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I think that the canonical reference when talking about a data driven approach to the homeless problem should be "Million Dollar Murray" by Malcolm Gladwell. Gladwell cites Dennis Culhane's research on homelessness that produced a surprising outcome: the most frequent period of homelessness is a single day. The second most frequent duration? Two days.

Why? Because when you're talking about homelessness you're talking about (at least) two different populations. The first are those individuals who are homeless only briefly--they are often employed and after a night or two of sleeping in a car or on a bench they find shelter on a friend's couch or in the basement of their parents home. In Gladwell's narrative they can be ignored because they can take care of themselves.

The other population is far more problematic. For this group of individuals the average stay on the streets isn't measured in days, it's years. Rates of drug abuse and mental illness are far higher for this group than for the general population, along with the concomitant issues of joblessness and familial isolation. (Culhane in another interview said that they tend to have "tenuous" relations with friends and family. Translation: they can't stay at Mom's house because they pawned the tv to buy crack and are now persona non grata.)

This is not a distinction without a difference. If homelessness has its roots in simple economics than providing housing vouchers or subsidies should be enough to make a difference. If the real issue is addiction and mental illness than those measures will be woefully inadequate.

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