An interaction (in statistics) occurs
when two variables have an effect in combination that is not
predictable on the basis of the effects of both of them alone. One
type is a catalytic interaction. It occurs when two
variables both have the same effect, but their combined influence is
much greater than the sum of their individual effects. For example,
both alcohol and barbiturates are depressants, but taken together their physiological effect is extremely severe and has
resulted in accidental suicides. The one acts as a catalyst for the
other.
John Roman of the Urban Institute gathered FBI homicide data from 2005 to 2010 (the last year
available), a total of 82,986 cases. The primary variables of
interest were the race of the perpetrator and the race of the victim,
so unsolved crimes were excluded. The outcome of interest was
whether the homicide was ruled justified. Cases involving law
enforcement—usually an automatic acquittal—were omitted. Roman also examined whether the
case occurred in one of the 23 states having SYG laws. Other control
variables available in the data base were the number of perpetrators and
victims, whether they were strangers, the weapon used, the year, the
region, and the age and gender of the parties. Here are the data:
If we look at all cases, it is clear
that both the race of the perpetrator and the race of the victim have
significant effects. A homicide is more likely to be declared
justified if the shooter is white and if the victim is black.
However, the most important effect is a catalytic interaction between
these two variables. The shooter is much more likely to be
exonerated when a white perpetrator kills a black victim than with the
other three combinations, which don't differ very much.
SYG laws also increase the likelihood
that homicides will be ruled justified. However, the evidence that they act as a catalyst of racial bias is mixed, since SYG laws
increase the number of exonerations in three of the four racial
combinations—all but the case when the shooter is black and the
victim white.
Would a critic be persuaded by these
data? Probably not. It's possible that other variables not recorded
in the FBI data base are influencing the outcome, variables such as
the location of the incident or the immediately preceding events. A
critic might claim, for example, that the white shooter-black victim
category includes more home (or business) invasions where standing one's ground is justified. In such cases, we would
expect the shooter and the victim to be strangers. As you can see,
homicides are more likely to be ruled justified when the perpetrator
and the victim are strangers, but lack of acquaintance seems to
increase perceived justification in all four racial combinations, not
just the white perpetrator-black victim case, as this explanation
would suggest. (I drew this conclusion by eyeballing the charts;
Roman does not present an analysis of these data.)
Laboratory experiments might help to
eliminate some of the ambiguity inherent in the FBI data by creating
scenarios which vary the races of the perpetrator and victim and hold
other characteristics constant. For example, Birt Duncan showed subjects an ambiguous incident in which one man may or may not have shoved
another and asked subjects whether an act of violence occurred. The
results were similar to Roman's data; the incident was most likely to
be judged violent with a black perpetrator and a white victim. If we
are only interested in homicide, we might present
participants with written descriptions of killings which vary the
races of the shooters and victims and ask them to play the role of
jurors. In fact, it wouldn't surprise me if social psychologists
around the country are doing that very thing right now.
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