Why Statistical Bigotry Is Just Bigotry, Round 2
San Francisco Chronicle columnist Chip Johnson’s March 28 column rationalized the fact that 62% of the Oakland Police Department’s traffic stops involve African Americans (just 28% of the city’s population) because blacks commit the overwhelming majority of the city’s serious crime. This latest example of penalizing “driving while black” is a classic case of what I call statistical bigotry.
“African Americans comprised 83 percent of the 12,161 suspects in last year's homicides, attempted homicides, robberies, assaults with firearms and assaults with weapons other than firearms, according to crime suspect data provided to me by the Oakland Police Department,” Johnson, an African American, wrote, calling for “a straight-forward discussion about race” that doesn’t end in blaming the cops for their response to disproportionate African American crime.
Sounds logical, doesn’t it? If traffic stops are in part a crime prevention tool, why not concentrate limited police resources on stopping the people who, statistically, are most likely to be criminals?
But there are two big problems with this logic, as I previously suggested. The first is that saying that African Americans commit a large majority of Oakland’s crimes does not mean, or even imply, that most African Americans are criminals. In fact, the 10,000 black suspects in 2012 (which does not translate into 10,000 individuals, since most serious offenders commit multiple offenses) amount to just a small fraction of the city’s 80,000 African Americans ages 12 and older.
If we apply statistics as Johnson suggests, police should act as if the vast majority of black drivers and pedestrians are not criminals.
But there’s a second, bigger reason why statistical bigotry is just bigotry: it is selectively applied only to disfavored, powerless groups.
Just about every population group harbors some damning statistics. For example, everyone would agree that drug abuse and marketing is a major, if not the most virulent, force driving violent, property, and drug crimes in Oakland and elsewhere.
In the Oakland area, Center for Health Statistics reports show that non-Hispanic whites account for 56%, and ages 35 and older account for 80%, of deaths from abusing illicit drugs. Whites also account for a highly disproportionate share of hospital cases involving illicit-drug overdose.
So, would Oakland police be justified in randomly stopping older white motorists due to their greater race- and age-based propensity to drug abuse? Administer drug tests bases on race? Randomly detain middle-aged white men in suits due to their racially excessive numbers of white-collar crimes or soliciting prostitution?
That would never happen. Even President Obama’s pronouncements singling out young black men for crime (while remaining silent on older white and black men’s disproportionate drug abuse and crime) make it clear that privileged groups enjoy immunity from negative statistical generalization.
Chip Johnson’s history of rationalizing age-biased curfews, racially disproportionate traffic stops, and other police tactics aimed at deterring “young toughs” is echoed by many others, including Fox News’ conservative Bill O’Reilly, who by advantage of race or age are very unlikely to be subjected to these repressive policings themselves.
But if we truly apply statistics as the statistical bigots urge, Johnson’s and O’Reilly’s demographics would be ones targeted by police for disproportionate curfew, stop and frisk, and traffic stops founded in racial and older-age statistical excesses. I doubt their enthusiasm for police crackdowns would persist if their own population groups were subjected to arbitrary suspicion.
Police already are empowered to stop individuals based on reasonable suspicion of criminal involvement. That suspicion should be based on empirical evidence, not demographic characteristics—that is, what someone does, not who they are. But it’s hard to get pundits and cops to apply rules of fairness when even the president does not get the basic fact that the veneer of statistics can be misused to advance narrow bigotries when they should be tools of broader, rational analysis.
Posted in Blog, Political Landscape, Social Justice
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