"Hey, there ain't no space between us!" - a flight attendant who saw me reading this book This is a very important book about a very important topic (segregation and race relations). It is also a book that strongly agrees with my priors about how the world works. And not just my priors, but with my desires - I want segregation to be a bad thing. So because I'm so biased in favor of this book's thesis, I'm going to try to be especially hard on it in this review. Just realize that that's what I'm doing here. You should absolutely read this book. The research it explains is eye-opening, well-executed, and very important for our national future. And the theory that Enos weaves to explain his observations probably captures important features of reality, and deserves to be a central
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Despite these limitations, Enos does - in my opinion - convincingly demonstrate two-thirds of his theory. He does show that the size and proximity of an outgroup pretty predictably generate negative feelings toward that outgroup. But the third part of his theory - the idea that geographic segregation plays a big role, above and beyond the impact of human interaction, in determining which groups get defined as an "outgroup" in the first place - is harder to demonstrate. And it's here that I feel Enos; methods, though probably the best available, don't end up being conclusive.
This is due to two interrelated problems: A) the question of contact vs. context, and B) the problem of scale. Both are problems that Enos discusses extensively, but in the end I don't think there's an easy solution.
The problem is that it's very difficult to separate contact from context, observationally. In a lab, you can control the two - you can have people sit in chairs not talking to each other, or allow them to talk. But in the real world, it's hard to tell who's interacting with whom. If you put Protestants and Catholics next to each other in a city and you see a deterioration in relations between the two, was it due to proximity (Enos' theory) or due to some kind of negative interaction that sprung up between the two? If you see that desegregation leads to an improvement in race relations, was it because people got used to each other after chatting on the street, or because desegregated living arrangements made group differences less salient (Enos' theory)? Hard to tell.
Sometimes context and contact aren't even conceptually distinct. For example, take Enos' famous Boston Train Experiment. In this experiment, Enos sent Spanish-speakers to train stations in Boston, and found that observing Spanish speakers made Anglophone whites more likely to take a hard line against immigration.
Was this an experiment about contact, or context? The title of Enos' paper is "Causal effect of intergroup contact on exclusionary attitudes", which would seem to indicate that it's the former. But in "The Space Between Us", Enos writes that he "altering both space and contact", "increasing socio-geographic impact", and "moving Boston to the right on the horizontal axis of the plane of context" (p. 110). He thus claims that the Train Experiment altered context - that it didn't just represent an interaction between Anglo white Bostonians and Spanish speakers, but that it actually made those Anglo white Bostonians feel like Spanish speakers had moved in next to them. Enos thus claims this experiment as evidence for the impact of context on racial attitudes.
The truth is, we don't know which it was. It might be that the Anglo white train commuters were annoyed at the experience of hearing a language they didn't understand, and that Enos was therefore measuring a negative contact effect. Or it's possible the Anglo white train commuters really did feel like their neighborhoods were becoming more Hispanic. (Asking additional survey questions might have helped differentiate these two hypotheses, but those responses might not have been completely reliable.)
Enos says that when possible, he attempts to control for intergroup contact when measuring the effect of context. This is the right approach, but the problem is that it's often impossible outside of a lab. The same issue crops up in some of the other studies Enos describes in the book. Personally, I think that Enos theory describes a real phenomenon - context matters, and probably in the way Enos describes. The lab experiments Enos runs, together with his correlational studies, add to the pile of circumstantial evidence.
But the fact that all the ecological causation studies involve a lot of contact makes it hard to identify and validate Enos theory. And there's a second problem that directly impacts the theory's potential usefulness: the problem of scale.
Proximity or Segregation?
Enos' theory is that all else equal, proximity increases racial tensions, and segregation increases them as well. But how do you tell the difference between the two? If a black family moves in nextdoor to me, is that decreasing segregation (which Enos thinks should soften racial tensions) or increasing proximity (which Enos thinks should heighten racial tensions)?
In a very nice diagram on p. 26, Enos explains the difference between desegregation and proximity. In one panel, the white and black dots are all clumped together, but the two clumps are very close. In another, the white and black dots are interspersed:
To put this another way, imagine a neighborhood where every block is either all black or all white, but the white and blacks alternate. Is that integrated or segregated? Suppose you think it's segregated. Now change it so that each block is integrated, but each building is either all black or all white. Is that integrated or segregated? Note that if we're free to keep increasing the resolution of our segregation measures, so that every "desegregation" still results in a "segregated" distribution, then each "desegregation" is just an increase in proximity (bad in Enos' theory).
The lack of any guide to what resolution we should use to measure segregation means that this resolution can be used as a free parameter, to make the overall theory ("proximity bad, desegregation good") fit almost any outcome. Enos is definitely tempted to do this at times. On p. 203 he writes:
[I]n fact, typical measures of segregation probably understate the actual segregation in Los Angeles because much of the separation between Latinos and Blacks happens at a much finer level, alternating from block to block within neighborhoods, and our measures of segregation are not equipped to capture this.And on p. 223:
As populations became intermixed in closely segregated blocks, proximity between groups increased.What is desegregation, if not intermixing populations?
And on p. 20:
For my purposes, though, there is no single "right" unit [of geographical area], but rather the psychologically salient local environment of each individual.But if the researcher is free to guess what environment is salient, how can the theory be tested?
Throughout the book, Enos is consistently better at measuring the impact of proximity than the impact of segregation. His most eye-opening and well-designed study is a 2015 paper looking at how white people in Chicago changed their voting patterns after nearby mostly-black housing (such as the Cabrini-Green Homes project) was torn down and poor black residents dispersed. Enos finds that white people who lived near the projects voted less, while white voters far away from the projects didn't change. It's a natural experiment, and is thus a powerful demonstration of how the proximity of an outgroup can raise racial threat. Enos measures proximity by physical distance, rather than any predetermined unit of area, which lends credence to his finding.
But while researchers can use distance to measure proximity in a study like this, they can't use it to measure segregation. Segregation, unlike proximity, has no natural units, so to measure it we have to specify a resolution at which to measure the dispersion or concentration of groups of people.
Ideally, that resolution should be included as a parameter in a quantitative model, along with proximity (represented by distance), relative size, and maybe some other variables. The segregation-resolution parameter could be estimated on one dataset (say, Chicago), and then tested on other data sets (say, New York City, Los Angeles, etc.). If the segregation resolution that worked in Chicago also worked to predict racial attitudes in NYC and L.A. and elsewhere, it could be treated as a structural parameter - a more-or-less universal constant of human psychology.
Of course, this is a lot easier said than done. It requires extremely high-resolution datasets on where people of various groups live. AND it requires natural experiments in multiple cities in order to validate the model out-of-sample. Much much easier said than done.
But in the meantime, we're left to wonder...and worry.
The Question of Policy
The overarching question of "The Space Between Us" is whether or not Hispanics and other Americans will experience racial conflict in the years and decades to come - and, even more importantly, how to prevent or reduce this conflict. Should we implement initiatives designed to get Latino and Anglo populations to mix more? Would that exert a psychological effect that would reduce the salience of the difference between the two groups, causing them to start to think of themselves as one single group? Or would it exacerbate the backlash that led to Trump's election?
Take Enos' statement on p. 223, recounting a case in Los Angeles where "as populations became intermixed in closely segregated blocks, proximity between groups increased." According to his theory, that's a recipe for conflict. If block-by-block segregation is even worse for race relations than neighborhood-by-neighborhood segregation (because of higher proximity), what does that say about the prospect for the success of federal housing desegregation initiatives? If these resulted in "populations became intermixed in closely segregated blocks", would that backfire and make race relations worse?
It's because of this question - which "The Space Between Us" doesn't answer - that the book ends up having an uncomfortably alt-right sort of undertone. Enos provides lots of evidence about why proximity between racial groups induces conflict - a staple of alt-right thinking - but little evidence that desegregation could be used to reverse the problem, or even what that would entail.
In fact, Enos' otherwise wonderful diagram on p. 26, showing the difference between proximity and segregation, has a very disturbing picture in the lowest panels. When illustrating a "low proximity, low segregation" situation - i.e., what Enos thinks would minimize racial conflict - it displays a dense clump of white dots at the center, surrounded by a far-flung scattering of black dots:
Back to Contact
Enos' book does offer a ray of hope regarding America's racial future: Tuscon, Arizona. In the final chapter, he describes how Tuscon has achieved much more harmonious relations between Anglo whites and Hispanics, through long-term positive interaction between the two groups. But he worries that in the rest of America, far-flung suburban development patterns and the increasing social isolation described by Robert Putnam will conspire to prevent this sort of long-term positive conflict, leaving Anglos and Hispanics permanently and bitterly divided.
In other words, Enos' good and bad visions for America's future depend not on context, but on contact. He doesn't propose large-scale desegregation initiatives (perhaps because of the measurement difficulties described above). Instead, his vision of racial tolerance relies on something outside the scope of his theory: long-term positive contact.
And in fact, this seems like exactly the right approach. Enos' theory may be right - and in fact, in spite of the measurement difficulties I still think it is right, and that there is some structural psychological scale at which segregation operates. But that doesn't mean it's helpful.
In Enos' theory, there are basically three ways to reduce racial conflict:
1. Reduce proximity between races. This sounds scary and bad.
2. Reduce the size of minority outgroups. This sounds even more scary and bad.
3. Reduce segregation. This is obviously the good option. But measurement difficulties mean that it's hard to know how to do desegregation right.
So instead of trying to use context-based theories to heal racial divides, it seems like we should use contact-based ones - in other words, we should do desegregation in a way that's designed to facilitate positive long-term contact among people of different races.
A Big Complicated World
Fortunately, there are probably additional ways to address the problem of race relations in America. Enos' book, like many books that are centered around a theory, tends to ignore or downplay all the other factors that affect attitudes toward outgroups. For example, in America, black-white relations are deeply affected by the history of slavery, Jim Crow, lynchings, race riots, and other terrible events; that will make Anglo-Latino relations in Phoeniz different from black-white relations in Chicago in ways Enos' theory doesn't describe. When measuring general attitudes towards outgroups, relative amounts of wealth and political power - which Enos touches on only lightly - should be taken into account as well.
This isn't a problem with "The Space Between Us", it's just a natural limitation of this sort of book. When reading it, you have to keep in mind that there's a lot of other stuff going on in the world.
But that also offers a reason for hope. There are probably many ways of improving race relations that don't involve the expensive, politically difficult, long-term process of changing living patterns and urban development. Geography is undoubtedly a big factor, but it's not an iron law that governs everything that happens to our society.
Anyway, that's it for my overly critical review. Just remember to put these caveats in context (no pun intended). "The Space Between Us" is definitely a book worth reading - the research it describes is both well executed and eye-opening, and the theory it puts forth probably describes a very real phenomenon.