analogies to insulting one’s mother; this is generally communicable across societies, because emotional family ties are fundamental. And the collective paroxysms of rage, anger, and violence, due to violations of communal honor probably draw from the same cognitive reflexes as those which are triggered by violations of family honor.

But let’s put the shoe on the other foot here. Would Americans tolerate anti-American preaching from Muslim clerics in this country? We can explore this with the General Social Survey with the SPKMSLM variable. It asks:

Now consider a Muslim clergyman who preaches hatred of the United States.

If such a person wanted to make a speech in your community preaching hatred of the United States, should he be allowed to speak, or not?

The question was asked in 2008 and 2010. Since the sample sizes are large I’ll limit to non-Hispanic whites first.

Now in tabular format.

Non-Hispanic whites, 2008 & 2010
Demographic Allow Muslim clergymen to preach hatred of US
Male 52.6
Female 39.7
< HS 19
High School 38.2
Junior College 45.3
Bachelor 62.5
Graduate 71.6
Stupid 28
Average 43.7
Smart 73.6
Liberal 59.9
Moderate 40.6
Conservative 43.6
18-34 years old 49.3
35-64 years old 48.5
65-* years old 33.4
Protestant 40.7
Catholic 43.6
Jewish 45.7
No religion 61.1
Word of God 26.6
Inspired Word of God 48
Book of Fables 66.1

The exact row variables in the GSS:

SEX DEGREE WORDSUM(r:0-4″Stupid”;5-8″Average”;9-10″Smart”) POLVIEWS(r:1-3″Liberal”;4″Moderate”;5-7″Conservative”) AGE(r:18-34;35-64;65-*) RELIG BIBLE

I then decided to run a logistic regression. I wanted to see which variables predict attitudes toward speech on this issue. I expanded the data set to include Hispanics and non-whites.

Below positive values in the “B” column include opposition to allowing a Muslim cleric preach. Therefore, a negative value favors freedom of speech in this case.

B SE(B) Probability
SEX 0.484 0.156 0.002
AGE 0.008 0.005 0.084
SEI -0.01 0.005 0.041
REALINC 0 0 0.43
DEGREE -0.289 0.082 0
WORDSUM -0.301 0.05 0
RACE(Recoded) -0.059 0.229 0.795
HISPANIC(Recoded) 0.843 0.333 0.012
GOD 0.145 0.057 0.012
POLVIEWS 0.075 0.055 0.176
Log Likelihood = -533.697
Pseudo R-sq = 0.151

What’s striking to me is that once you account for education and intelligence, income and socioeconomic status don’t matter. That makes sense since the former are related causally to the latter. The sex difference here is pretty robust. Once you account for other variables race is not so important, but Hispanic identity is. I would suggest here that assimilation to American values is the determining factor, but nativity (BORN variable) doesn’t seem to matter when I checked. It is not surprising to me that political ideology (very liberal to very conservative) doesn’t matter when you account for other variables, especially religion. Well educated conservatives who are not religious tend toward social libertarianism. So once you account for religion and education, ideology isn’t as predictive, similar to race.

There are other similar variables in related to free speech. One pattern is clear. American cultural elites are particularly protective of free speech, while the lower orders tend to have attitudes which are more “relaxed,” and would be more in keeping with other parts of the world. Why? One can imagine many reasons, but this republic was founded by prominent and powerful men who were traitors, and who valued their own personal individual liberty. This is not an uncommon tendency; liberty of thought has been one of the privileges of aristocracy throughout human history. One aspect of ancient Greek democratic populism which rankled aristocrats was that the community might censor and restrain the freedoms of those who traditionally had more license to violate communal norms.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Anthropology, Geography, GSS 
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It’s basically impossible to avoid hearing about Todd Akin right now. My Twitter and Facebook feeds are kind of swamped. But it did make me wonder: what percentage of Americans reject abortion in cases of rape and incest? The GSS has a handy variable, ABRAPE, which asks respondents about the possibility of abortion if a woman gets pregnant as a result of rape (let’s stipulate that it’s possible to get pregnant as a result of rape!). I also limited the sample to the year 2000 and later, and non-Hispanic whites (to clear out confounds). Demographic breakdowns below….

Before people start complaining, the scale below goes from 0% to 50%, NOT 0% to 100%!


(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Abortion, Data Analysis, GSS 
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Long time readers know that one of my pet hobby-horses is to try and convince more pundits that they should use the GSS. Opinions based on opinions may be fun, but opinions based on facts may be useful. In general my appeals have fallen on deaf ears. But today I notice that Will Saletan is using GSS data to discussion the Todd Akin case. You may not agree with Saletan’s take on the results, but at least he bothered to generate some results.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, GSS 
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Reihan Salam has a post up on the alignment of racism and political orientation. He begins:

Recently, Chris Hayes, host of MSNBC’s UP with Chris Hayes, made the following observation:

It is undeniably the case that racist Americans are almost entirely in one political coalition and not the other.

Chris is a good friend of mine, and we grew up in the same milieu. I can attest to the fact that the view he expressed is very widely held in the circles in which we both travel….

Salam then links to Alex Tabarrok, who uses party identification data to indicate that actually racism is split between the two groups, while John Sides suggests that there is a definite lean toward Republicans being more racist, using a few indicator variables. Overall I think Sides is about right, all things equal conservatives are more racist than liberals. At least in the modern context of the two ideologies.* I say conservative/liberal rather than Republican/Democrat, because my experience with the GSS data set is that ideology is a more powerful predictor of social views among whites. This holds true with the variables which Tabarrok and Sides query from what I can see; the gap between Democrats and Republicans is smaller than between liberals and conservatives. Why? There are still a non-trivial number of self-identified conservative Democrats in this country, as well as very well off socially moderate Republicans who vote their economic interests.

Before further analysis, I do want to admit one thing: “racism” is a subjective term to a great extent. I say this because there are very few Americans left who will defend legal segregation and white supremacy. At the other extreme there are some Democrats and liberals who would claim that opposition to affirmative action is racism. That seems too far. Between the two are a whole host of views ad positions, and there is dispute where to draw the appropriate line. But no matter where you draw the line there does seem a robust difference between white liberals and conservatives. The only key issue is that the difference, even if consistent, is often not very great. Sides and Tabarrok seem to have the right of it in relation to Hayes.

What I think is going on with Hayes’ assertion is similar to what’s going on with social conservatives who talk about “pro-family” views and attitudes. Very few liberals are “anti-family” (though some Leftist radials arguably are, insofar as they want to overturn normative understandings of the American family). And yet similarly very few conservatives are “pro-racism.” Rather, the terms have become implicit code among conservatives and liberals for opinions on a wide range of family and race related issues. Even if conservatives don’t live the pro-family agenda (e.g., Newt Gingrich), they believe in it. Similarly, even if white liberals live among, socialize, and marry, other white liberals, they believe in a particular vision of race relations. More concretely, conservatives who label themselves pro-family support a suite of policies which they presume support the values of families, even if their own families are a shambles. Liberals who oppose racism in Vermont or rural Oregon do so through their support for particular policies which they believe foster national racial equality.

But to some data. Replicating John Sides’ results with ideology, for non-Hispanic whites after the year 2000:

But I wanted to take the analysis just a little further than Sides. First, what about segregation in one’s personal life?


I did find a variable where there was a strong difference between whites by ideology:

These results prompted me to look for some literature in this domain. Here’s what I found, Is Love Colorblind? Political Orientation and Interracial Romantic Desire:

As shown in Figure 2, the probability that a White participant at 1 SD toward the liberal end of the spectrum would say “yes” to a Black speed-dater was approximately 26%, whereas the probability that a White participant at 1 SD toward the conservative end of the spectrum would say “yes” to a Black speed-dater was approximately 16%.

I think these results encapsulate the truth which Chris Hayes’ elided: a tendency toward racial whites consciousness, whether explicit or implicit, increases the odds that one is conservative (and vice versa), but it does not guarantee that one is conservative.

* There was a time in the 19th century where being racialist was the more progressive ideology.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, GSS, Interracial, Racism 
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Prompted by a comment below I was curious as to the correlation between intelligence and income. To indicate intelligence I used the GSS’s WORDSUM variable, which has a ~0.70 correlation with IQ. For income, I used REALINC, which is indexed to 1986 values (so it is inflation adjusted) and aggregates the household income. Finally, I limited my sample to non-Hispanic whites over the age of 30 (for what it’s worth, this choice also limited the data set to respondents from the year 2000 and later).

The results don’t get at the commenter’s assertions, because 10 out of 10 on WORDSUM does not imply that you’re that smart really. But the trendline is suggestive. Note that aggregated 0-4 because the sample size at the lower values is small indeed.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data, Data Analysis, GSS, IQ 
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A few years ago I put up a post, WORDSUM & IQ & the correlation, as a “reference” post. Basically if anyone objected to using WORDSUM, a variable in the General Social Survey, then I would point to that post and observe that the correlation between WORDSUM and general intelligence is 0.71. That makes sense, since WORDSUM is a vocabulary test, and verbal fluency is well correlated with intelligence.

But I realized over the years I’ve posted many posts using the GSS and WORDSUM, but never explicitly laid out the distribution of WORDSUM scores, which range from 0 (0 out of 10) to 10 (10 out of 10). I’ve used categories like “stupid, interval 0-4,” but often only mentioned the percentiles in the comments after prompting from a reader. This post is to fix that problem forever, and will serve as a reference for the future.

First, please keep in mind that I limited the sample to the year 2000 and later. The N is ~7,000, but far lower for some of variables crossed. Therefore, I invite you to replicate my results. After the charts I will list all the variables, so if you care you should be able to replicate displaying all the sample sizes in ~10 minutes. I am also going to attach a csv file with the raw table data. As for the charts, they are simple.

- The x-axis is a WORDSUM category, ranging from 0 to 10

- The y-axis is the percent of a given demographic class who received that score. I’ve labelled some of them where the chart doesn’t get too busy

All of the charts have a line which represents the total population in the sample (“All”).


The “Row” variable in all cases was WORDSUM. I put in YEAR(2000-*) in “Selection Filter(s).”

For the columns:

Sex = SEX

Race/ethnicity = For non-Hispanic blacks and whites put HISPANIC(1) in the filter. Then RACE. For Hispanics just limiting the sample to Hispanics will do, HISPANIC(2-*). Nothing in the row needed.

Education = DEGREE

Region = REGION

Political ideology = POLVIEWS(r:1-3″Liberal”;4″Moderate”;5-7″Conservative)

Political party = PARTYID(r:0-2″Democrat”;3″Independent”;4-6″Republican”)

Belief in God = GOD(r:1-2″Atheist & agnostic”;3-5″Theist”;6″Convinced Theist)

Religion = RELIG

Opinion about Bible = BIBLE

Income standardized to 1986 = REALINC(r:0-20000″0-20″;20000-40000″20-40″;40000-60000″40-60″;60000-80000″60-80″;80000-100000″80-100″;100000-120000″100-120″;120000-140000″120-140″;140-*”140-”)

Wealth = WEALTH(r:1-3″”)

Evolution = EVOLVED

You can find the raw table here.

(Republished from Discover/GNXP by permission of author or representative)
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Update: There was a major coding error. I’ve rerun the analysis. No qualitative change.

As is often the case a 10 minute post using the General Social Survey is getting a lot of attention. Apparently circa 1997 web interfaces are so intimidating to people that extracting a little data goes a long way. Instead of talking and commenting I thought as an exercise I would go further, and also be precise about my methodology so that people could replicate it (hint: this is a chance for readers to follow up and figure something out on their own, instead of tossing out an opinion I don’t care about).


Just like below I limited the sample to non-Hispanic whites after the year 2000. Here’s how I did it: YEAR(2000-*), RACE(1), HISPANIC(1)

Next I want to compare income, with 1986 values as a base, with party identification. To increase sample sizes I combined all Democrats and Republicans into one class; the social science points to the reality that the vast majority of independents who “lean” in one direction are actually usually reliable voters for that party. So I feel no guilt about this. I suppose Americans simply like the conceit of being independent? I know I do. In any case, here are the queries:

For row: REALINC(r:0-20000″LLM”;20000-40000″M”;40000-80000″UM”;80000-*”BU”)
For column: PARTY(r:0-2″Dem”;3″Ind”;4-6″Rep”)

What I’m doing above is combining classes, and also labeling. The GSS has documentation to make sense of it if you care. Some of you were a little confused as to what $80,000 household income in 1986 means. I went and converted 1986 dollars to dollars today.

Value of income conversion
1986 2012
$20,000 $42,000
$40,000 $83,000
$80,000 $166,000


As you can see $80,000 in 1986 would be $166,000 today. So what percentile in household income is $166,000? Here it is (I rounded generously, so it is really 43 or 93 and such, instead of 40 or 95):

Income range Quantitative class Descriptive class
Up to $20,000 < 40% Lower & Lower Middle (LLM)
$20,000 to $40,000 40% to 70% Middle (M)
$40,000 to $80,000 70% to 95% Upper Middle (UM)
$80,000 and up > 95% Broad Upper (BU)

To clear up future confusions I have relabeled the income ranges with the descriptive classes above. You can argue all you want that being in the ~5% of income is not upper class, but just pretend I used a different term (e.g., higher middle class?). I’m not too hung up on the terminology, I’m more focused on the people in the top 5% of the income distribution. The local doctor or successful business person, not the billionaire who owns an island in the Caribbean.

Now you have a sense of the classes which we’ll be looking at. In the results below I report the proportions of the row and column values. So the leftmost three columns will tell you the percentage of Democrats who are upper class, while the rightmost three columns will tell you the percentage of upper class people who are Democrats. The leftmost three columns add up to 100% vertically, the rightmost three columns 100% horizontally.

The second major aspect of reading the table below is that I “controlled” for various sets of characteristics. So, for example, you see the income and party identification patterns for those with no college education, and those with college educations. Here are the variables:

DEGREE(r:0-2″No College”;3-4″College”), BIBLE, REGION(r:1-4,8-9″Not South”;5-7″South”), SEI

Two notes here. First, I used the Census division categories. Second, the “socioeconomic status index” is more than just income, and I created three broad classes, giving you the percentile ranges.

Columns = 100% Rows = 100%
Dem Ind Rep Dem Ind Rep
LLM 42 51 33 40 24 33
M 28 27 28 37 18 45
UM 21 16 27 35 13 53
BU 8 6 11 34 11 55
No College
Dem Ind Rep Dem Ind Rep
LLM 51 55 39 39 26 35
M 29 27 31 36 20 44
UM 16 14 24 31 16 53
BU 4 3 6 28 15 57
Dem Ind Rep Dem Ind Rep
LLM 24 28 19 45 13 42
M 25 28 24 42 11 47
UM 32 25 35 40 8 35
BU 19 19 22 38 9 53
Bible is Word of God
Dem Ind Rep Dem Ind Rep
LLM 63 61 39 35 22 44
M 27 28 32 24 16 59
UM 10 10 23 16 10 75
BU 1 2 5 7 11 82
Bible is Inspired of God
Dem Ind Rep Dem Ind Rep
LLM 37 49 28 41 23 36
M 31 29 29 41 16 43
UM 24 17 29 37 11 52
BU 8 5 14 30 8 62
Bible is Book of Fables
Dem Ind Rep Dem Ind Rep
LLM 37 51 28 51 29 28
M 25 22 24 53 20 24
UM 23 20 30 50 17 30
BU 15 7 18 55 11 34
Not the South
Dem Ind Rep Dem Ind Rep
LLM 40 50 28 41 24 35
M 27 27 28 39 18 43
UM 23 17 28 38 13 49
BU 10 6 11 39 12 49
The South
Dem Ind Rep Dem Ind Rep
LLM 47 54 33 39 23 33
M 29 28 29 35 17 48
UM 18 14 27 28 11 60
BU 6 4 12 23 9 67
Bottom 50% of socioeconomic status
Dem Ind Rep Dem Ind Rep
LLM 55 59 44 40 27 33
M 28 27 30 36 23 41
UM 14 11 21 32 17 51
BU 4 3 5 34 17 49
40% to 10% of socioeconomic status
Dem Ind Rep Dem Ind Rep
LLM 34 38 26 40 19 41
M 31 30 29 38 14 47
UM 26 24 31 33 13 54
BU 9 7 15 28 10 62
Top 10% of socioeconomic status
Dem Ind Rep Dem Ind Rep
LLM 18 28 17 43 14 43
M 24 27 24 41 11 48
UM 30 20 34 40 6 53
BU 26 25 25 42 9 48
(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data, Data Analysis, Demographics, GSS, Politics 
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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).

Mean WORDSUM Score by Ethnicity and Region
No college education




German 6.05 5.81 5.79 6.11
Eastern Europe 6.17 6.16 6.18 6.29
Scandinavian 6.35 5.97 6.23 6.35
British 6.6 6.21 6.02 6.57
Irish 6.66 5.83 5.69 6.58
Italian 6 5.85 5.8 6.18
College educated




German 8.03 7.48 7.63 7.33
Eastern Europe 7.7 7.37 7.5 8.09
Scandinavian 8.5 7.82 7.86 7.92
British 8.44 8.06 7.76 7.95
Irish 8.03 7.79 7.39 7.59
Italian 7.45 7.75 7.6 7.87
Correlation of college and non-college
German 0.08
Eastern Europe 0.92
Scandinavian 0.57
British 0.70
Irish 0.57
Italian 0.40
(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data, Data Analysis, GSS, I.Q., Regionalism 
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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:

Next, the main course:

Finally, let’s separate by religion for Germans and Eastern Europeans:

I include the last plot because these reports of nationality have to be taken with a consideration for the structure they may mask. People whose ancestors from Poland in the United States fall into two large categories: people of Jewish heritage whose identity as ethnic Poles was contested (recall that Jews often spoke Yiddish as their first language, a Germanic language), and Roman Catholic Slavs. I suspect many of those in the “None” category are also Jews by culture, if not religion.

Second: there is a tendency of people of all ethnic groups to have lower vocabulary scores if they are from the South or Midwest. This tendency is in many cases outside of the 95 percent confidence interval. It’s especially striking in the three groups with huge samples sizes in all regions: Germans, Irish, and British. Irish here includes both Scots-Irish and those of Irish Catholic background. Not only are the sample sizes for these groups large, but the roots of these groups in some of these regions go rather far back. In particular, the division between the people of British ancestry goes back centuries in the North vs. South divide.

How to understand this? There are a lot of complicating factors. But as outlined in Albion’s Seed and The Cousins’ Wars the divisions between the Anglo-Celtic folkways runs deep and long. If a time traveler from the 18th century arrived in the United States today and were asked which region was the heart of intellectual ferment they would correctly guess New England. Early Puritan New England was the first universal-literacy society in the world. This was to some extent a matter of conscious planning. The leaders of the New England colonies enforced limitations upon who could emigrate to their dominion. Religious exclusions and persecutions in this region are well known, but there was also a policy of rejecting the settlement of those who were perceived to be possible burdens upon the community. New England then selected for a middle class migration out of East Anglia and the port towns of southwest England. But the fathers of the early colony also rejected the transfer of the privileges of the blood nobility from the motherland, thereby throwing up a barrier to the migration of the aristocracy.

In contrast the lowland South received a more representative selection of the British class strata. The younger sons of the British nobility and self-styled gentlemen arrived to make their mark, as did those who became indentured servants and even slaves. A class society on the model of southwestern England recapitulated itself in this region. As for the uplands, what became Appalachia, an influx of Scots-Irish came to dominate the scene by the mid of the 18th century, disembarking in Philadelphia, and pushing down the spine of the high country down to the Deep South.

Conflicts between these “Anglo” groups framed the terms of debate over the 18th and 19th centuries. They were to some extent at the root of the Age of Sectionalism. Today because of the salience of race, and the prominence of the later wave of migration in the late 19th and early 20th century which remained vibrant in living memory for mod, these early divisions have moved out of sight. But they still remain. The difference between Germans in Texas and the Anglos of Southern extraction remains to this day, but note that Germans exhibit the same regional differences in vocabulary score as Anglos. Why? This may be a case where the original cultural substratum has an outsized impact (the dialect of eastern New England, made famous by the Catholic Irish of Boston, is descended from East Anglian English!).

Of course there might be a genetic difference. Intelligence is a quantitative trait, so it would be trivial to generate two populations which are genetically similar, but very different in trait value, simply through selection. In the 1630s ~20 thousands Puritans settled New England. For various reasons there was very little migration over the next century and a half. By 1780 New England’s population was 700,000, almost all through natural increase (not only was New England the world’s first universal literacy society, but its fertility was the highest in the late 17th century).

Finally, there’s the issue of disease and pathogen load. Endemic hookworm infection does seem likely to have made Southerners, of both races, relatively indolent and lethargic in comparison to Northerners. Who knows what pathogens simply fall below our radar?

Overall I think that a more fine-grained and detailed exploration of these topics is warranted. Our public discussion is too coarse, and data-thin.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, Demographics, GSS, WORDSUM 
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There’s a variable in the GSS, GENESELF, which asks:

Today, tests are being developed that make it possible to detect serious genetic defects before a baby is born. But so far, it is impossible either to treat or to correct most of them. If (you/your partner) were pregnant, would you want (her) to have a test to find out if the baby has any serious genetic defects?

This is relevant today especially. First, the technology is getting better and better. Second, couples are waiting longer to start families. Unfortunately this question was only asked in 1990, 1996, and 2004. But on the positive side the sample sizes were large.

I decided to combine 1990 and 1996 into one class. Also, I combined those who were very liberal with liberals, and did the same for conservatives. For political party ideology I lumped strong to weak identifiers. For intelligence I used WORDSUM. 0-4 were “dull,” 5-7 “average,” and 8-10 “smart.” For some variables there weren’t results for the 1990s.

The biggest surprise for me is that there wasn’t much difference between the 1990s and 2004. The second biggest surprise was that the differences between demographics were somewhat smaller than I’d expected, and often nonexistent. Below is a barplot and table with the results.


Yes to fetal genetic tests by demographic
Demographic 1990s 2004
Male 69 67
Female 68 65
White 67 65
Black 79 72
Hispanic * 71
Less than HS 72 67
High School 68 65
Junior College 64 69
Bachelor 71 65
Graduate 69 71
Protestant 69 65
Catholic 62 63
Jewish 95 78
No Religion 78 69
Dull 74 71
Average 65 65
Smart 71 66
Liberal 80 77
Slight Liberal 70 64
Moderate 70 69
Slight Conservative 68 66
Conservative 59 52
Democrat 73 74
Independent 69 67
Republican 65 58
Yes to abortion on demand 80 75
No to abortion on demand 61 56
Bible Word of God 63 61
Bible Inspired Word 68 65
Bible Book of Fables 82 75
Evolution definitely true * 81
Evolution probably true * 70
Evolution probably not true * 67
Evolution definitely not true * 58





(Republished from Discover/GNXP by permission of author or representative)
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One of the things I’m interested in is the perception by some that self-identified conservatives can mobilize better as a collective unit on the American political scene. To test that proposition I often poke around the General Social Survey. For example, it seems to be a common assumption among many liberals that women tend to be more supportive of abortion rights than men. This isn’t born out by the GSS data. There’s no sex difference. Until you correct for ideology. It turns out that among liberals women are more supportive of abortion rights…while among conservatives men are more supportive of abortion rights! If people socialize only with their own ideological subset then the perception of the relationship between sex and ideological opinions will differ a great deal.

Below I decided to attempt to ascertain differences between liberals and conservatives on “hot button” issues as a function of intelligence. I used WORDSUM to probe this. I classed those who scored 0-5 as dull, those who scored 6-8 as not dull, and those who scored 9 and 10 as smart. I also limited the sample to the year 2000 and later, and only non-Hispanic whites.

I’ll give you the results without comment.


Liberals Conservatives
Abortion for any reason acceptable
Yes Yes
Dull 46 29
Not Dull 65 27
Smart 79 26
Homosexual relations
Always wrong Always wrong
Dull 52 78
Not Dull 15 70
Smart 7 57
Ban Bible prayer in schools
Approve Approve
Dull 39 28
Not Dull 65 36
Smart 85 54
Allow anti-religionist to speak
Yes Yes
Dull 73 69
Not Dull 93 82
Smart 99 96
Humans developed from animals
Yes Yes
Dull 53 44
Not Dull 79 33
Smart 94 51
Belief in God
Atheist & agnostic Atheist & agnostic
Dull 6 5
Not Dull 21 4
Smart 31 9
Trade took away American jobs
Yes Yes
Dull 29 39
Not Dull 36 41
Smart 11 11
College educated
Yes Yes
Dull 11 16
Not Dull 40 33
Smart 72 59
(Republished from Discover/GNXP by permission of author or representative)
• Category: Ideology, Science • Tags: General Social Survey, GSS, Politics 
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In the comments below a weird fact came to light: it does not seem that liberal/Democrat reduced skepticism toward astrology vs. conservatives/Republicans can be explained just by a secularization, and therefore diminished Christian orthodoxy. There are two reasons for this. First, on a priori grounds most people are religious, liberals and conservatives. The difference between the religious and irreligious on this issue would have to be rather large, and the different apportionment across ideology to be striking, for it to drive the division which seems so robust. Second, within the results it seems rather clear that the gap between liberals and conservatives is most evident amongst the religious of both! In other words, secular liberals and conservatives tend to agree (and be skeptical) in relation to astrology. While religious conservatives are skeptical of astrology, as one would expect from orthodox conservative Christians, religious liberals are not. The table below shows some results.

Astrology is…. Very scientific Sort of scientific Not at all scientific
Protestant Liberal 5 31 64
Conservative 5 18 77
Catholic Liberal 3 35 62
Conservative 6 25 69
No religion Liberal 6 22 72
Conservative 9 31 60
Atheist & agnostic Liberal 7 19 74
Conservative 3 22 75
Believe in higher power Liberal 3 26 71
Conservative 3 31 66
Believe in god sometimes Liberal 1 28 71
Conservative 19 18 63
Believe in god with doubts Liberal 3 29 68
Conservative 3 20 77
Know god exists Liberal 6 35 59
Conservative 6 21 73
Southern Baptist Liberal 11 33 56
Conservative 7 16 77
United Methodist Liberal 4 13 83
Conservative 4 23 73
Episcopal Liberal 4 23 72
Conservative 5 16 80
Bible is Word of God Liberal 8 41 51
Conservative 6 22 72
Bible is Inspired Word of God Liberal 5 28 67
Conservative 5 21 74
Bible is Book of Fables Liberal 3 23 73
Conservative 8 21 71
Humans developed from animals Liberal 4 25 71
Conservative 8 25 67
Humans did not develop from animals Liberal 7 37 56
Conservative 5 16 79

Observe the huge difference between Creationist and fundamentalist liberals and conservatives!

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Astrology, Data Analysis, GSS 
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Someone on twitter was curious about GOP attitudes toward astrology. I left the party breakdown out of the previous post because ideology accounts for most party differences. In other words, conservatives are more skeptical of astrology than liberals, and Republicans more than Democrats, but the second result just seems to emerge from the Republican’s greater conservatism.

Astrology very scientific Astrology somewhat scientific Astrology not scientific
Strong Democrat 6 31 63
Democrat 7 30 63
Lean Democrat 4 28 67
Independent 7 37 57
Lean Republican 3 26 71
Republican 4 21 75
Strong Republican 4 20 76

Why are independents so gullible? It probably has to do with their lower average intelligence (this goes for moderates too). So I simply limited the sample to those with at least bachelor’s degrees to control for intelligence:

Limited to those with college degrees or more
Astrology very scientific Astrology somewhat scientific Astrology not scientific
Strong Democrat 3 21 76
Democrat 4 17 79
Lean Democrat 2 21 78
Independent 4 22 75
Lean Republican 1 9 90
Republican 0 11 88
Strong Republican 1 10 89

The distinctiveness of independents diminishes somewhat, but Democrats with college degrees or more remain more gullible than Republicans with the same (the difference remains if you control for sex by the way).

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Astrology, Data Analysis, GSS 
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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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At Culture of Science there’s a little discussion about whether acceptance of evolution indicates intelligence. Looking at the GSS data there doesn’t seem to be a strong causal relationship when you control for other variables. But there is a correlation. That correlation can be explained by the fact that, for example, people who are Biblical literalists tend to be duller than those who are not, and Biblical literalists don’t accept evolution (in fact, I’ve seen evidence that very intelligence Biblical literalists are more Creationist than their duller co-religionists, probably because they’re more coherent in their beliefs).

With that, I’ll leave you with a screenshot of the results for WORDSUM, a 10 word vocabulary test, against acceptance or rejection of human evolution from other organisms (note that the numbers below the proportions are weighted sample sizes):

The real divergence is at the super high end of intelligence.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Creationism, Data Analysis, Evolution, GSS 
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I few years ago I complained that no one was using the General Social Survey web interface for blogging, a practice which probably can be traced back to the Inductivist (yes, social scientists use the GSS constantly, but they use it to publish papers, not blog posts). Kevin Drum noted my lament in late 2008 and promised that he’d revisit the GSS in the future. He hasn’t. That’s fine, there are 1 million things I mean to do which I don’t manage to get to. But still, it’s kind of depressing to me the amount of opinion people can express which they don’t bother to follow up on by using a web interface to a rich data source which requires no more than 1997 era browser skills.

There’s a lot you can do with the GSS interface, but I thought it might be useful to do something very simple so that people can see how easy it really is. Since most of the people I follow on twitter lean Left I see a lot of political chatter which is concerning to that segment of the population. For example there is a lot of talk about conservative white males and their lack of concern for global warming.

Can we explore this with any greater precision with the GSS? Yes we can.

First you need to find the appropriate variables. So go to the search box and enter in what you want to find. I typed “warming.” When you hit the “Go” button it will return a list of variables which we can then use in your further queries. My own suggestion is to keep the query simple and one word, this isn’t Google. You’ll get a lot of results usually, but at least it will give you options. Often there are many overlapping variables and you want to pick the one with the largest sample size or which was asked most recently.

Here is some of what I got for “warming”:

I want the last variable. If I click it it puts it into the “Selected” text box. I hit “Row” to copy it to the appropriate box. If you use the GSS enough with a few variables you get to know them off the top of your head and can skip this step. For evolution for example I know that “evolved” is a dichotomous response which was surveyed relatively recently.

But you want more than one variable. Going back to my initial curiosity I want to “cross” the variable under consideration with race and sex. I happen to know that there is a “Sex” variable where males are 1 and females are 2. I also know there is a “Race” and “Hispanic” variable, where 1 is white and non-Hispanic. I’ll put “Race” in the column box, so it crosses with the row. I’ll also limit the sample to Non-Hispanics and males. So you see I entered something in the “Selection Filters” box. There’s a lot more fine-tuning you can do at this point, but let’s just go with this.

Below are the results for the query above. As you can see it’s vintage 1997 as well:

All sorts of details are clear here. You can see the weighted sample size, the exact form of the question, and of course the results in combination of row and column classes.

Finally let’s control for ideology. I happen to know that the POLVIEWS variable has seven response classes, from extremely liberal to extremely conservative. I’m combine the three liberal classes and three conservative classes using the recombine option. You can see it below in the “Control” box. This means that the query above will now be split into three categories, one for liberals, one for moderates, and one for conservatives. Here’s a response for liberals and conservatives:

The sample sizes for non-whites here are very small, but the big difference is across ideology among white males. In other words we’re talking ideology as the causal factor. White male are more conservative. And conservatives are less concerned about Arctic seals possibly being threatened by global warming.

I used very much a toy example above. I just wanted to show you how easy the interface really is.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: General Social Survey, GSS 
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I just finished reading My Fertility Crisis, which is excerpted from a longer piece you can get on Kindle 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:

An issue mentioned in the piece above is that there is a focus on the successes of IVF as opposed to the failures. I don’t really buy that narrative. But, there is a tendency not to focus too much on the fact that many IVF successes for women in their 40s are due to donor eggs. A clear example of this phenomenon is that very few in the media highlighted the likelihood that Elizabeth Edwards’ last two children were conceived with the help of donor eggs. She was 49 and 51 when they were born.

Recently a friend asked me about the value proposition of freezing eggs in the case of a 35-year-old female friend. I think it’s something that many people in the developed world really need to consider. Yes, the cost is going to be in the range of tens of thousands, but that’s the magnitude of a car, and far less than a home. A healthy child seems to me much more valuable than either of these objects to people who want to have children.

One of the implications that many people take away from these results is that society should aid those who wish to have children at later ages. I’m broadly sympathetic to this viewpoint. The type of people that I know personally are often in this class; they have delayed starting families to finish their extended educations and invest in their own human capital. In 15 states the law requires than health insurance cover infertility treatment. But we must not ignore the class ramifications of these policies. Mandating the coverage of infertility may alter the behavior of some individuals (just as the existence of ART has changed the stance of many people toward the “reproductive clock” more generally), but it is operationally a transfer from those who have children earlier, and are generally of lower socioeconomic status, toward those who have delayed childbearing toward later ages and are usually of higher socioeconomic status. The counterargument could be that higher socioeconomic status individuals pay greater taxes already.

The General Social Survey has a variable, AGEKDBRN, which asks respondents when their first child was born. Below I limited the data set as follows:

1) All responses are from the year 2000 and later

2) All responses are from women

All the x-axes on the plots are age of the mother when the first child was born, while the y-axes are proportions across classes. I’ve smoothed the data some. In the first plot ~10% of women whose family wealth is less than $100,000 had their first child at 20. For women whose family wealth as more than $100,00 the proportion was ~8%. For the last plot I categorized “Dull”, “Not Dull” and “Smart” with WORDSUM, which is a 10 question vocabulary test which has a 0.70 correlation with I.Q. The dull category encompasses the bottom 35% of the distribution, the not dull encompasses the middle 53% of the distribution, and the smart the top 12% of the distribution.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Culture, Data Analysis, Fertility, GSS, Health 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"