What John Lott Gets Right

What John Lott Gets Right
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ERIC THAYER / Reuters

If there is one name which creates anger and hostility within the gun violence prevention (GVP) community, it’s not Wayne LaPierre, head of the National Rifle Association, it’s John Lott. His book, More Guns, Less Crime, has become the Magna Carta for the pro-gun movement and his argument that armed citizens deter violent crime is immediately cited in any public debate involving the regulation of guns.

So before I go any further, I’m going to let you in on a little secret. It’s not that I necessarily agree with anything John Lott says. But what the GVP community does not acknowledge is that the data Lott uses to make his argument is not only essential for understanding gun violence; it also should serve as the primary source for crafting effective laws and regulations to keep guns out of the “wrong” hands.

One quick example. The GVP research community insists that it’s not more legally-owned guns which reduces gun violence; it’s more legal constraints on gun ownership. Again and again, well-meaning GVP researchers look at gun-violence rates, compare these rates with gun regulation, and find a positive connection between both. My state, Massachusetts, is rated as one of the most regulated states; it also ranks near the bottom of all 50 states when it comes to injuries from guns.

The largest city nearest me, Springfield, has an annual gun violence rate at least three times the national average; the adjacent town, Longmeadow, hasn’t been the location of any kind of gun violence for God knows how many years. What does state-level data on gun violence tell you about the differences between Springfield and Longmeadow? Nothing. And since the data doesn’t illustrate the difference in violence between those two jurisdictions, how could any law be effective which applies equally to both?

Lott’s argument about legal, armed resistance to crime may be based on all kinds of statistical models which can be shown to be inadequate or worse, but at least he has done what no GVP scholar has yet attempted to do, namely, to use locally-based data which can sometimes illustrate the difference between gun violence in communities within the same state.

Last year Lott published data which gives murder numbers for every county in the United States. What did the data show? That even at the county level, the extreme locality of gun violence begins to disappear the moment you examine the problem beyond the particular neighborhood or street corner where the violence occurred.

The lack of geographic specificity found in GVP research is equally evident in explanations about racial differences found in the population injured by guns. Brookings says that “gun violence varies dramatically by gender and race,” the data showing that death rates for black men are twice as high as the death rates for whites. Where did Brookings get their data? From an article published by a group of public health gun researchers which says exactly the same thing.

There’s only one little problem. How can anyone take seriously a comparison of similar behavior between two racial groups who experience such dramatic differences in socio-economic status as whites versus blacks? When you compare gun-violence rates in communities with different racial demographics but the same or similar socio-economic trends, gun-violence rates based on racial categories begin to disappear. In Baton Rouge, Louisiana, where a majority of the residents are black, last year the per-100,000 homicide rate hit an all-time high at 21.5. In Acadia Parish, which is mostly white, the homicide rate every year runs around 25.

Finally and most important, whenever Lott is criticized by a GVP researcher, he responds at length on his website and either reproduces or references the criticism from the other side. I have yet to see a single critique about Lott’s work which extends him the courtesy of a response. If the GVP community really wants to find some kind of “middle ground,” it will only happen if both sides contribute their thoughts in the same space.

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