On the popularly reported black implicit association test (IAT) results

Recently the media and various friends and family have been asserting that implicit association tests (IAT) “prove” that whites are biased against blacks and that this presumably substantially explains the racial disparities in police shootings.

Since I am skeptical about the racial angle in police shooting, the validity of measures like IATs, and of received wisdom in general, I thought I would take a look at “Project Implicit” to better understand it.  The raw data for these results is available in SPSS format on OSF.io (albeit at >2GB) so I downloaded the data and performed some analysis in R.

A brief post on racial disparities in officer involved shootings

I have recently heard it said that the reason the police shoot blacks, especially young black men, at such a disproportionate rate is because they have an irrational fear of them because they are black.   Presumably the proponents of this view believe that shootings, “justifiable” or otherwise, should happen in roughly equal proportion to their share of population.  Although I do not believe the police are incapable of excessive force, racial discrimination, negligence, or what have you, the presumption that such disparities must be explained by presumed irrational fear of blacks strikes me as terribly naive on several levels.

Robert VerBruggen of RealClearPolicy did an interesting post on “Race, Age, and Police Killings” a few weeks back that compared nation-wide homicide rates by age group and race to the police shooting statistics.

I thought this was a good and fair way to better illuminate the “fairness” issues here, since groups (e.g., sex, age, race, ethnicity, education, etc) that commit more murder (and other violent crimes) nationally can be reasonably assumed to be more likely to have confrontations with police and more violent confrontations when they do.

I found some data to take this point further by looking more granularly at the demographics of offenders that have actually killed law enforcement and offenders that have assaulted and seriously injured the police (as in with guns, knives, etc).  This data gives us a much better sense for the risks posed by each groups to the police and which groups are relatively more likely to be be confrontational, disobey, or even resort to violence, i.e., it speaks much more directly to the dynamics of police encounters with particular demographics (to the extent that one can argue that, say, national homicide rates are only black-on-black, gang-on-gang, or some such).  Most police encounters do not result in death of either party or even an exchange of gun fire, but groups that kill, injure, or assault the police at (much) higher rates can be reasonably presumed to be at (much) higher risk of getting killed by the police, “justifiable” or otherwise.

Some visualizations of ancestry.com’s genetic data

As a quick follow up to my earlier post using ancestry.com’s “Genetic Census of America”, I thought I’d post some more heat maps using the data I aggregated by major continental group (“race”) and by the more granular “adjusted” European ethnicities (i.e., whereby I simply divide the ethnicity by the total european “ethnicities” in the state).

Note: You can click these images for an interactive view to see the actual numbers for each state if you care.

Adjusted European Ethnicities

 

The probable genetic explanation for interstate differences in mortality amongst non-hispanic whites

A couple months ago I stumbled across ancestry.com’s  “Genetic Census of America”.  Since I was researching the health outcomes question already I remembered that this data existed and I decided to bite the bullet and actually analyze this data systematically.  Lo and behold, I quickly discovered some very strong correlations between these genetic proportions (crudely without any particular techniques) and the life expectancy of non-hispanic whites in each state.  I refined this a bit and produced a toy model that can explain about 85% of the variance in life expectancy between states (not to mention other things)!

Before I get started, let me get some caveats out of the way:

• correlation does not necessarily imply causation
• these particular genetic groups may just be proxies in this country for particular ethnic or other genetic groups (at least in part)
• this could “cultural” (people with particular frequencies of SNPs are also more likely to have had particular cultural mores, values, and the like passed onto them through their ancestors/parents).
• most “whites” have some fraction of other continental groups, but it’s usually pretty small on average
• the DNA testers may not necessarily be representative of the larger “white” population, but I think it’s good enough to represent the white population (probably less so other groups).
• binning these together by states and other high levels of aggregation likely improves the “accuracy” of these methods since random accidents, stochastic variances in gene expression, or what have you get averaged out to large degree.  Likewise, to the extent these groups are just a crude proxy for actual groups, this level of aggregation likely further helps.
• Ancestry.com does not provide details by race/ethnic group and my procedures cannot perfectly remove any potential signature introduced by others.   Blacks and latinos, in particular, surely introduce some european genetic groups into this data, although they are obviously much under-represented in ancestry’s DNA analysis and I do not think it would skew the results that much.

This is a simple model that I produced to calculate non-hispanic white (NHW) life expectancy by state using a simple genetic calculation and smoking rates (weighted equally on standard deviations from the national non-hispanic mean amongst states) .

As for how I got here….