Colorism and Crime

One of the many arguments for colorism runs: Darker African-Americans have been found to receive longer prison terms than lighter African Americans. Ergo.. Yes, that’s the argument — with the implicit premise being: And there are no plausible causes, besides anti-dark skin bias, for the correlation between color and length of sentence. Commenting on findings, one science blogger noted:

This proven correlation between skin tone and judicial outcomes doesn’t absolutely prove that skin tone directly causes shorter sentences and earlier release for recent black female prison convicts in North Carolina (“correlation is not the same as causation”). However, it’s hard for me to envision what these intervening factors may be, and there’s clearly a strong link between the two.

And yet new research sheds light on the mechanisms of one probable intervening factor:

Turning to the findings from the IQ Model, three points deserve attention. First, individual-level IQ differences were significantly related to violent misconduct. Inmates with above average IQ scores (relative to other inmates housed in the same facility) were at decreased risk of being involved in a violent incident. A one standard deviation increase in IQ score (as compared to other inmates within the same prison unit) was associated with a ten percent reduction in the odds of committing violent misconduct. The second finding of interest was that the introduction of the IQ variables led to a slight attenuation of the relationship between race/ ethnicity and misconduct. Finally, the average IQ of the prisoners within each of the 30 different prison units was found to have a significant effect on the likelihood of an inmate committing violent misconduct. Simply stated, individuals housed in a unit with a higher average IQ score were significantly less likely to engage in violent misconduct. (Diamond et al., 2012. Individual and group IQ predict inmate violence)

Since the darkest African Americans are only 0.5 SD less intelligent than the lightest, other pathways than color-> IQ-> inmate violence-> increased sentence length must account for some of the 12% of sentencing differences found (as there would only be a 5% difference in immate violence rate, as conditioned by IQ). As IQ has consistently been found to be associated with impulsivity, other pathways may lead from IQ differences to sentence length differences. Alternatively, since in large multicultural samples criminality has been found to be modestly heritable, the causal pathways may be more direct.

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13 Responses to Colorism and Crime

  1. nooffensebut says:

    “the causal pathways may be more direct”

    A new study shows that IQ interacts with MAOA alleles to affect antisocial tendencies.

  2. Kiwiguy says:

    Chuck, there is a discussion here in the comments that may be of interest:

    “it isn’t that — in the human case specifically — the edges are fuzzy. That would be so if there were, for example, some kind of narrow hybrid zones. But with the human species it’s all edges, all fuzziness. Isolation by distance and nothing much else. This wouldn’t count as having subspecies for any other species either. Many subspecies in songbirds, for example, were erected just to cover clinal variation and have been abandoned because the subspecies only work if you consider only end members and ignore the clines.

    There are some good ring species, the best being the West Coast Ensatina complex. And a good ring species will cause trouble for any species concept. Just goes to show you that “species” is a good enough abstraction of true biological variation much of the time, but not all of the time. Same with subspecies: works great for long-term geographically isolated populations, not so well otherwise.”

    http://sandwalk.blogspot.co.nz/2012/03/do-human-races-exist.html#more

  3. Kiwiguy says:

    fyi. Just another comment on that discussion – this one from Nick Matzke of Panda’s thumb discussing the 1998 Templeton paper.

    http://pandasthumb.org/archives/2012/02/continuous-geog.html#comment-279881

  4. Kiwiguy says:

    Nice comments on the above thread. More fun and games (although with much less knowledgeable characters) here.

    http://boards.straightdope.com/sdmb/showthread.php?t=644144&page=5

    • Chuck says:

      My major point was that the amount of genetic diversity is not small at least when put on the metric commonly used to judge effect size, Take a look at table 2 in the supplementary section of “Natural selection has driven population differentiation in modern humans.” http://www.nature.com/ng/journal/v40/n3/extref/ng.78-S1.pdf (page 9) You will notice that the between population PST is 0.11, as typically found. What might surprise some is that the FST standard deviation is also .11. So the average between population genetic distance is 1 SD. If we partition out intra-individual differences, the average becomes 2 SD. This is somewhat higher than I estimated by just transforming standardized differences into within/between variance, based on the assumption of equal population sizes, normality, and equal standard deviations.

      I think showing that the genetic difference is not small — at least given how effects sizes are typically interpreted — is fairly important.

    • Chuck says:

      Seems that I was blocked. If you get a chance, post the following reply for me.

      Jason Antrosio said:With regard to acoolcoolhippo, would like to throw a couple of recent studies into the mix. On the distinction between Sub-Saharan Africans and non-Sub-Saharan Africans, the 2009 study by Long et al.

      Jason,

      You bring up a great example of why it’s important to specify a subspecies concept — along with this concept’s criteria. How does Long et al.’s critique relate to the classification of human populations by the geographic race concept being discussed? (Refer to my discussion above.) Maybe Long et al.’s point is relevant when it comes to some other subspecies concepts, but it is not when it comes to this one.

      However, a more recent assessment, Strauss and Hubbe 2010, Craniometric Similarities Within and Between Human Populations in Comparison with Neutral Genetic Data suggests that the craniometric clusters may not be quite as evident as they have been portrayed: “Contrary to what was observed for the genetic data, our results show that cranial morphology asymptotically approaches a mean ω of 0.3 and therefore supports the initial statement–that is, that individuals from the same geographic region do not form clear and discrete clusters–further questioning the idea of the existence of discrete biological clusters in the human species.”

      If you noticed, above I said:

      But what about the 75% differing interpretation? This is where I get caught up. Craniometric and dental variation is such that while you can use it correctly classify individual, the differences aren’t so extreme that 75% of one population differ from 97% of another even using any combinations of the traits; it’s not even close. These then are not good differentiating criteria.

      The reason I said this is because I was aware of Strauss and Hubbe’s study. The findings seem to imply that in no set of craniometric differences are more than 75% of one population different from 97% of another. It would be interesting to run the same analysis using the dental data or skeletal data or a combination of all. Whatever the case, the situation illustrates the important difference between two main interpretations of the 75% rule. One can correctly classify more than 75% of individuals based on a set of differentia, without 75% of individuals lying outside 97% of the range of the others in the same differentia.

      Anyways, this is why I offered natural hair curliness as a differentia (for Subsaharan Africans and non-Africans.) Or was that too superficial for you?”

      • Chuck says:

        Another comment — for some reason I can’t post. Whatever the case, that would be my ‘subspecies case’:

        Several papers have recently criticized the nonhuman literature for exactly this. I’m traveling so I don’t have the papers handy, but amongst the points made are (1) the clustering algorithms can produce clusters even when the data was simulated with no clustering, only clinal patterns; (2) therefore people should test for clinal variation before naively throwing the data into clustering algorithms; (3) different clustering algorithms can produce different clusters with the same data; (4) small changes in the input data or the settings can produce different clusters in many situations

        Last comment.

        Nick and Jason,

        I would agree that human populations are at best only weakly subspeciated. As such, if you tighten up the taxonomic standards, likely, no set will qualify as taxonomic races. But, as it is, the standards for non human populations are fairly lax. Let me quote from Remsen (2010), “Subspecies as a meaningful taxonomic rank in avian classifications”:

        Mayr et al. (1953) provided objective, quantitative definitions of subspecies based on degree of overlap that can be applied across taxa. They outlined why using simple linear overlap in measurements, for example, overemphasizes extreme individuals in a population and overestimates true population overlap. They also discussed various interpretations of the “75% rule” as the threshold for naming subspecies. Although one interpretation is that only 75% of the individuals of each sample have to be correctly classified, the rule as defined by Amadon (1949), Mayr et al. (1953), and Patten and Unitt (2002) is based on standard deviations from the mean of normally distributed data. Depending on which metric is applied, in essence these definitions mean that 90–97% of the individuals of one population must be distinguishable from the equivalent percentage of the other population to be considered subspecies under the somewhat misleadingly named 75% rule.

        As I was noting above, there are multiple interpretations of the 75% rule. The more lax interpretation is (or was) just that 75% of individuals can be correctly classified into the respective populations. This is the interpretation that Sewall Wright (quoted above) was referring to in “Evolution and the Genetics of Populations” in his discussion of human races. Ditto Bodmer and Cavalli-sforza in “Genetics, Evolution and Man.” By this reading of the rule, clearly the 5-7 major human population clusters qualify as subspecies. I can’t imagine anyone seriously dissenting on this point. Perhaps, they would argue that by event of mass transportation many individual don’t “share a unique geographical range ” with others of their said race and maintain that this invalidates the concept as applied to humans. This is an interesting point — or would be were someone to make it, but this would, at best, only regress the question from “Are the said populations subspecies?” to “Were the said populations recently subspecies?”
        Continuing….

        […]Although the 75% rule has a long history in ornithology, its application has been erratic at best. For example, it is generally not mentioned as a criterion for recognizing subspecies in classifica- tions (e.g., American Ornithologists’ Union 1957, Dickinson 2003) or in any of the Handbook of the World series (del hoyo et al. 1992–2008). It is not possible to tell how many of the subspecies currently recognized in such sources would qualify as subspecies under the 75% rule, but it is certain that many subspecies, especially in North America, would not qualify as valid taxa under this rule, particularly those defined by mensural differences. From personal experience in attempting to use subspecies diagnoses, such as the keys in the Birds of North and Middle America series (ridg way and Friedmann 1901–1950), I predict that more than 75% of North American subspecies taxa delimited by mensural data would not survive application of the 75% rule

        Now, by this more rigorous interpretation of the rule, it’s not clear if the 5-7 major human population clusters qualify using any combination of traits — at least, I’m not aware of the qualifying differentia. They might be out there, though. I suggested hair curliness as a differentia between non-Sub Saharans and Sub Saharans. Based on the means and standard deviations presented in Hrdy’s “Quantitative Hair Form Variation in Seven Populations,” for “hair curvature,” these two populations seem to meet the 75% (differentia) criteria. The among to within F-ratio for this trait was 365. And the results agree with that of Loussouarn (2007), assuming curliness and curvature refer to basically the same trait. I’m sure if pressed, though, I could find other traits.

        Whatever the case, going by Remsen (2010), it doesn’t seem as if the 75% (differentia) rule is rigorously applied. Why should it be de rigueur, then, when it comes to humans? Can one really maintain that describing human populations as subspecies is an affront to the subspecies concept, give how the concept is actually employed?

  5. Kiwiguy says:

    The straight dope people have gone feral.

  6. Kiwiguy says:

    I posted that comment. btw. gnxp has a discussion about Clines that may be of interest.

  7. Kiwiguy says:

    Sports teams examples. Wonder how this will go down with the punters.

    http://boards.straightdope.com/sdmb/showpost.php?p=14868459&postcount=353

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