Work Requirements Can’t Solve Poverty

whoispoor1

Work requirements can’t solve poverty because 97 percent of the poor are either children, retired, disabled, students, caregivers, or already working. Public opinion research consistently shows high levels of support for aiding the poor, matched with equally high levels of concern that aid only be given to those who deserve it. This concern to distinguish between the deserving and undeserving, while an understandable impulse, has been extremely harmful to producing effective anti-poverty policies. It has also mixed with racial stereotypes of lazy blacks to produce an image of the poor as undeserving others who can be dismissed as ‘takers’  unworthy of aid and bent on gaming the system.

Perhaps the simplest way to remind the public that the poor really do deserve our help is just to remind the public of who the poor are, as Brookings does in the graph below:

whoispoor1

I believe all people deserve aid, but even if you use a stricter criteria or you think aid needs to come with tough love, the overwhelming majority of the poor aren’t poor because they’re too lazy to work and need paternalistic oversight – they’re poor because they’re children, elderly, students, disabled, or already working a job that doesn’t pay enough to lift them out of poverty. Even among the 3 percent that aren’t in the labor force, many have probably given up after a long bout of unemployment.

Effective work policy for the poor means getting jobs to pay enough to lift people out of poverty, not adding to the misery the poor already experience by punishing them for being unable to find good work.

Most importantly though, work is never going to replace public and non-profit assistance to children, the elderly, students, the disabled, and caregivers. Cuts to anti-poverty programs have a real impact on people who are going through hard times. Children didn’t choose to be born into poverty. Students are trying survive poverty while bettering their future. Caregivers are often the only ones available to help others in their families. The disabled and the elderly aren’t able and aren’t expected to find productive employment. These are people who deserve help, not a government making a concerted effort to make their lives even more difficult.

 

 

 

 

Don’t panic over a positive medical test…use Bayes’ theorem to put it in perspective

My baby’s newborn hearing screening came back positive – that is, they referred us to an audiologist for further testing. Like all parents, I’m worried. But understanding statistics and probability makes a me a little less worried, so I’m writing this up to help me relax about it until we see the audiologist in a few weeks (one possible cause is simply some residual fluid in the baby’s ear, so they wait a few weeks before testing again).
The basic intuition behind the statistics in reacting to a positive medical test is that it maters how rare the condition is, and how likely the test is to get it wrong. When 1,000 newborns are screened for hearing loss about 22 will test positive. Two of those 22 will be the 2 in 1,000 who actually have hearing loss (the actual rate of hearing loss in newborns). But of the 998 newborns who don’t have hearing loss, about 20 of them will get false positives (a 2 percent false positive rate). That means of the 22 positive test results – the category my daughter falls in – only 2 out of the 22, or about 9 percent actually have hearing loss.
To calculate more precisely the probability that my daughter really does have some hearing difficulty given she had a positive hearing screening, we need to know three numbers: the overall percentage of newborns with hearing loss(between .001 and .003); the rate of false positives on the test (.02); and the rate of false negatives on the test (between .02 and .09). (Note: I found these numbers by reading abstracts in medical journals for the ABR hearing test).
Combining these three numbers using Bayes’ theorem, the odds of hearing loss given a positive screening result is somewhere between 4 percent and 13 percent. That’s enough to make me worry and see an audiologists – but it’s a lot less worrying than if I only knew she had a positive screening on a test with a 2 percent false positive rate. (I’ve posted the code for combining the three numbers below for those who are interested in the details of how this works).
A few more things that aren’t in the math: 1) most importantly, she can clearly hear us;  2) this is one of many screenings for newborns, which increases the odds that at least one of them will be false positive; 3) my daughter is demographically in a low-risk group (e.g. young mother etc.);  4) the test depends at least as much on the newborn being relatively calm during testing as it does on hearing ability, and she was being a little fussy; and 5) she passed in one ear but not the other. Combine all those things and it makes me think we should lean towards the 4 percent end of the range of estimates.
Code is below:
#Using Bayes rule with medical testing info to see how worried a test should make you
#A is hearing loss
#B is a postive test
bayes_med<-function(base_rate, false_positive, false_negative){
hit<-1-false_negative
prob_B<-((hit*base_rate)+false_positive*(1-base_rate))#P(B)=P(B|A)*P(A)+P(B|not_A)*P(not_A)
posterior<-(hit*base_rate)/prob_B#P(A|B)=(P(B|A)*P(A))/P(B), Baye's Theorem
posterior
}
bayes_med(.002, .02, .055)#medium estimate
bayes_med(.001, .02, .09)#low estimate
bayes_med(.003, .02, .02)#high estimate

Freedom of Speech is not Freedom from Criticism (A note on political correctness)

Political correctness has been a major source of anger throughout the Republican primary, fueling Donald Trump (and more briefly, Ben Carson). It has even reached the point where conservatives have argued that political correctness is limiting their freedom of speech. So, I thought I should clarify:

You have the right to say things that are hurtful and offensive to other groups of people (or, in conservative lingo, to be politically incorrect). I have the right to tell you that what you’ve said is hurtful,offensive, and possibly also bigoted, sexist, or racist, depending on the particular comment. If a lot of people choose to exercise their right to criticize what you’ve said, that’s not a limit on your free speech – it’s other people, using their same right to free speech, criticizing you. Of course, being criticized is unpleasant, and you can argue that the criticisms are misguided, but no one’s freedom of speech is being violated in this process.

 

How unlikely was Golden State’s 4 for 30 from 3-point range performance?

I’m taking a relatively rare (for the blog) detour into sports statistics. Golden State was a heavy favorite to beat Los Angeles on Sunday (3/6/16), but lost in part due to poor 3-point shooting, hitting a mere 4 of their 30 3-point attempts. This got me wondering just how unlikely that poor of a 3-point performance is.

To get something out of the way before we get into the math – I do believe there is a hot hand effect in basketball. However, outside of three-point shooting contests, where players shoot exactly the same shot multiple times in a row, the effect is fairly small – which is why a lot of the early papers missed it altogether. There’s also basically no evidence of a cold hand, which is what we’re investigating here. (See this article from Vox for a decent summary). All that’s just to say, an estimate based on the classic assumption that each shot is independent of the shot before it is just an estimate – but probably a fairly reasonable one.

This season, Golden State has made 41.2 percent of their 3pt attempts. This means when they shoot 30 times, we’d expect them to make around 12 or 13 of their shots. In fact, leaving the math aside for later, we can see that we’d expect exactly 12 threes to go in 14.6 percent of the time, with each possible outcome getting less and less likely as we move away from 12.

Golden State 3s

As you can see, the odds of the Warriors making exactly 4 threes is very small, and the odds of them making 3,2,1, or 0 threes is so small it doesn’t show up on the graph. Adding up the ways the Warriors could make 4 or fewer threes while shooting 30 times, the odds of them doing so are .099 percent.

Let’s add some context here by comparing the  Warriors as a whole to Steph Curry. Curry was 1/10 from three in the Warrior’s loss, and this season he’s making his threes 45.9 percent of the time. Here’s the likelihood chart for Curry when he shoots 10 threes.

Curry 3s

While Curry making 1 or fewer threes in 10 shots is rare, it’s not surprising to see it happen at least once a season. It happens just over 2 percent of the time. While this sounds pretty rare, it translates into 1 out of every 49 games, and the NBA plays an 82 game season, plus playoffs. (When talking about rare events it’s important to keep in mind how often there’s a chance for the event to occur).

By contrast, the Warriors as a team making only 4 out of 30 shots should only occur once every 1,007 games. So either we just saw cold shooting of the sort that should only happen about once every 12 seasons due to chance, or there was something about the defense or some other unknown factor that was throwing off the Warrior’s three-point attempts. (I expected the Warriors to win in a blowout and was watching the U.S. beat France in women’s soccer instead, so I don’t really know if there was something visibly different to explain the poor three-point shooting).

The comparison between the Warriors as a whole and Curry also shows just how quickly sample size starts to make a difference. The Warriors going 1 for 10 for their first 10 threes would be even less unusual than Curry going 1 for 10 (the team as a whole shoots less accurately than Curry). The difference is that the poor shooting by the team spanned an entire 30 shots. Shooting incredibly poorly over a 10 shot span might be a once a season occurrence, but shooting poorly over a 30 shot span is a once every 12 seasons occurrence.

A few words on the math in this post – uninterested readers can skip this as all the conclusions have already been mentioned above.

The odds of making any particular shot in basketball can be reasonably (though imperfectly) estimated using the same math used for calculating probabilities of a biased coin. Thus, if flipping heads is making a 3, we could say that the coin used for Curry has a 45.9 percent chance of landing on heads, while the coin used for the Warriors has a 41.2% chance of landing on heads. The math for then figuring out how likely it is to flip exactly k heads in n flips, with p percentage of flipping a head is well-established.

It’s a basic binomial distribution, where in the case of basketball it tells us the probability of making precisely k shots in n attempts given that p percentage of shots go in over the long run.

\frac{n!}{k!(n-k)!}p^k(1-p)^k

When 30 shots are taken, there are 31 possible outcomes (0-30) as seen in the first chart above. Calculating this separately for each would be quite tedious. Fortunately, the R statistical programming language allows this sort of calculation and doesn’t even require any looping. k can simply be a vector of all possible outcomes 0 through n. The code I used for the calculations and graphs in this post is below.

##Setting up a function to calculate binomial probabilities
binomial<-function(k,n,p){
factorial(n)/(factorial(k)*(factorial(n-k)))*p^k*(1-p)^(n-k)
}

##Calculating odds of Warrior's making 4 or fewer threes
bin.prob<-binomial(k=0:30,n=30,p=.412)
sum(bin.prob[1:5])#The first five possible outcomes are 0,1,2,3, and 4.
100/(sum(bin.prob[1:5])*100)#Translates to this happening every X games

##Graphing
library("ggplot2")
library("ggthemes")
k<-0:30
data<-data.frame(k,bin.prob)
plot<-ggplot(data, aes(x=as.factor(k),y=bin.prob))+geom_bar(stat="identity", fill="blue")
plot<-plot+ggtitle("Distribution of 3-pointers made when the Warriors shoot 30 3-pointers")+
ylab("Likelihood of making X number of threes")+ xlab("Number of made threes")
plot+theme_tufte()

##Steph Curry
s.curry<-binomial(k=0:10,n=10,p=.459)
sum(s.curry[1:2])#Odds of Curry making 0 or 1 threes
100/(sum(s.curry[1:2])*100)#This happens once out of X games

k<-0:10
data.c<-data.frame(k,s.curry)
plot.c<-ggplot(data.c, aes(x=as.factor(k),y=s.curry))+geom_bar(stat="identity", fill="blue")
plot.c<-plot.c+ggtitle("Distribution of 3-pointers made when Curry shoots 10 3-pointers")+
ylab("Likelihood of making X number of threes")+ xlab("Number of made threes")
plot.c+theme_tufte()

 

Coal Mining and Population Loss

Fig 2

My first peer-reviewed publication is out in the Journal of Appalachian Studies. I’ve posted the full paper here,  and below is a shortened and non-technical version. The Data, Methods, and Analysis section is rewritten for this blog to make it more accessible for lay readers, while the other sections are merely abridged.

Coal Mining and Population Loss

If your community is making its living primarily by the export of raw materials for manufacture elsewhere, then along with your logs or your wheat or your cattle or your minerals you are exporting jobs, and then you will be exporting your young people to take those jobs.

– Wendell Berry (2010c, 60)

Introduction 

From the beginning of the European colonization of the Americas, Appalachia was notable for its rich natural resources. Originally it was desired for its wealth of timber, and then later for coal. In spite of this resource wealth, Appalachia has been poor for most of its history. The question, then, is Why is Appalachia poor? More specifically, What contribution did natural resource wealth make to Appalachia’s development? Would Appalachia have been even poorer in the absence of timber and coal, or did its natural resource wealth actually cause or exacerbate poverty?

Before coal, Appalachia was desired for its timber, leading to the destruction of rich farmland as well as a population cycle of boom and bust following the rise and fall of the Appalachian timber industry. In a detailed study of West Virginia, Ronald Lewis (1998) found that over 60 percent of West Virginia’s farmland was lost, and 90 percent of the state suffered soil erosion. It takes between 300 and 1,000 years to replace an inch of topsoil, which means this damage is irreversible for centuries. Following the timber boom in Appalachia, around 750,000 people moved out of the region.

Economic Theory in the Writings of Wendell Berry

One of the defining characteristics of a theory is the information that it considers to be relevant. Philosophical theories of ethics, for instance, are almost entirely determined by their informational criteria: utility for utilitarians, liberty for libertarians, equality for egalitarians, and so on (Sen 1999). Theories in economics are similarly determined not only by the relationships they posit among various aspects of the economy, but by the initial choice of which aspects are considered important. Inevitably, in the choice of what information matters and how it is to be interpreted, facts and values become entangled (Putnam 2002). This inevitable entanglement is one of many reasons to pay particularly close attention to the way in which individuals interpret their own economic situations.

Wendell Berry is a Kentucky farmer, author, and poet whose ground-level view of the economy stands in stark contrast to more abstract modeling. Herman Daly draws out this contrast well and points to its philosophical roots in the foreword to a collection of Berry’s essays on economics:

Aristotle distinguished “oikonomia” from “chrematistics.” Oikonomia is the science or art of efficiently producing, distributing, and maintaining concrete use values for the household and community over the long run. Chrematistics is the art of maximizing the accumulation by individuals of abstract exchange value in the form of money in the short run. Although our word ‘economics’ is derived from oikonomia, its present meaning is much closer to chrematistics.  (Daly 2010, x)

Berry focuses on economics as household management or stewardship and urges a return to a more holistic vision of economics: “Any little economy that sees itself as unlimited is obviously self-blinded. It does not see its real relation of dependence and obligation to the Great Economy; in fact, it does not see that there is a Great Economy. Instead, it calls the Great Economy ‘raw material’ or ‘natural resources’ or ‘nature’ and proceeds with the business of putting it ‘under control’” (2010d, 130).

Berry argues that the economy is built up in stages, with nature being the foundational stage, followed by land use, then manufacturing, and finally the consumer economy. For Berry, economics is about the stewardship and distribution of resources, not the accumulation of wealth. Berry also shifts the unit of analysis of economics away from individuals and toward places, writing, “[W]e need to stop thinking about the economic functions of individuals for a while, and try to learn to think of the economic functions of communities and households. We need to try to understand the long-term economies of places – places, that is, that are considered as dwelling places for humans and their fellow creatures, not as exploitable resources” (2010a, 78).

Rather than seeing individuals as components in economic production, Berry argues that the economy must instead be shaped around an understanding of people as being integrally connected to their land and community. Berry is consistently critical of an economic paradigm that reduces individuals to their productive abilities (labor) and consumer desires (consumption):

By what standard, or from what point of view, are we permitted to suppose that the displaced people were not needed in their original places? According to the industrial standard and point of view, persons are needed only when they perform a service valuable to an employer. When a machine can perform the same service, a person then is not needed…. Our mobility, whether enforced or fashionable, has dismembered and scattered families and communities…. Might it not be that displaced persons were needed by their families and their neighbors, not only for their economic assistance to the home place and household, but for their love and understanding, for their help and comfort in times of trouble? (2010b, 21)

This paper attempts to draw some specific hypotheses out of Berry’s economic theory in order to test them using the statistical tools of the academy.

First, I expect that areas with high concentrations of extractive industries will experience short term economic growth but long term economic stagnation following resource extraction. This is in keeping with Berry’s notion that because having a self-renewing ecological system intact within a locality is the foundation of a functional economy, any system that does not prioritize nature and land use will be unsustainable. Second, I expect to see declining populations following resource extraction. Berry argues that in exporting raw materials, one is exporting the basis of the economy, and therefore exporting jobs. Given the relative mobility of the modern era, this means that young people will follow those jobs and, consequently, be lost to their home communities.

Data, Methods, and Analysis

Those of you interested in the technical details  should refer to the full paper. For the purposes of this blog, the results can be summarized in a few graphs. Each graph shows the relationship between coal production in 2000 and population change between 2000 and 2010 after controlling for other factors, including the county’s size, economic state, and education levels. Thus, the results are visual depiction of the relationship between coal production and population change, other things (economy, education, county size) equal.

First, for all Appalachian counties:

Fig 1

Appalachia is quite large, covering parts of 13 states, and most counties don’t mine any coal, so I also looked at just the 110 coal-mining counties:

Fig 2

The relationship is clearer and stronger without the extra noise of all the counties that aren’t in coal country. The paper also looks at the relationship in pairs of coal-mining intensive states, Kentucky and West Virginia, Alabama and Mississippi, and Ohio and Pennsylvania. Kentucky and West Virginia are shown below, but all three state pairings show a similar pattern:

Fig 4

 Conclusion and Discussion

The analysis supports the hypothesis that increased coal mining leads to slower population growth (or faster population loss)….This study does not find support for the idea of coal production leading to economic stagnation, and instead shows coal production correlating with decreased unemployment and poverty and increased per capita income.

By starting with the work of Wendell Berry, this paper draws in another dimension to the economic and environmental debate over natural resource extraction. Berry has written extensively about the impacts on local communities that often go unobserved in statistical records and national debates. As an offshoot of the importance of places as dwelling places and not mere natural resources, Berry introduces the concept of affection as a counterweight to the ideal of scientific objectivity. Berry writes,

It is readily evident, once affection is allowed into the discussion of “land use,” that the life of the mind, as presently constituted in the universities, is of no help. The sciences are of no help, indeed are destructive, because they work, by principle, outside the demands, checks, and corrections of affection…The problem simply is that land users are using people, places, and things that cannot be well used without affection. To be well used, creatures and places must be used sympathetically, just as they must be known sympathetically to be well known. The economist to whom it is of no concern whether or not a family loves its farm will almost inevitably aid and abet the destruction of family farming .(2010a, 82).

Berry’s writings serve as a reminder that it is often things that cannot be easily measured that may be of the most importance in determining public policy. Most of the debate over the extraction of natural resources has framed it as a conflict between economic growth and environmental protection. By reframing our analysis to look at communities considered as dwelling places that need both functioning local economies and a healthy environment, Berry points to the overall impact the over-extraction of resources has in ultimately making the surrounding communities less attractive places to live.

 

 

The flawed logic of conservative opposition to regulations: the case of jury duty

Conservatives often start from the premise that individual freedoms ought to be maximized. Since regulations limit freedoms, regulations therefore ought to be minimized. But the concept of freedom is nowhere near as straightforward as it initially appears. In deference to the general conservative love of the Constitution, the complicated nature of individual freedom can be illustrated with the example of jury duty.

In order to insure individuals are free from arbitrary or capricious imprisonment, the sixth amendment sets forth the right to a trial by an impartial jury. The jury, however, has to come from somewhere, and so the government compels individuals to give up their time and serve jury duty. Even a relatively straightforward right – the right to avoid being unfairly convicted – wound up imposing a corresponding obligation on others, the obligation to give up their time in order to participate in a system designed to increase the odds of getting a fair trial.

The government obligating me to do something is a reduction of my personal freedom, and jury duty isn’t the only example. Individual freedoms stop at the point where they violate other’s freedoms (e.g. you can’t punch me in the face for writing a blog you disagree with), a principle most conservatives agree with. By itself this wouldn’t necessarily entail a positive obligation on others, but it turns out that not everyone voluntarily cooperates, and thus society needs an enforcement mechanism. To restrict people’s freedom to violate your freedom via theft, assault, or murder, society is obligated to construct a system to both judge and enforce laws – a system that others are obligated to fund through taxes.

The right for our property not to be polluted by those upriver springs directly from the right to property. Other people can no more freely damage my property than they can take it – both are forms of theft. But since pollution doesn’t recognize property lines, this restricts my upriver neighbors from disposing of their property as they wish.

Health and safety regulations in the workplace spring from worker’s asserting rights to safe, decent working conditions. These rights are still contested, but it is clear that in a meaningful way they increase the freedom of workers to live safe, healthy lives. At the same time, they decrease the freedom of employers to offer contracts that involve work in unsafe conditions. The same tradeoff is present in minimum wage legislation, and discussions of paid family leave.

Society is complicated, and any meaningful discussion of freedom needs to recognize that there’s no simple maximization of freedom, but rather a complicated balancing act where the freedoms to own property, not be arbitrarily imprisoned, live healthy lives, and spend time with newborn children all involve corresponding restrictions on other people’s freedoms.

Regulations – like the right to a trial by jury – can increase freedom. Regulations can also balance freedoms, the way an environmental regulation balances freedom of economic activity with the freedom of others (and future others) to enjoy the environment. Finally, poor regulations can reduce freedom. Not everyone agrees on which freedoms are most important to protect or which regulations will do the best job protecting them, but the idea that regulations are monolithically bad and freedom-decreasing rules imposed by the government is simply false. Democratic deliberation about the extent of regulations is a necessary and vital part of government by the people, but the premise that regulations and freedom are always opposed to each other isn’t a solid basis for an argument.

Why the narrative of personal responsibility slips so easily into racism

http://www.brookings.edu/blogs/social-mobility-memos/posts/2015/07/22-opportunity-gap-isnt-going-away-reeves

When it comes to explaining poverty and inequality in the U.S., there tend to be two broad categories of explanations. The first is personal responsibility. On this narrative, poverty and inequality are caused by personal failings. The second focuses on institutional factors, arguing that poverty is a result of the choices we’ve made about the structures of our political and economic institutions.

The continued existence of racial inequality poses a serious dilemma for the narrative of personal responsibility. In the United States, there is a large racial gap in wealth, and it hasn’t been shrinking over time.

 

The narrative of personal responsibility remains a popular explanation among conservatives, and some conservative outlets like the Wall Street Journal have even gone so far as to declare an end to institutional racism. But can personal responsibility really explain the racial wealth gap?

For any given individual it’s easy enough to find shortcomings that explain why they didn’t graduate high school or why they wound up in or near poverty. But if we want to explain why blacks, as a group, are not as wealthy as whites, then we’re left with two options. For personal responsibility to explain the wealth gap, it’s not enough to say an individual failed to live up to their responsibility, one would have to claim that blacks, as a group, are less likely to live up to their responsibilities than whites. Less likely to try hard to get a good education. Less likely to make the financial choices that lead to wealth accumulation. But, of course, to say that blacks, as a group, are less responsible, is the very definition of racism – it’s attributing a negative trait to an entire race.

Next time someone tells you the poor need to pull themselves up by their own bootstraps, ask them why blacks, according to the data on wealth, are so much worse at this bootstrap pull than whites. Could it be that centuries of slavery, a hundred years of legal discrimination, and decades of ongoing de facto discrimination have left them without bootstraps?

The other explanation for poverty and racial inequality is institutional/structural. This explanation enjoys two major advantages. First, it can explain group-level outcomes without recourse to the idea that those outcomes must be driven by innate differences between the groups. Instead, they could be driven by institutional differences in the way the groups are treated. Second, There’s a lot of evidence on how our past and present political and economic institutions are leading to racial disparities.

For an overview of institutional discrimination, I highly recommend Ta-Nehisi Coates’ lengthy feature article in the Atlantic, “The Case for Reparations.” There’s also a good feature on the history of voting rights and the ongoing effort to role them back in last week’s New York Times Magazine. And here’s a shorter piece from Vox on how the school system’s racial biases create a gap in educational achievement by pushing black students out of the school system and into the criminal justice system.

For book-length treatments, I highly recommend Michelle Alexander’s The New Jim Crow, which traces the history of how institutions were transformed at the end of the Jim Crow era in ways that made discrimination less visible but did not eliminate it. For an academic approach, I recommend Disciplining the Poor, by Soss, Fording, and Schram.

Finally, it’s worth highlighting one of the more obvious and direct ways in which discrimination persists. Black applicants find themselves at a severe disadvantage in the labor market. Economists Marianne Bertrand and Sendhil Mullainathan tested this by sending out resumes that differed only in the name at the top, comparing Greg Baker and Emily Walsh to Jamal Jones  and Lakisha Washington. They found that Greg and Emily received 50 percent more callbacks for interviews than Jamal and Lakisha.

So where does this leave personal responsibility? It’s not wrong to encourage individuals to be responsible and to make good choices. It is wrong to suggest that individual choices are the only things that determine individual outcomes, and it’s very wrong to suggest that individual choices determine group-level outcomes. For example, telling a high school student (who you personally know) that they should still try to graduate from high school even in an unfair school system is a good thing to do. Ideally, you’d also encourage them to work with others to change the school system.

The problem is when personal responsibility is used as something to be preached to others – to people you don’t know – and used as an excuse not to work for just institutions. Personal responsibility can’t explain all the outcomes that we see in society, and in particular it can’t explain the vast chasm or racial inequality in the U.S. today.  Structures and institutions matter. The good news is that it’s in our power to  change them.

Go Read Ta-Nehisi Coates’ ‘Letter to My Son’

As a general rule, you should read everything Ta-Nehisi Coates writes. Over the weekend, he exceeded his own already exceptional standards, publishing Letter to My Son in the Atlantic. More than anything I’ve ever read, Coates manages to make the reader feel, just for a moment, the full weight of the damage done by racism, past and present:

In America, it is traditional to destroy the black body—it is heritage. Enslavement was not merely the antiseptic borrowing of labor—it is not so easy to get a human being to commit their body against its own elemental interest. And so enslavement must be casual wrath and random manglings, the gashing of heads and brains blown out over the river as the body seeks to escape. It must be rape so regular as to be industrial. There is no uplifting way to say this. I have no praise anthems, nor old Negro spirituals. The spirit and soul are the body and brain, which are destructible—that is precisely why they are so precious. And the soul did not escape. The spirit did not steal away on gospel wings. The soul was the body that fed the tobacco, and the spirit was the blood that watered the cotton, and these created the first fruits of the American garden. And the fruits were secured through the bashing of children with stovewood, through hot iron peeling skin away like husk from corn.

As Coates points out and then brings to life in his letter, it is one thing to have an intellectual understanding of the facts and figures, but it is as important to stop and remember the actual lived impact of all the policies and analysis that I (and many others) write about and study. Coates reminds us that:

all our phrasing—race relations, racial chasm, racial justice, racial profiling, white privilege, even white supremacy—serves to obscure that racism is a visceral experience, that it dislodges brains, blocks airways, rips muscle, extracts organs, cracks bones, breaks teeth. You must never look away from this. You must always remember that the sociology, the history, the economics, the graphs, the charts, the regressions all land, with great violence, upon the body.

Now go read the rest of it.

Of Riots and Racism

I should be writing term papers, but I’ve been stunned at the amount of casual racism floating through social media and the internet in the wake of riots in Baltimore. An overwhelming number of people seem to believe one can explain riots and protests in Baltimore simply by saying people are making the choice to riot. But this explains precisely nothing when the question is why people are making those choices.

To dig into this a little deeper, think of choices as being determined by a combination of internal factors (things we like/dislike, tendencies towards certain behaviors) and external factors (the choices in front of us, the things we’ve experienced, what we’ve been exposed to). There’s an understandable – though in this case unfortunate – tendency to focus on the internal factors that drive behavior. After all, in our day to day dealings with other people, and even with ourselves, those are the ones we can hope to exert some influence on. I can’t change large social and economic problems by myself, so most of the time it makes sense to focus on things that I have more control over – to find ways to make the best of a bad situation.

But when faced with a social phenomena where we’re trying to explain the behaviors of a large group, it doesn’t make much sense to turn to internal factors as an explanation. It’s far more likely that there’s a common external factor that has pushed the entire group towards that behavior. Let’s step away from Baltimore for a minute. There’s a large and well-documented wealth gap and education gap between blacks and whites. The wealth and education gaps can either be explained by external factors like “two hundred fifty years of slavery, ninety years of Jim Crow, sixty years of separate but equal, and thirty-five years of racist housing policy” (Ta-Nehesi Coates), or one can try to explain the differences between races through internal factors. But, of course, suggesting that blacks and whites are different on internal factors (like laziness and intelligence, to take two commonly cited examples that would explain the wealth and education gaps) is the very definition of racism.

Returning to Baltimore, the same basic logic applies. Either poor blacks are rioting because poor blacks are inherently violent and prone to riot, or they are rioting because of a brutal police culture marked by racial injustices and a political and economic system that has utterly failed many of the residents of Baltimore. The failure so stark that it is even reflected in life expectancy data, with Johns Hopkins’ John Bagger explaining, “only 6 miles separate the Baltimore neighborhoods of Roland Park and Hollins Market, but there is a 20-year difference in the average life expectancy.”

And yet people turn instead to the time-tested refrain of personal responsibility. The problem is that almost any attempt to explain Baltimore in terms of internal factors and personal responsibility is bound to slip into racism because it has nowhere else to go. Explaining a group-level social phenomena requires an account of what that group has in common – and if it isn’t an external motivation, it must be that all the poor black people suddenly had a collective failure of personal responsibility. (And again, we’re back to an inherent difference in the races rather than external differences in how they’re treated).

Sometimes it makes sense to preach personal responsibility and tell people to make the best of a bad situation. But sometimes, it’s the situation itself that needs to change.

None of this is to suggest that violence is either the correct response or the most effective response to racial injustice. As Martin Luther King Jr. said in response to riots in the 60:,

I would be the first to say that I am still committed to militant, powerful, massive, non­-violence as the most potent weapon in grappling with the problem from a direct action point of view. I’m absolutely convinced that a riot merely intensifies the fears of the white community while relieving the guilt.

From everything I’ve seen, King is entirely correct that the white community has used riots as a way to relieve their guilt (and stoke their fears) in a way that they could not have done if the protests had remained peaceful. Nonetheless, as part of the white community and speaking mainly to the white community, I want to end by echoing King’s call in the same speech to be more concerned about justice and humanity than about tranquility:

But it is not enough for me to stand before you tonight and condemn riots.It would be morally irresponsible for me to do that without, at the same time, condemning the contingent, intolerable conditions that exist in our society. These conditions are the things that cause individuals to feel that they have no other alternative than to engage in violent rebellions to get attention. And I must say tonight that a riot is the language of the unheard. And what is it America has failed to hear? It has failed to hear that the plight of the negro poor has worsened over the last twelve or fifteen years. It has failed to hear that the promises of freedom and justice have not been met. And it has failed to hear that large segments of white society are more concerned about tranquility and the status quo than about justice and humanity.