Why Heritage is wrong on the new Census race/ethnicity question

Sorry this is long and rambly. I just want to get the main points down and I’m in the middle of other things. I hope it helps.

Mike Gonzalez, a Bush-era speech writer with no background in demography (not that there’s anything wrong with that), now a PR person for the Heritage Foundation, has written a noxious and divisive op-ed in the Washington Post that spreads some completely wrong information about the U.S. Census Bureau’s attempts to improve data collection on race and ethnicity. It’s also a scary warning of what the far right politicization of the Census Bureau might mean for social science and democracy.

Gonzalez is upset that “the Obama administration is rushing to institute changes in racial classifications,” which include two major changes: combining the Hispanic/Latino Origin question with the Race question, and adding a new category, Middle Eastern or North African (MENA). Gonzalez (who, it must be noted, perhaps with some sympathy, recently wrote one of those useless books about how the Republican party can reach Hispanics, made instantly obsolete by Trump), says that what Obama has in mind “will only aggravate the volatile social frictions that created today’s poisonous political climate in the first place.” Yes, the “poisonous political climate” he is upset about (did I mention he works for the Heritage Foundation?) is the result of the way the government divides people by race and ethnicity. Not actually dividing them, of course (which is a real problem), but dividing them on Census forms. (I hadn’t heard this particular version of why Trump is Obama’s fault — who knew?)

How will the new reforms make the Trump situation he helped create worse? Basically, by measuring race and ethnicity, which Gonzalez would rather not do (as suggested by the title, “Think of America as one people? The census begs to differ,” which could have been written at any time in the past two centuries).

Specifically, Gonzalez claims, completely factually inaccurately, that Census would “eliminate a second question that lets [Hispanics] also choose their race.” By combining Hispanic origin and race into one question — on which, as before, people will be free to mark as many responses as they like — Gonzalez thinks Census would “effectively make ‘Hispanic’ their sole racial identifier.” He is upset that many Latinos will not identify themselves as “White” if they have the option of “Hispanic” on the same question, even if they are free to mark both (which he doesn’t mention). Some will, but that is not because anyone is taking away any of their choices.

The Census Bureau, of course, because they always do, because they are excellent, has done years of research on these questions, including all the major stakeholders in a long interactive process that is scrupulously documented and (for a government bureaucracy) quite transparent. Naturally not everyone is happy, but in the end the trained demographic professionals come down on the side of the best science.

Race that Latino

The most recent report on the research I found was a presentation by Nicholas Jones and Michael Bentley from the Census Bureau. This is my source for the research on the new question.

First, why combine Hispanic with race? You have probably seen the phrase “Hispanics may be of any race” on lots of reports that use Census or other government data. The figure below is from the first edition of my book, using 2010 data, in which I group all 50 million Hispanics, and show the races they chose: about half White, the rest other race or more than one race (usually White and other race). Notice that by this convention Hispanics are removed from the White group anyway, just because we don’t want to have people in the same picture twice (“non-Hispanic Whites” is already a common construction).

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The “may be of any race” language is the awkward outcome of an approach that treats Hispanic as an “ethnicity” (actually a bunch of national origins, maybe a panethnicity), while White, Black, Asian, Pacific Islander, and American Indian are treated as “races.” The distinction never really made sense. These things have been measured using self-identification for more than half a century, so we’re not talking about genetics and blood tests, we’re talking about how people identify themselves. And there just isn’t a major categorical difference between race and ethnicity for most people — people of any race or ethnicity may identify with a specific national origin (Italian, Pakistani, Mexican), as well as a “race” or panethnic identify such as Asian, or Latino. And now that the government allows people to select multiple races (since 2000), as well as answering the Hispanic question, there really is no good justification for keeping them separate. As you can see from my figure above, when we analyze the data we mostly pull all the Hispanics together regardless of their races. The new approach just encourages them to decide how they want that done, which is usually a better approach.

Of course, Asians and Pacific Islanders have been answering the “race” question with national origin prompts for several decades. There was no “Asian” checkbox in 2000 or 2010 (or on the American Community Survey). So they have been using their ethnicity to answer the race question all along — that’s because for some reason you just can’t get “Asian” immigrants, especially recent immigrants — that is, people from India, Korea, and Japan, Vietnam, and so on — to see themselves as part of one panethnic group. Go figure, must be the centuries of considering themselves separate peoples, even “races.” So, a new question that combines the more ethnic categories (Mexican, Pakistanis, etc.), with America’s racial identities (Black, White, etc.), just works better, as long as you let people check as many boxes as they want. This is what the “race” question looked like in 2014. Note there is no “Asian” checkbox:

acsrace2014

As a general guide, the questionnaire scheme works best when (a) everyone has a category they like, and (b) few people choose “other.” That is the system that will yield the most scientifically useful data. It also will tend to match the way people interact socially, including how they discriminate against each other, burn crosses on each other’s lawns, and randomly attack each other in public. We want data that helps us understand all that.

Through extensive testing, it has become apparent that, when given a question that offers both race and Hispanic origin together, Latino respondents are much more likely to answer Hispanic/Latino only, rather than cluttering up the race question with “some other race” responses (often writing in “Hispanic” or “Latino” as their “other race”). If I read the presentation right, in round numbers, given the choice of answering the “race” question with “Hispanic,” in the test data about 70% chose Hispanic alone; about 20% chose White along with Hispanic, and 5% choose two races. In fact, the number of Latinos saying their only race is White probably won’t change much; the biggest difference is that you no longer have almost 40% of Latinos saying they are “some other race,” or choosing more than one race (usually White and Other) which usually just means they don’t see a race that fits them on the list.

In the end, the size of the major groups (Hispanics and the major races) are not changed much. Here’s the summary:

betterhispanic

In fact, the only major group that will shrink is probably the non-group “multiracial” population, which today is dominated by Hispanics choosing White and “some other race.”

It’s really just better data. It’s not a conspiracy. It’s not eliminating the White race or discouraging assimilation of Hispanics. In short, keep calm and collect better data. We can fight about all that other stuff, too.

I’m sure Gonzalez doesn’t really think this will “eliminate Hispanics’ racial choices.” He’s dog-whistling to people who think the government is trying to reduce the number of Whites by not letting Hispanics be White. His statements are factually incorrect and the Washington Post shouldn’t have printed them. (I don’t know how the Post does Op-Eds; when I wrote one for the NY Times it was pretty thoroughly fact-checked.)

MENA

The Migration Policy Institute estimates there are about 2 million MENAs in the U.S. now, about half of them immigrants. This is a pretty small population, mostly Arab-speaking immigrants and their descendants, and more Christian (relative to Muslim) than the countries they left. This is especially true of the more recent immigrants, which don’t include a lot of Iranians (who aren’t Arab).

Census could have instead defined them by linguistic origin (Arab), and captured most, but they instead are going with country of origin, which is consistent with how the other race/ethnic groups are identified (for better or worse). Their testing showed that this measure captures most people with MENA ancestry, encourages them to identify their ancestry, cuts down on them identifying as White, and cuts down on them using “some other race.”

The difference is dramatic for those identifying as White, which fell from 85% to 20% in the test once a MENA category was offered. Would it be better if they just identified as White? I’m really not trying to shrink the count of Whites, I just think this is more accurate. I don’t care about the biology of Whiteness and whether Iranians are part of it, for example (and don’t ever say “Caucasian,” please), I care about the experience and identity of the people we’re talking about — as well as the beliefs of the people who hate them and those who want to protect them from discrimination. Counting them seems better than shoehorning them into a category most of them avoid when given the chance.

Here’s one version of the proposed new combined question, from that Census presentation:

newraceq

Yuck

Why not Mike Gonzalez to run Census? Unbelievably, he probably knows more about it than Trump’s education and HUD department heads know about their new portfolios.

But that’s just one odious possibility. It makes me kind of sick to think of the possible idiots and fanatics Trump might put in charge of the Census Bureau, after all this work on research and testing, designed to get the best data we can out of a very messy and imperfect situation.

What else would they do? Will they continue to develop ways to identify and count same-sex couples? The Supreme Court says they can get married, but there is no law that says the Census Bureau has to count them. What about multilingual efforts to reach immigrant communities? This has been a focus of Census Bureau development as well. And so on.

It is absolutely in Trump’s interest, and the interests of those who he serves (not the people who voted for him), to reduce the quality and quantity of social science data the government produces and enables us to produce.

How do Black-White parents identify their children?

In 2015 the American Community Survey yields an estimate of 66,913 infants who have one Black parent and one White parent present in the household. (Either parent may be multiracial, too.)

What is the race of those infants? 73% of them were identified as both White and Black by whoever filled out the Census form.

bwinfants

(Note “other” doesn’t mean they specified “other,” it just means they used some other combination of races.)

These are children age 0 living with both parents, so it’s a pretty good bet they’re mostly biological parents, though some are presumably adopted. This is based on a sample of 507 such infants. If you pooled some years of ACS there is plenty to study here. Someone may already have done this – feel free to post in the comments.

That’s it, just FYI.

Civility in the swelter (Hershey Park edition)

This post combines my love of vacations (context), my habit of taking pictures of people in public places (data)*, and my sociological tendency to invent big conclusions from minor events (theory). As with last year’s selfie post , I hope you don’t take from this that I don’t really love vacations.

With 3.2 million annual visitors, Hershey Park is barely in the top 20 amusement/theme parks in the country. And unlike the top draws, all Disney properties, I reckon Hershey mostly draws a local and regional crowd, which means they’re not as rich as the average Disney visitor.

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What interests me is the way this lower-middle amusement park creates the context for civility in a very diverse environment, even as racial and ethnic conflagration seems to be breaking out all over.

It’s very racially and ethnically diverse, and most of the Whites either aren’t rich or they’re hiding their wealth well.

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Why didn’t Charles Murray, in his obnoxious “do you live in a bubble” quiz, which is supposed to test your exposure to and familiarity with working-class White culture (yes, just White culture, though the PBS promoters of the quiz only mentioned that after people complained), ask about amusement parks, where White working class people spend their vacations mingling with — or at least in close proximity with — racial minorities?

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Including in the historically-fraught pool.

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Some may be merely standing shoulder-to-shoulder with people from different races. But I saw more interracial couples and families than I usually see in my diverse suburb.

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Are they just tolerating each other, or are they really getting along? Of course, I’m White and rich and blind to all sorts of things, but I’m not stupid. I have no doubt there were slights and insults and aggressions going on outside of my perception (though I was looking for them). But there were also the kind of casual moments of “us just getting along” that usually go unremarked, like when parents enjoy watching their kids having fun together.

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I’m not making an argument about the relative racism apparent across classes. I know your feed today is probably awash in racist stuff coming from all over the social spectrum. I’m more interested in what the social context does to interpersonal interaction. The park is very leveling, economically. The poorest people are obviously excluded, and the richest aren’t interested. And then most people buy tickets before they arrive, and it’s in a remote place, so there is no one visible who can’t get in, no obvious fast lane for rich people (even at the rides, unlike Disney). We all ride the same tram from the parking lot to the gate, so the car interaction is minimized. We go through the same giant line to enter, and then wait in the same lines to ride the same rides and eat the same food once inside.

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There are ways to spend more money conspicuously, buying extra crap, but there is less of that than I’ve seen at Disney or Universal Studios (have you priced a genuine Princess dress lately?). In short, it brings out what a lot of different Americans have in common: overpaying for entertainment, overeating greasy food, and alternately yelling at and loving on their children.

I’m reminded of two things. One is that there is less racial conflict and violence in the U.S. than there was in the past (dating the data trends here is obviously debatable). The level of racism — structurally and interpersonally — is still way too high, of course. But it partly stands out now because we have more casual, positive interaction, than we did in the past. Social movement scholars will tell you that periods of improving relations are ripe for upheaval and unrest, because expectations are raised and subordinate groups are empowered. Don’t draw from the level of conscious resistance we see now the conclusion that conditions are worse than ever, because that’s not how it works.

Two is that civility can be engineered. In 2002 my friend Jennifer Lee wrote of the “important untold story [of] the mostly quotidian nature of commercial life in neighborhoods like New York’s Harlem and West Philadelphia,” areas at the time experiencing racial tension erupting in occasional violence around the issue of ethnic turf and racism in retail spaces. This Civility in the City was partly the product of deliberate, conscious effort by store owners and employees to preserve it. The level of interpersonal conflict and expression of animosity is not determined by structural inequalities alone. That deep inequality remains the defining American problem of our time. I don’t know how the level of interpersonal conflict plays into our ability to confront and address that inequality — and I’m not saying we should settle for civility over equality — but I’m sure it’s somehow relevant.

* This is ethical and legal as long as I’m not trying to harm anyone – millions of people do it every day. If you happen to be in one of these pictures and want me to take them down I will happily oblige. Before you get mad about me using these pictures, close your eyes and think of all the pictures you’ve seen just this week of strangers who did not consent to have their pictures taken.

On Asian-American earnings

In a previous post I showed that generalizations about Asian-American incomes often are misleading, as some groups have above-average incomes and some have below-average incomes (also, divorce rates) and that inequality within Asian-American groups was large as well. In this post I briefly expand that to show breakdowns in individual earnings by gender and national-origin group.

The point is basically the same: This category is usually not useful for economic statistics, and should usually be dropped for data on specific groups when possible.

Today’s news

What’s new is a Pew report by Eileen Patten showing trends in race and gender wage gaps. The report isn’t focused on Asian-American earnings, but they stand out in their charts. This led Charles Murray, who is fixated on what he believes is the genetic origin of Asian cognitive superiority, to tweet sarcastically, “Oppose Asian male privilege!” Here is one of Pew’s charts:

pewraceearn

The figure, using the Current Population Survey (CPS), shows Asian men earning about 14.5% more per hour than White men, and Asian women earning 11% more than White women. This is not wrong, exactly, but it’s not good information either, as I’ll argue below.

First a note on data

The CPS data is better for some labor force questions (including wages) than the American Community Survey, which is much larger. However, it’s too small a sample to get into detail on Asian subgroups (notice the Pew report doesn’t mention American Indians, an even smaller group). To do that I will need to activate the ACS, which is better for race/ethnic detail.

As a reminder, this is the “race” question on the 2014 American Community Survey, which I use for this post:

acsrace2014

There is no “Asian” or “Pacific Islander” box to check. So what do you do if you are thinking, “I’m Asian, what do I check?” The question is premised on that assumption that is not what you’re thinking. Instead, you choose from a list of national origins, which the Census Bureau then combines to make “Asian” (the first 7 boxes) and “Pacific Islander” (the last 3) categories. And you can check as many as you like, which is good because there’s a lot of intermarriage among Asians, and between Asians and other groups (mostly Whites). This is a lot like the Hispanic origin question, which also lists national origins — except that question is prefaced by the unifying phrase, “Is Person 1 of Hispanic, Latino, or Spanish origin?” before listing the options, each beginning with “Yes”, as in “Yes, Cuban.”

Although changes have not been announced, it is likely that future questions will combine the race and Hispanic-origin questions, and also preface the Asian categories with the umbrella term. This may mark the progress of getting Asian immigrants to internalize the American racial classification system, so that descendants from groups that in some cases have centuries-old cultural differentiation start to identify and label themselves as from the same racial group (who would have put Pakistanis and Japanese in the same “race” group 100 years ago?). It’s hard to make this progress, naturally, when so many people from these groups are immigrants — in my sample below, for example, 75% of the full-time, year-round workers are foreign-born.

Earnings

The problem with the earnings chart Pew posted, and which Charles Murray loved, is that it lumps all the different Asian-origin groups together. That is not crazy but it’s not really good. Of course every group has diversity within it, so any category masks differences, but in my opinion this Asian grouping is worse in that regard than most. If someone argued that all these groups see themselves as united under a common identity that would push me in the direction of dropping this complaint. In any event, the diversity is interesting even if you don’t object to the Pew/Census grouping.

Here are two breakouts. The first is immigration. As I noted, 75% of the full-time, year-round workers (excluding self-employed people, like Pew does) with an Asian/Pacific Islander (Asian for short) racial identification are foreign born. That ranges from less than 4% for Hawaiians, to around 20% for the White+Asian multiple-race people, to more than 90% for Asian Indian men. It turns out that the wage advantage is mostly concentrated among these immigrants. Here is a replication of the Pew chart using the ACS data (a little different because I had to use FTFY workers), using the same colors. On the left is their chart, on the right is the same data limited to US-born workers.

api1

Among the US-born workers the Asian male advantage is reduced from 14.5% to 4.2% (the women’s advantage is not much changed; as in Pew’s chart, Hispanics are a mutually exclusive category.) There are some very high-earning Asian immigrants, especially Indians. Here are the breakdowns, by gender, comparing each of the larger Asian-American groups to Whites:

api2

Seven groups of men and nine groups of women have hourly earnings higher than Whites’, while nine groups of men and seven groups have women have lower earnings. In fact, among Laotians, Hawaiians, and Hmong, even the men earn less than White women. (Note, in my old post, I showed that Asian household incomes are not as high as they look when they are compared instead with those of their local peers, because they are concentrated in expensive metropolitan markets.)

Sometimes when I have a situation like this I just drop the relatively small, complex group, which leads some people to accuse me of trying to skew results. (For example, I might show a chart that has Blacks in the worst position, even though American Indians have it even worse.)

But generalization has consequences, so we should use it judiciously. In most cases “Asian” doesn’t work well. It may make more sense to group people by regions, such as East-, South-, and Southeast Asia, and/or according to immigrant status.

Tell me why it’s not racist to oppose Black Oscar categories

cr

Good comedy is like sociology only better. Today’s edition: Race and gender.

In Chris Rock’s monologue at the Oscars, he said this:

Hey, if you want Black nominees every year, you need to just have Black categories. That’s what you need. You need to have Black categories.

You already do it with men and women. Think about it: There’s no real reason for there to be a man and a woman category in acting.

C’mon. There’s no reason. It’s not track and field.

You don’t have to separate ’em. You know, Robert De Niro’s never said, “I better slow this acting down, so Meryl Streep can catch up.”

No, not at all, man. If you want Black people every year at the Oscars, just have Black categories. Like Best Black Friend.

If you say, “Where does it end?”, then tell me why you don’t oppose the gender categories. Tell me why it’s not racist to leave the acting gender categories unquestioned but oppose race categories. Not making that argument, of course, just asking the question.

Looks like racist Southern Whites like Trump

We’ve been given lots of reasons people support Trump, like authoritarian attitudes and “the legitimate anger that many Americans feel about the course that the country has taken.” But it’s also racism, I’m pretty sure. Or at least racists.

It’s hard to measure racism – or even define exactly what we mean by racism. One way to approach it is racial salience, which is closely related to racism, and we can measure that with the proportion of the local population that is Black. (I reviewed a bunch of this research here.)

It’s also usually hard to get measures of just White behavior, which makes a Southern Republican primary perfect — they’re basically all White. This is also good because we’re trying to figure out what’s driving the Trump thing. In South Carolina, it looks like it was driven by the presence of Blacks and people born in South Carolina, and less urban populations.

In counties with less than 40% of the population born out of South Carolina — 33 of the 46 countries — there is a strong positive relationship between Trump vote share and population proportion Black. Here is the plot, with the high local-born counties in red:

Those red dots are the classic percent-Black racism pattern. Whites are more racist where there are more Blacks. Interesting in the case of Trump, because most of his overt racism is directed at immigrants and Muslims. But the regular anti-Black racists have been very apparent in his crowds, and in his endorsements.

I looked at the out-of-state share because of the outliers. That’s Horry County in the top left (site of Myrtle Beach) and Richland County at the bottom right (site of Columbia), two places with less of an old-school (i.e., rural slave plantation) feel. The rural thing is important, too, as larger counties voted less for Trump.

I’d love to see someone do this for the Super Tuesday states. The other variables you could use would be slave populations in 1850, or post-bellum lynchings.

Here it is in regression terms, with the 46 counties (ask me for the data and code):

trump-sc-black-gop-reg

Objection addendum:

This is just a descriptive analysis. And I probably only presented it because it fits so well with my prior assumptions – so that’s good or bad on my part, I guess. That said, I did it and posted it so I own it.

Someone on Facebook objected that I am obscuring the positive slope in the high out-of-state counties. In fact, if you exclude Horry County, you see a positive slope in those counties as well. As you would if you included all the counties together. That black line is not good because it’s so skewed by the outlier. However, the regression didn’t use the categorical breakdown of out-of-state population. There you can see the positive effect of proportion Black in all counties, but at high levels of out-of-state the model says proportion Black would turn negative – which is because of the Horry County outlier.

In fact, if you just drop Horry County, the interaction and out-of-state effects are no longer significant, it’s just proportion Black and population size! So, you could rephrase the conclusion as: more Trump votes where there is more Black population, and in smaller-population counties, and ignore the out-of-state thing. But I don’t know enough about South Carolina to know whether it’s justifiable to exclude Horry County that way. It’s one of the most populous counties (6% of the total).

Here is the chart with all the counties, dropping the out-of-state distinction. Still a nice positive relationship and a good racism story, but weaker:

trump-sc-black-gop2

And just to show how extreme the effect of the outlier is, here are just the high out-of-state counties, with and without Horry:

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When the map says race but all you can talk about is fatherhood

Raj Chetty and colleagues have a new paper showing that “childhood environments play an important role in shaping gender gaps in adulthood.” Essentially, boys from poor or or single parents are doing worse. Also, this gender difference is greater in Black and poor places.

The tricky thing with this data, and I don’t blame Chetty et al. for this, although I would like them to say more about it, is that they don’t know the race of the children. The data are from tax records, which allow you to know the income and marital status of the parents, but not the race. But they know where they grew up. So if they have a strong effect of the racial composition of the county kids grow up in, but they don’t know the race of the kids, you have to figure a big part of that is race of the kids — and by “you” I mean someone who knows anything about America.

So here’s their map of the gender difference in employment rates associated with having poor parents:

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To help make the point, here is their list of local areas at the top and bottom of the map:

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I hope that is enough to make the point for the demographically literate reader.

I credit them in this paper for at least using percent Black as a variable, which they oddly omitted from a previous analysis. This allows the careful reader to see that this is the most important local-area variable — which makes perfect sense because it is doing the work of the individual data, which doesn’t include race.

racechettyeffects

Wow!

It’s important that these examples are all about employment rates. We know that the penalty for being a Black man is especially large for employment, partly because of the direct effects of mass incarceration, but also because of discrimination, some of which is directly related to incarceration and the rest of which may be affected by its aura. This is not something we measure well. Our employment reporting system does not include prison records. Prisoners are excluded from the Current Population Survey, but then included when they are released. So they show up as jobless (mostly) men.

Whenever you see something about how race affects poor men, you have to think hard about what incarceration is doing there — we can’t just rely on the data in front of us and assume it’s telling the whole story, when we know there is a massive influence not captured in the data.

This is exactly what marriage promoters delight in doing. I give just one example, a blog post by the Brookings Institution’s Richard Reeves, which — amazingly, astoundingly, remarkably, disappointingly, not surprisingly — discusses the effect of growing up poor and “less-educated” in Baltimore (Baltimore!) without once mentioning race or incarceration. Instead, he goes right to this:

Wanted: Fathers

Of course, there is much more to being a man than money: in fact, to define masculinity in breadwinning terms alone is a fatal move. As Barack Obama said on Fathers’ Day seven years ago, fathers are “teachers and coaches. They are mentors and role models.” But as he also said, “too many fathers are missing—missing from too many lives and too many homes.” In its poorest neighborhoods, America faces a fathering deficit, one that will make it even harder for the boys of today to make it as men in the new world.

Fatherhood is important. You could investigate a fathering deficit, but if you really cared about it you want to look at in the context of well-known, massive causes of harm to Black boys in America, chief among them racism and mass incarceration.

 

Visualizing attitude differences

This didn’t turn into something more substantial, so I’m just leaving it here as is. I like the idea of visualizing attitude (or other) differences by race/ethnicity, sex, and generation (or other characteristics) with distances. Plus my daughter is learning about x-y coordinates in math.

I got these just using the General Social Survey online analysis tool (here). These are the question texts.

HELPBLK (1-5):

Some people think that African-Americans have been discriminated against for so long that the government has a special obligation to help improve their living standards; they are at point 1. Others believe that the government should not be giving special treatment to African-Americans; they are at point 5. a. Where would you place yourself on this scale, or haven’t you made up your mind on this?

FEFAM: Strongly agree to strongly disagree (1-4):

It is much better for  everyone involved if the man is the achiever outside the home and the woman takes care of the home and family.

I used two categories each of race (Black/White), Sex (man/woman), and Generation (18-44/45+). Scores are shown as differences between each group’s mean score and the population average.

Short story: Whites show little difference by age, gender, or generation on the race question, but big differences by gender and age on the gender question. Blacks are similar to Whites on the gender question except that younger Blacks men are less opposed to breadwinner-homemaker family arrangements than are younger Whites (especially men).

I also added some other groupings for comparison:

No real point to make about this except that I like the idea of representing these patterns like this. Someone should make a GSS tool that does this for you on any question. With confidence intervals. (If there are already are such tools, please advise.)

I overspoke myself on Twitter

Possibly not the only time.

A blog called Random Critical Analysis (RCA) has posted, “On Philip Cohen’s knee-jerk response to Chetty’s “causal mobility” data and its association with single-motherhood.” I now must admit that I overspoke myself on Twitter.

But I think the blog post I wrote holds up OK. I complained in the post that the now-famous Chetty et al. analysis of intergenerational mobility had mishandled race, leading to people like David Leonhardt (and rightward from there) to conclude that the big story of hampered social mobility is family structure. It’s part of the overall pattern of polite society embracing the issue of economic inequality but also using that as a foil to avoid the issue of race inequality.

Brad Wilcox has seized on the Chetty analysis, repeating ad nauseum the quote that single parenthood is the “single strongest correlate of upward mobility.” My beef was, and is, that the analysis that was based on — which used the rate of single parenthood at the labor market level to predict intergenerational mobility — did not control for the racial composition of the labor market. That’s an obvious problem when your map of mobility looks like this:

mobilitymap

When your analysis is ecological, that is, based only on aggregate characteristics, you have to be very cautious about drawing conclusions. It’s especially dicey in the Chetty case because the basic data, from tax, returns, includes family structure (because of parents’ marital status) but not race (which doesn’t go on your tax form). And that’s even more dicey because we know that at the individual level single parenthood is definitely not the “single strongest correlate of upward mobility.” I’ve been writing about this for years (follow the single-mother tag), but this figure from 2012 sums it up nicely (details in the old post):

You just have to keep that in perspective when you jump to an aggregate-level analysis. The difference between averages in Atlanta versus Salt Lake City — important as it is — is never going to be as big as the difference between a rich family and a poor family. Social parents’ class matters much more for determining children’s social class than does family structure.

Anyway, RCA is reworking my very simple analysis showing the effect of single motherhood rates was reduced by two-thirds when a single control for racial composition (percent Black) was added. That’s making the obvious point that, because single parenthood and percent Black in the local area are so strongly correlated, if you don’t take percent Black into account it looks like single parenthood has a huge, independent effect — which incorporates the effects of racism or other community factors associated with historical race composition. The new RCA post goes much further in the analysis, and concludes:

It ought to be pretty clear by now single-motherhood is capturing something quite powerful and that, contrary to Cohen’s strong assertions, it is not well explained by race.  If anything, single-motherhood mediates the black association much better than the reverse.

I’m not persuaded by the conclusion; you can evaluate it yourself. But the premise of the RCA post is actually not my blog post, but my tweets. As time went by I apparently became frustrated at the continued repetitions of the single mother thing by people who were ignoring my very clever post, and with the carelessness that distance allows I overstated my own claim, so I tweeted this,

The table and the highlighting are mine. What I should have paid attention to was my own next sentence after the underlined part: “That’s not an analysis, it’s just an argument for keeping percent Black in the more complex models.” I didn’t do a serious analysis — I just did enough to prove the point that racial composition should be in the model. Without that, you shouldn’t run around saying single parenthood is the most important factor. (RCA also believes I shouldn’t have said in the post that “Percent Black statistically explains the relationship between single motherhood and intergenerational immobility.”  I think “explains” is defensible, in that the effect is no longer statistically distinguishable from zero at the conventional level, but it’s clearly not the same as proving there is no effect, so I’ll take the criticism, too.)

I actually first did the little analysis in an earlier post, debunking a univariate analysis by Scott Winship and Donald Schneider. In that case I concluded: “This [my analysis] is not a rigorous examination of the cause of intergenerational immobility. It is just debunking one bivariate story that is too easily picked up by the forces of bad.” That seems about right.

Anyway, in conclusion, it was incorrect based on what I did for me to tweet, “the single mother effect in Chetty is all in the % Black effect.” I should just say single parenthood hasn’t been proven to matter as much as its partisans say it has. Even if it’s less effective in a tweet. This is a common frustration, that it takes more work to debunk something than to bunk it in the first place. But that’s not a good excuse.

Finally, I’m grateful that what I write matters enough that someone would go to the trouble of testing my claims to hold me accountable.

Quick correction on that 90-percent-of-faculty-are-White thing

The other day I saw a number of anti-racist people tweeting that “nearly 90% of full-time professors are White.” As I have previously complained when 90% of the full professors at my then-school (UNC) were White, I was interested to follow up. Unfortunately, that popular tweet turns out to be a stretched description of a simple error.

The facts are in this Education Department report from May, which was reported at the time by The Ed Advocate, and suddenly started going around the other day for unknown reasons. The “nearly 90%” is the Ed Advocate’s description of 84%, which is the percentage White among full-time full professors, which the original report in one place accidentally describes as just full-time professors. Among all full-time instructional faculty, in fact, 79% are White. So the headline, “Study: Nearly 90 Percent of Full-time Professors Are White,” was a conflation of two errors. It presumably became popular because it put a number to a real problem lots of people are aware of and looking for ways to highlight.

Here is the original chart:

whitefac

The problem of White over-representation among college faculty is not that apparent in this national 79% statistic. Consider, for example, that among all full-time, full-year workers age 40 and older (my made-up benchmark), 71% are non-Hispanic White. Among those with a Masters degree or higher, 77% are White. So faculty, nationally and at all levels, don’t look that different from the pool from which they’re drawn.

The 84% full professor statistic reflects the greater White representation as you move up the academic hierarchy. And that’s not just a question of waiting for younger cohorts with more non-White faculty to age into the professoriate. Because the pipeline isn’t working that well, especially for Black faculty. Which brings me back to my old UNC complaint, which focused mostly on Back under-representation. In 2010 I noted that the North Carolina population was 22% Black, while the UNC faculty was 4.7% Black. But full professors at UNC were just 2.4% Black, while the assistant professors were 7.5% Black. Is that the pipeline working? Well, only 4.5% of the recent faculty hires were Black.

I went back to check on things. As of the 2014 report (they’re all here), the update is that UNC has stopped reporting the numbers by rank, so now all they say is that 5.2% of all faculty are Black, and they don’t report the makeup of recent hires. So take from that what you will.

And what about further up the pipeline? I previously shared numbers showing a drop in Black representation among entering freshmen at the University of Michigan, from 10% to 5% over the 2000s. The trend at UNC is in the same direction:

unc black studentsOf course we always need to be cautious about numbers that support what we already know or believe. Some people will respond to this by saying, “but the point remains.” Right, but if the number is irrelevant to the point, there’s no need to use the number. Plenty of people can say, “In all my undergraduate years, I never had a Black professor,” or some other highly relevant observation.*

On the other hand, others of us need to disabuse ourselves of the notion that progress on under-representation is just happening out there because everyone thinks it should and it’s just a matter of time. That common assumption allows defensive administrators to do write thinks like this caption (from UNC’s 2011-2012 report):

unc1112

This is misleading: There was a big increase in Hispanic students (North Carolina has a growing Hispanic population) and Asian students, and marked drops in Black and American Indian students. But “overall, steady increase” is an easy narrative to sell.

If they scaled that chart from 0 to 12 and dropped Whites, “overall, steady increase” would look like this:

uncscaled

* I think I had three great Black professors at Michigan: Walter Allen, Robin D. G. Kelley, and Cecilia Green, each of whom changed my life forever. Sorry if I’m forgetting someone.

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