I have written a review of Nicholas Wade’s book, A Troublesome Inheritance: Genes, Race and Human History, for Boston Review. Because there already are a lot of reviews published, I also included discussion of the response to the book. And because I’m not expert in genetics and evolution, I got to do a pile of reading on those subject as well. I hope you’ll have a look: http://www.bostonreview.net/books-ideas/philip-cohen-nicholas-wade-troublesome-inheritance
Tag Archives: race
Yesterday the Supreme Court ruled that Michigan voters have the Constitutional right to ban the state’s government from using race-specific policies. The immediate implication for Michigan, and other states, is for university admissions polices. So now if the state wants to pass a law allowing children of alumni easier admission to the University of Michigan, it’s a simple act of the legislature; but if they want to consider race in their admissions, they will need to amend the state constitution.
The University of Michigan has been at the center of national affirmative action debates for several decades (at least since I arrived there in 1988). I previously reported that court decisions against the state’s affirmative action policy led to a precipitous decline in Black students entering the University in the 2000s, as shown in this graph:
That’s just the University of Michigan, an important school, but only one. (The New York Times has a graphic showing enrollment trends in a series of states with affirmative action bans.) For the whole state of Michigan, Black college graduation rates fell further behind the national average over the last decade. Here is the percent of Black 25-29 year-olds who have completed college, from 1970 to 2012, nationally versus in Michigan alone, for women (left) and men (right):
Source: 1970-2000 Decennial Censuses and 2010-2012 American Community Survey, via IPUMS.
During the 2000s, the national-Michigan gap widened from 2.3 points to 4.1 points for men, and from 3.4 to 4.8 points for women.
I am not expert in the legal arguments over this, so I can’t analyze the decision (here’s one good take). But regardless of whether it’s bad law, I think it’s bad policy.
Yesterday in a tweet I picked on the new, data-heavy news operations run by (from left to right) David Leonhardt (NY Times Upshot), Ezra Klein (Vox), and Nate Silver (Five Thirty Eight) for having very White-looking staff teams:
I don’t know any more about what goes into their hiring decisions than I do about what goes into University of Michigan admission decisions (and I know they have staff beyond these featured writers). I’m sure they all want talented people with a wide range of perspectives and skills. But the outcome in both the media and college situations is bad. It limits the perspectives presented, undermines progress toward racial-ethnic equality, and contributes to the inertia that stymies the potential of future leaders.
Referring to The Bell Curve, Paul Krugman wrote that Charles Murray was “famous for arguing that blacks are genetically inferior to whites.” In response, Murray wants us to know that the book was not about race and IQ. The research in the book (co-authored with Richard Herrnstein), purporting to show the powerful effect of genes on intelligence and success in America, was about Whites. Its sole concrete statement about race, Murray says, was this:
It seems highly likely to us that both genes and the environment have something to do with racial differences. What might the mix be? We are resolutely agnostic on that issue; as far as we can determine, the evidence does not justify an estimate.
That led to this Twitter exchange:
Why do so many people think the book was a sociobiological racist tract, when it made only indirect claims about genetic racial hierarchies? Context matters. In the U.S., you can practice racism without speaking about race.
In my teaching, I often discuss the role of male incarceration, mortality, and unemployment in contributing to the difference in marriage rates between Black and White women. And when I show that Black men have incarceration rates many times higher than White men’s, I focus on racism more than race. That is, these inequalities are not the outcomes of race, but of the way racial inequality works — explicit and implicit racism, unequal opportunity, policing practices, incarceration policies, and so on. Sometimes I do use phrases like “low-income communities,” or “inner city areas,” but I try to be specific about race and racism when it’s called for — even though of course it can be uncomfortable, for me and my students, to do that. It’s important because in the U.S. system of inequality racial inequality is not just an outcome: the system doesn’t just differentiate people by class or gender or skills or something else, with a lower-class population that “just happens” to be disproportionately from racial-minority groups.
One thing that frustrates me in the growing conversation about economic inequality is the appearance of a perhaps-too-comfortable stance in which being explicit about economic inequality means not having to address racial inequality. It is true, and important, economic inequality exacerbates racial (and gender) inequality. That’s why this stance frustrates me rather than angering me. But there is a certain politeness involved in talking about class instead of race that sometimes doesn’t help. Of course, this issue is not new at all, having been litigated especially extensively in the 1980s around the sociological work of William Julius Wilson (see, e.g., this collection).
Wilson’s research — the declining significance of race, or, the increasing significance of class — contributed to today’s movement against class inequality (as Krugman’s post illustrates). But it has also been co-opted by people taking the really racist position that inequality is caused by race (rather than racism). That is: poor minorities cause poverty. This position ironically doesn’t have to discuss race at all, because the framing is the dog whistle.
Which brings us around to the flap over Paul Ryan’s recent racist-without-race remarks. Here is a series of quotes to put that in context. None mentions race. Follow the underlined sequence:
William Julius Wilson: “Inner-city social isolation also generates behavior not conducive to good work histories. The patterns of behavior that are associated with a life of casual work (tardiness and absenteeism) are quite different from those that accompany a life of regular or steady work (e.g., the habit of waking up early in the morning to a ringing alarm clock).”
Newt Gingrich: “Really poor children, in really poor neighborhoods, have no habits of working, and have nobody around them who works. So they literally have no habit of showing up on Monday, they have no habit of staying all day.”
Paul Ryan: “We have got this tailspin of culture, in our inner cities in particular, of men not working and just generations of men not even thinking about working or learning the value and the culture of work.”
Charles Murray: “Try to imagine a GOP presidential candidate saying in front of the cameras, ‘One reason that we still have poverty in the United States is that a lot of poor people are born lazy.’ You cannot imagine it because that kind of thing cannot be said. And yet this unimaginable statement merely implies that when we know the complete genetic story, it will turn out that the population below the poverty line in the United States has a configuration of the relevant genetic makeup that is significantly different from the configuration of the population above the poverty line. This is not unimaginable. It is almost certainly true.”
In this progression, we go from children not being sufficiently exposed to steady work, to children seeing no one working in their daily lives, to multiple generations not even thinking about working, to people who are genetically lazy. That’s something!
What they talk about when they’re not talking about race
In his post on the Paul Ryan comment, Shawn Fremstad compares Ryan to Murray and concludes that Murray is more apocalyptic because he’s warning against a White cultural collapse, not just complaining about a Black one. Murray has perfected the strategy of writing about Whites (including in his latest book, Coming Apart). But I usually think of this as a dog whistle device to protect his mainstream image while whipping up his racist base. That is, if you show that genetic intelligence determines economic inequality among Whites (Bell Curve) or that declining moral standards undermine families and the work ethic among Whites (Coming Apart), then the implications for Blacks — poorer and therefore supposedly more morally decrepit and less intelligent on a population level — are obvious and need not be repeated in polite company. Just say, calmly, “Smoke,” and let (racist) nature takes its course.
But maybe Fremstad is right, that the Full Murray is more extreme than the dog-whistling Ryan. Here’s how he puts it:
In short, today’s Charles Murray thinks the much bigger culture problem—the one that really puts American society’s very survival at risk—is with white working-class people, which is what makes Ryan’s almost-nostalgic dog-whistling about “inner-city” men so striking. The big question here is whether Ryan is willing to up ante, and go for the full Murray by calling out white working-class “culture”, particularly in the suburbs and small towns where so many low- and moderate-income white people live.
I don’t know. But one answer to that came in the follow-up flap, in which Ryan insisted to a reporter that he was talking about all poor people, such as the rural poor, for whom “there are no jobs.” As Jay Livingston points out, that’s not a clarification that was warranted when he was talking about “inner city” men who are “not even thinking about working.”
What does Brad Wilcox have to not say about this?
The other recent entry in this tradition is none other than Brad Wilcox, currently a colleague of Murray’s (and apparently an impressive one) at the American Enterprise Institute (AEI). In last year’s attempt to promote early marriage, the “Knot Yet” report, he wrote about the “education and class divide” in non-marital births — and avoided race almost entirely.
But seriously, if you claim to be serious about the serious issue of unmarried women having babies, you can’t politely ignore race and racism. It’s ridiculous (as I’ve argued before, about mobility). This issue simply does not reduce to social class or education level. Look: Black mothers are much more likely than White mothers to be unmarried at every education level.
Among college graduates, Black mothers are 5.4-times more likely than White mothers to be unmarried; for high school graduates it’s 1.7-to-1. Asian mothers who are high school dropouts are less likely to be unmarried than Black college graduates. However you want to address this issue (if you want to address it at all), if you ignore this pattern and only talk about education or social class, you’re either uninformed or dishonest.
Or, you don’t care about Black families. This is exactly what Wilcox exhibited in a shocking interview with James Pethokoukis for AEI. Wilcox said the government should lead a public education campaign to convince people to be married before they have children. Then the question was, “What would be the nature of that sort of PR campaign, and to whom would it be directed?” This was his answer (from the edited transcript):
Well, the first thing is you have to understand is where all the momentum is here. Basically, since the 1970s, you’ve seen pretty high levels of single parenthood and non-marital child bearing among poor Americans and Americans who are high school dropouts. And we’ve also seen in the last really 20 or 30 years that in some important respects, marriage is stronger among college-educated Americans. So, for instance, divorce has come down from the ’70s to the present for college-educated Americans. So there’s been progress there.
But I think in terms of where all the sort of movement is recently, and it’s primarily in a negative direction, it’s among moderately educated Americans who have got a high school degree or some college or kind of classic working-class or lower middle-class Americans. And it’s this particular portion of the population and where about half of their births are outside of marriage today. And they’re at a tipping point. They can go down the road of not having marriage as the keystone to their family formation, family life, or we can hold the line, if you will, and try to figure out creative strategies for strengthening marriage in this particular middle demographic in the United States.
What is the “classic working class or lower middle-class American”? Hm. Here I’ll switch to my own transcription of the audio file AEI posted, because the details they edited out are interesting. Pethokoukis asks Wilcox to elaborate, “is this the bottom 20 percent we’re talking about”?
No, no. I’m talking about, essentially, from the 25th percentile, if you will, to the 65th percentile. So, one way to talk about it would be, sort of, you know, in some ways the NASCAR demographic would be one way to talk about it. Actually a large share of the Hispanic population in the United States would fit into this demographic group. You know, it’s sort of this middle American group, both white and Hispanic, where, once again, they’re at kind of a tipping point. And if we can kind of I think get a positive message to this group or these groups about marriage and fatherhood, you know it’s kind of an ideal, it’s a goal. That is part of the solution.
Really. The 25th to the 65th percentile of family income? That is from $32,500 to $85,000 income per year. That includes 33 percent of the African American population, 37 percent of Whites, and 38 percent of Latinos.* So, it’s more or less the middle third of each group. Or, you know, sort of, Whites and Hispanics. And NASCAR people.**
Now I suppose this is what Shawn Fremstad calls the Full Murray. Wilcox is raising the alarm about Whites, “classic” Americans, who are “at kind of a tipping point.” Just as Ryan invokes the lack of jobs when he gets out of the “inner city,” when Wilcox is talking about “classic” Americans, he says there is still time to stop them from going “down the road of not having marriage as the keystone to their … family life.” With them, “we can hold the line” for marriage. The clear implication is that Blacks passed that “tipping point” already, so that no such intervention is warranted.
*All these numbers are based on the Current Population Survey of the civilian non-institutional population.
One thing a lot of liberals and conservatives can agree on: not talking about race.
[If you don't have time for the text, just skip to the figure.]
Liberals are happy when conservatives talk about inequality, which they’re doing a lot more these days. And when they debate marriage as a way to “cure” poverty, neither talks about race. For example, Annie Lowrey writes in the the NYT Magazine:
With Democrats and Republicans pitted against one another in a vicious election-year battle over how to alleviate poverty, marriage is the policy solution du jour.
First, Lowrie makes the now universal mistake in interpreting the famous Chetty et al. result:
In a new study, the economist Raj Chetty and his co-authors found that, in terms of income mobility, nothing matters more for a low-income child than the family structures she sees in her community — not neighborhood segregation, school quality or a host of other factors.
Traditionally in America, when you say “a host of other factors,” that includes race. But the Chetty et al. paper is nearly unique in its avoidance of race, partly because race isn’t specified in tax records. So “nothing matters more” is at best untested, and at worst completely wrong, since race isn’t in the model. (My argument on this is here).
To those of us old enough to remember, or have read stuff from, the 1980s, not including race in this conversation is bizarre. Of course, it is not crazy to talk about poverty as an issue. In that article, Kristi Williams is right when she says:
It isn’t that having a lasting and successful marriage is a cure for living in poverty. Living in poverty is a barrier to having a lasting and successful marriage.
But the article doesn’t address the hard demographic reality that the things that make marriage less available or attractive to poor women — Lowrey lists “globalization, the decline of labor unions, technological change and other tidal economic forces” — have done it much more for Black women, even among the poor. In addition to even worse job prospects, for Black men you need to add incarceration, mortality, and intermarriage rates much higher for men than for women.
Here’s a simple way to see this. Adapting the old formula from William Julius Wilson, I counted up the number of employed, non-married men per non-married woman (employed or not) in the age range 25-34, separately for Blacks and Whites, and by education, for the 50 biggest metropolitan areas (one not shown because of data shortage, one outlier excluded). With intermarriage rates so low for Black women, and the tendency not to marry men without jobs, this is a reasonable approximation of the marriage market for Black women, though it understates the number of men available to White women.
This is the result:
Dots in the green areas show relative surpluses of men. Dots under the red line show better markets for White women than for Black women. It takes a minute to figure out. If your jaw dropped, you got it. With or without college degrees Black women face a shortage of “mariageable” men in every single market except five (Portland OR, Minneapolis, Denver, Salt Lake City, and Providence, which was the outlier not shown). For college graduates Black women are under 75 men per 100 women in all but two markets, non-graduates are under 75 in 40 out of 48.
White women’s market is better than Black women’s in all but six (those five plus Sacramento). In most cases White women graduates have a surplus of men from which to choose.
Poverty is one thing. Race is another. They overlap, but on some questions they can’t be combined. Marriage is one of those issues. So, when you talk about the shortage of men to marry, I recommend remembering race.
Note: After I made this graph, Joanna Peppin and I decided to write a paper together on this. That is still in the pipeline, and I was going to save this for when it’s ready. But there will be plenty more.
Yesterday I wondered about the treatment of race in the blockbuster Chetty et al. paper on economic mobility trends and variation. Today, graphics and representation.
If you read Brad Wilcox’s triumphalist Slate post, “Family Matters” (as if he needed “an important new Harvard study” to write that), you saw this figure:
David Leonhardt tweeted that figure as “A reminder, via [Wilcox], of how important marriage is for social mobility.” But what does the figure show? Neither said anything more than what is printed on the figure. Of course, the figure is not the analysis. But it is what a lot of people remember about the analysis.
But the analysis on which it is based uses 741 commuting zones (metropolitan or rural areas defined by commuting patterns). So what are those 20 dots lying so perfectly along that line? In fact, that correlation printed on the graph, -.764, is much weaker than what you see plotted on the graph. The relationship you’re looking at is -.93! (thanks Bill Bielby for pointing that out).
In the paper, which presumably few of the people tweeting about it read, the authors explain that these figures are “binned scatter plots.” They broke the commuting zones into equally-sized groups and plotted the means of the x and y variables. They say they did percentiles, which would be 100 dots, but this one only has 20 dots, so let’s call them vigintiles.
In the process of analysis, this might be a reasonable way to eyeball a relationship and look for nonlinearities. But for presentation it’s wrong wrong wrong.* The dots compress the variation, and the line compresses it more. The dots give the misleading impression that you’re displaying the variance around the line. What, are you trying save ink?
Since the data are available, we can look at this for realz. Here is the relationship with all the points, showing a much messier relationship, the actual -.76 (the range of the Chetty et al. figure, which was compressed by the binning, is shown by the blue box):
That’s 709 dots — one for each of the commuting zones for which they had sufficient data. With today’s powerful computers and high resolution screens, there is no excuse for reducing this down to 20 dots for display purposes.
But wait, there’s more. What about population differences? In the 2000 Census, these 709 commuting zones ranged in population in the 2000 Census from 5,000 (Southwest Jackson, Utah) to 16,000,000 (Los Angeles). Do you want to count Southwest Jackson as much as Los Angeles in your analysis of the relationship between these variables? Chetty et al. do in their figure. But if you weight them by population size, so each person in the population contributes equally to the relationship, that correlation that was -.76 — which they displayed as -.93 — is reduced to -.61. Yikes.
Here is what the plot looks like if you scale the commuting zones according to population size (more or less, not quite sure how Stata does this):
Now it’s messier, and the slope is much less steep. And you can see that gargantuan outlier — which turns out to be the New York commuting zone, which has 12 million people and with a lot more upward mobility than you would expect based on its family structure composition.
Finally, while we’re at it, we may as well attend to that nonlinearity that has been apparent since the opening figure. We can increase the variance explained from .38 to .42 by adding a quadratic term, to get this:
I hate to go beyond what the data can really tell. But — what the heck — it does appear that after 33% single-mother families, the effect hits its minimum and turns positive. These single mother figures are pretty old (when Chetty et al.’s sample were kids). Now that the country has surpassed 40% unmarried births, I think it’s safe to say we’re out of the woods. But that’s just speculation.**
*OK, OK: “wrong wrong wrong” is going too far. Absolute rules in data visualization are often wrong wrong wrong. Binning 709 groups down to 20 is extreme. Sometimes you have a zillion points. Sometimes the plot obscures the pattern. Sometimes binning is an inherent part of measurement (we usually measure age in years, for example, not seconds). None of that is an excuse in this case. However, Carter Butts sent along an example that makes the point well:
On the other hand, the Chetty et al. case is more similar to the following extreme example:
If you were interested in the relationship between age and earnings for a sample of 1,400 full-time, year-round women, you might start with this, which is a little frustrating:
The linear relationship is hard to see, but it’s about +$500 per year of age. However, the correlation is only .13, and the variance explained by linear-age alone is only 1.7%. But if you plotted the mean wage over ages, the correlation jumps to .68:
That’s a different question. It’s not, “how does age affect earnings,” it’s, “how does age affect mean earnings.” And if you binned the women into 10-year age intervals (25-34, 35-44, 45-54), and plotted the mean wage for each group, the correlation is .86.
Chetty et al. didn’t report the final correlation, but they showed it, even adding the regression line, so that Wilcox could call it the “bivariate relationship.”
**This paragraph was a joke that several people missed, so I’m clarifying. I would never draw a conclusion like that from the scraggly tale of a loose correlation like this.
What does race have to do with mobility? The words “race,” “black,” or “African American” don’t appear in David Leonhardt’s report on the new Chetty et al. paper on intergenerational mobility that hit the news yesterday. Or in Jim Tankersley’s report in the Washington Post, which is amazing, because it included this figure: That’s not exactly a map of Black America, which the Census Bureau has produced, but it’s not that far off:
But even if you don’t look at the map, what if you read the paper? Describing the series of maps of intergenerational mobility, the authors write:
Perhaps the most obvious pattern from the maps in Figure VI is that intergenerational mobility is lower in areas with larger African-American populations, such as the Southeast. … Figure IXa confirms that areas with larger African-American populations do in fact have substantially lower rates of upward mobility. The correlation between upward mobility and fraction black is -0.585. In areas that have small black populations, children born to parents at the 25th percentile can expect to reach the median of the national income distribution on average (y25;c = 50); in areas with
large African-American populations, y25;c is only 35.
Here is that Figure IXa, which plots Black population composition and mobility levels for groups of commuting zones: Yes, race is an important part of the story. In a nice part of the paper, the authors test whether Black population size is related to upward mobility for Whites (or, people in zip codes that are probably White, since race isn’t in their tax records), and find that it is. It’s not just Blacks driving the effect. I’m thinking about the historical patterns of industrial development, land ownership, the backwardness of racist elites in the South, and so on. But they’re not. For some reason, not explained at all, Chetty et al. offer this pivot:
The main lesson of the analysis in this section is that both blacks and whites living in areas with large African-American populations have lower rates of upward income mobility. One potential mechanism for this pattern is the historical legacy of greater segregation in areas with more blacks. Such segregation could potentially affect both low-income whites and blacks, as racial segregation is often associated with income segregation. We turn to the relationship between segregation and upward mobility in the next section.
And that’s it, they don’t discuss Black population size again, instead only focusing on racial segregation. They don’t pursue this “potential mechanism” in the analysis that follows. Instead, they drop percent Black for racial segregation. I have no idea why, especially considering this Table VII, which shows unadjusted (and normalized) correlations (more or less) between each variable and absolute upward mobility (the variable mapped above):
In these normalized correlations, fraction Black has a stronger relationship to mobility than racial segregation or economic segregation! In fact, it’s just about the strongest relationship on the whole long table (except for single mothers, with which it is of course highly correlated). So why do they not use it in their main models? Maybe someone else can explain this to me. (Full disclosure, my whole dissertation was about this variable.)
This is especially unfortunate because they do an analysis of the association between commuting zone family structure (using macro-level variables) and individual-level mobility, controlling for marital status — but not race — at the individual level. From this they conclude, “Children of married parents also have higher rates of upward mobility if they live in communities with fewer single parents.” I am quite suspicious that this effect is inflated by the omission of race at either level. So they write the following, which goes way beyond what they can find in the data:
Hence, family structure correlates with upward mobility not just at the individual level but also at the community level, perhaps because the stability of the social environment affects children’s outcomes more broadly.
Or maybe, race.
I explored the percent Black versus single mother question in a post a few weeks ago using the Chetty et al. data. I did two very simple OLS regression models using only the 100 largest commuting zones, weighted for population size, the first with just single motherhood, and then a model with proportion Black added: This shows that the association between single motherhood rates and immobility is reduced by two-thirds, and is no longer significant at conventional levels, when percent Black is added to the model. That is: Percent Black statistically explains the relationship between single motherhood and intergenerational immobility across U.S. labor markets. That’s not an analysis, it’s just an argument for keeping percent Black in the more complex models. Substantively, the level of racial segregation is just one part of the complex race story – it measures one kind of inequality in a local area, but not the amount of Black, which matters a lot (I won’t go into it all, but here are three old papers: one, two, three.
The burgeoning elite conversation about economic mobility, poverty, and inequality is good news. It’s avoidance of race is not.
Photo by Philip Cohen (for my other pictures from the march, see here).
I attended the 50th anniversary March on Washington march the other day. It looked to me like the majority of the crowd was Black, though I haven’t seen any estimates.
Here are a few recent polls on race relations and inequality, timed to coincide with the 50th anniversary of the March on Washington.
Source: Pew Research Center in LA Times.
Source: Gallup poll, June 13-July 5.
Source: General Social Survey (RACDIF1).
This is a serious post about life expectancy and inequality. But first a short rant.
Quick: Life expectancy in the U.S. is 78.7 Your parents are 85. How much longer are they expected to live? If you were worried about how much time you had left to spend with them, and you asked the helpful site seeyourfolks.com, you would get this:
This app, and the Slate piece about it, managed to combined two of my pet peeves: the understandable difficulty with understanding life expectancy, and the inexcusable use of second-person reporting on social science findings, which does more to discredit than to disseminate important research.
The error here (apart from “you”) is the common notion that “life expectancy” is the average age at which people of any current age can expect to die. If we were more rigorous about using the phrase “life expectancy at birth” it would be easier to grasp.
In 2008 the life expectancy at birth in the U.S. was 78.1. That means that if a group children born in 2008 lived every year of their lives exposed to the risks of death observed in 2008, their average lifespan would be 78.1 years. But those who made it to age 60 would live an average of 22.7 more years, for a total of 82.7. And those who live to age 99 would live an average of 2.4 more years, for an average of 101.4.
So “life expectancy” as commonly used is not a prediction of how long today’s babies will live — since we hope the future is better than living 2008 over and over — and it’s not a prediction of how long your elderly loved ones will live.
Life expectancy — for any age — is a measure of central tendency: the average number of years of life remaining. And so there is a dispersion around that mean. That dispersion is inequality. A very nice article in the open-access journal BMJ Open, by James Vaupel, Zhen Zhang and Alyson A van Raalte, describes the measure of life disparity. It’s complicated, but a neat tool.
Life disparity is the average number of years people are expected to live when they die. For example, in the U.S. in 2008 an infant who died on the first day of life died 78.1 years early. And a 78-year-old who died, counterintuitively, died 10 years early (since the life expectancy at 78 is 10). To understand what this measure means, consider that if everyone died at exactly 78.1 years of age, life expectancy would be unchanged but life disparity would be 0. On the other hand, the greatest life disparity would occur if all early occurred at age 0.
Life disparity and life expectancy usually go together. That’s because reducing early deaths has the biggest effect on both measures. Here is the cool figure from that paper:
Countries at the bottom left (0,0) have both the world’s highest life expectancy and the lowest life disparity in the world for that year, which occurred 89 times over 170 years. Countries below the diagonal have relatively low life disparity given their life expectancy; those above the diagonal (like the U.S.) have higher-than-expected life disparity for their level of life expectancy. In our case that reflects the fact that we do a pretty good job keeping old people alive, but let too many young people die.
The good news is that life expectancy is increasing in the U.S. (and most other places), and that the inequality between Blacks and Whites is getting smaller, as reported by the National Center for Health Statistics. That is, the Black-White inequality in average expectation of life at birth has shrunk.
The mixed news is that life disparity is much higher for Blacks than Whites — but that gap is falling as well. Here are those numbers for 1998 and 2008 (I did the life disparity calculations from this and this, and will happily share the spreadsheet). Click to enlarge:
So Black deaths are more dispersed than White deaths: 14 and 13 for males and females, compared with 12 and 11. For comparison, the Swedish female life disparity is 9. What does a higher disparity mean? Generally, a larger share of early deaths. That’s why the race gap in life expectancy at birth is greater than the race gap in life expectancy at older ages — average 65-year-old Whites and Blacks have more similar life expectancies than do infants.
Why is life disparity more interesting than life expectancy alone, and how does this help explain Black-White inequality in the U.S.? For one thing, high life disparity indicates either relatively unhealthy or dangerous living conditions at younger ages. So it’s partly a measure of the quality of life. Vaupel et al. add:
Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age makes savings more worthwhile, raises the value of individual and public investments in education and training, and increases the prevalence of long-term relationships. Hence, healthy longevity is a prime driver of a country’s wealth and well-being. While some degree of income inequality might create incentives to work harder, premature deaths bring little benefit and impose major costs. Moreover, equity in the capability to maintain good health is central to any larger concept of societal justice.
I think what they say about differences between countries would apply to differences between groups within a society as well.
Trigger warning: a little hate speech follows. If you’re interested in the hate-Trayvon stuff I’m sure you’ve found it already. Just so you know what I mean, here are a few comments from the Atlantic comment section:
…any rational white person should be presumptively afraid of young black men, so long as they “look” and act a certain way. Why? Because they commit a huge, disproportionate number of crimes against white people, and because they act menacingly.
The only solution is to make sure we have less blackies in society, sterilization of prisoners is probably the way to start to make sure they don’t leave any off-spring and forced abortions of mothers on welfare.
Its not fear to be wary of young black males, its simple common sense. Even Jesse Jackson agrees. What you should fear though is the Federal leviathan and the presstitute Corporate Media which will both come down on your head like an anvil if you are White and dare defend yourself from violent, feral blacks.
Trayvon actually got less than what he deserved. PS. not including eternity in Hell where he now resides. [You might be glad to know that the up-vote:down-vote ratio on this one is 2:1. -pnc]
That kind of overt racism seems to simply drive many reasonable people out of the comments section, so there isn’t much resistance. At the same time, about 100 people tweeted out the post, and the ones who had faces visible in their Twitter avatars were mostly Black:
(To fill out the square I enlarged the guy with 90,000 followers.)
I don’t have the data or the know-how to really analyze web traffic on the blogs I write for. But I do see some broad patterns. For example, stories about race get a higher ratio of tweets to Facebook likes, which could represent the greater Black presence on Twitter. The Zimmerman post has a FB/Twitter ratio of 2.5 at this writing, compared with 11.3 for my last post on gay marriage.
Once again, the divergences in this conversation are more obvious than the convergences. I wonder if this is getting better or worse. One piece of evidence suggests it might be getting worse.
Believe it or not, attention to this case has been low by the standards of “racially charged news stories,” according to polling from the Pew Research Center for the People and Press.
The final days of the trial of George Zimmerman … attracted relatively modest public interest overall. In a weekend survey, 26% say they were following news about the trial very closely. … However, the story has consistently attracted far more interest among blacks than whites – and that remained the case in the trial’s final days. Blacks are more than twice as likely as whites to say they tracked news about the Zimmerman trial very closely (56% vs. 20%).
That 26% interest is a big enough slice of the population to make CNN go wall-to-wall, but it’s not discourse-shattering. The most interesting part of that Pew report is the historical trend of Black and White interest for a series of related public moments. Their table is sorted so that the events with the largest Black-White interest gaps are at the top.
All the events show greater Black than White interest, unsurprisingly. But if you squint – or sort the table by date – you can see that the gap has widened since 1992. Here are the Black and White interest levels arranged by date:
This is only 10 events that generated national coverage, and there could be any number of reasons for the trend, so we can’t make too much of it. The Rodney King point is maybe in a different category because it’s not just a trial but a major conflagration afterwards. But that decline in White interest is pronounced even if that point is removed. If White interest in our “conversation on race” is declining, the apparent polarization we see now suggests it might be the middle that has lost interest.
My take on this is whole thing is mostly negative. Please correct me if I’m wrong.