… on averages, policing, and recidivism.
Averages. In all too many cases we see people basing their assessments on averages, even when the groups being averaged over are very heterogeneous. To me, that’s equivalent to ordering a dinner of onion soup, filet mignon, Caesar salad, a fine Bordeaux wine, and peach Melba – but instead of eating the courses separately, putting it all in a blender and eating it that way – after all, it goes into the same stomach, doesn’t it?
[Francis Galton criticized those who focused on averages as being “as dull to the charm of variety as that of the native of one of our flat English counties, whose retrospect of Switzerland was that, if its mountains could be thrown into its lakes, two nuisances would be got rid of at once.”]
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Policing. After my first few police ride-alongs in the mid-sixties I reached the conclusion, jokingly, that the police were report writers with the power of arrest. An exaggeration, of course, but it appeared to me that most of their activity seemed to be documenting the nature of their interaction with citizens.
Rather than look upon that as a joke, we can turn that around to some extent and realize that they are the only 24-hour-a-day representatives of the city on the street. And as such, they should note the deficiencies, not just in the people they meet, but in the city services that should be (but are often not) provided to the areas of most concern.
- Kids congregating on street corners? Document the lack of athletic facilities and parks
- Trash on, and potholes in, the streets? Notify the appropriate city agencies.
- Truancy? How much is invested in the neighborhood schools?
I don’t mean to imply that police officers should all be renaissance men/women, but that they should be aware that the problems they encounter are not for them to solve using their police power. In other words, the police should be tasked with not only dealing with problem persons but dealing with problems that are exacerbated by municipal deficiencies. This would make the “thin blue line” a little bit stronger and more substantial.
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Recidivism. Over thirty years I published a book on recidivism (called, appropriately enough, Recidivism). It focused, for the most part, on the way recidivism was measured at the time. In that era the effectiveness of a correctional program was evaluated based on the “one-year recidivism rate,” i.e., the fraction of those enrolled in the program who “failed” (choose a meaning: who were rearrested, or retried, or reconvicted, or whose probation or parole conditions were violated). That is, the status of the cohort at a single point in time was the criterion. So two programs with the same one-year recidivism rate were judged to be equally effective, which is a lousy measure. [1]
In our first paper on the topic, my colleague Dick McCleary (currently at UC Irvine) and I pointed out that a better measure would take into account the entire trajectory, not just one point in time. It was based on statistics originally developed in the biomedical field, for evaluating different treatment regimes for cancer patients.[2] In that field, rather than use the term “failure” for those who did not improve, the term “survival,” its complement, was used to denote those who did not fail. In other words, the flip side of the coin is considered as the important variable.
Now with a few more years under my belt, and a little more perspective, I realize that we should not only follow the lead of biostatisticians in the methodology to use, but also in the perspective we bring to evaluating correctional programs. Specifically, we should look at survival rather than failure as the more important consideration.
Words have impact, and these words promote different views of the context in which a failure may occur. When we say a person recidivates, we frame the situation using an active verb, as a deliberate action on the part of the offender. That is, we ascribe to the offender a willfulness to do bad. On the other hand, when we talk about correctional failure from the standpoint of survival analysis, we frame the situation as an action on the part of the offender due to his/her inability to withstand the pressures preventing rehabilitation.
Other correctional programs do not ascribe such willfulness to failure. As Alan Marlatt noted in his book Relapse Prevention, we realize that it may take a few tries before a person quits smoking, or drinking, or drugs. In these situations we say a person has thus far survived, and that s/he has not yet relapsed.
Obviously, there are people out
there who are truly beyond correction and who, regardless of the circumstances,
will continue to reoffend. But this is far from the norm, and tars every other
person released from incarceration with the same brush.
[1] Suppose, for example, that both had one-year recidivism rates of 60 percent. In one program, 5 percent of the cohort failed every month; in the other program, all 60 percent failed in the first month, with no subsequent failures in the next 11 months. Obviously, they should not be considered to be equally effective. While this is an extreme example, it points out that the entire trajectory of failure should be considered when evaluating programs. That is what the book focused on, and it helped to change the way recidivism was measured.
[2] We thought that we had developed this completely new way of assessing correctional failure, but found out later that others had gotten there first. Sic transit gloria mundi.
The problem with averages is even worse than described in some cases. Take the case of “stagnating wages”. The averages used not only fail to describe the variation among individuals at any one point in time; the change in the average does not describe the changing fortunes of even the same population over time, and less still the changing fortunes of any individuals in the population.
Averages are also often misleading/useless/etc because outliers of some kind are what we really care about. It’s the ones who die or kill or lose their homes or are tortured who drive policy responses (and mostly rightly). Or the ones who succeed spectacularly, as in sports records. (And because of the typical shape of distribution curves, choices that have barely-registered effects on the average/mean/median can have much larger effects on the outliers.)
On police, how many walk beats any more? Even in our small town I see officers almost exclusively in cars. Postal employees are much more present. (Also, I wonder what the effect would be of a ban on public safety officers wearing dark sunglasses. Few things so viscerally remove someone from their immediate social surroundings.)
Of course, postal workers are federal, not municipal, employees. And I think that trained properly, police officers could be useful in the way I suggest. Not only that, but it would tie them into the community to a greater extent by taking (partial) ownership of the problematic conditions they notice.