A non-emotional clearinghouse of facts

In my last post, I focused on a "fact" from Dana's book.  What I failed to realize at the time is who that "fact" was from, and just how heavily Dana was leaning on him for these "facts".

His name is John Lott, and Dana introduces him in chapter 3 like this:

John Lott's fabulous Crime Prevention Research Center has expertly debunked a number of [Mom's Demand's] claims by analyzing statistics and crime reports.

She calls them a, "hated clearinghouse ... of nonemotional analysis."  Then Dana goes off on a Shannon Watts tweet about how 84% of all female firearm homicides are in the US.  The CPRC has her covered, stating that women in the US are only 22% of all homicides, while the mean for those 25 countries, many of whom are small, is 24%, thus making them much worse.  Sorry, Mr. Lott, you forgot to mention that firearm homicide rates in those countries are also much lower. Most are below 1 in a hundred thousand, while here in the US, it is almost 5.  One would be left to believe that would also be a big contributor to that 84% figure from Shannon Watts.

Of course, if you select the right stat, everything looks good.  The CPRC has been known to not only select the "right stat", but to sometimes cook the books to make that right stat.

Ian Ayres and John Donohue wrote a paper that found that, if anything, concealed carry laws lead to more crime. Lott, (along with Florenz Plassmann and John Whitley) wrote a reply where they argued that using data up to 2000 confirmed the “more guns, less crime” hypothesis. In Ayres and Donohue’s response to that paper, they found that Lott’s data contained numerous coding errors that, when corrected, reversed the results. Furthermore, this was the second time these sorts of errors had been found in Lott’s data. Lott had presented to the NAS panel figures showing sharp declines in crime following carry laws. Declines which disappeared when the coding errors were corrected. Finally, when Lott saw Ayres and Donohue’s response he had his name removed from the final paper.

Dana does not let junk science that has been proven wrong in the past get in the way of getting the "right stat"/"fact".  In this case, it may have been good to find a better, non-tainted source.