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  • 1.  Racial Disparities in Criminal Justice Outcomes

    Posted 08-05-2016 14:34

    Below is an item posted today (about 1650 words) explaining that the President’s beliefs about the effects of modification of criminal justice practices on relative racial/ethnic differences in adverse criminal justice outcomes and the proportions racial minorities comprise of persons experiencing those outcomes are the opposite of reality. 

    “Things the President Doesn’t Know About Racial Disparities,” Federalist Society Blog (Aug. 5, 2016)

    http://www.fed-soc.org/blog/detail/things-the-president-doesnt-know-about-racial-disparities

    This is the subject addressed in my July 25, 2016 letter to American Statistical Association leadership that I posted here last week.

    http://www.jpscanlan.com/images/Letter_to_American_Statistical_Association_July_25,_2016_.pdf

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    James Scanlan
    James P. Scanlan Attorney At Law
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  • 2.  RE: Racial Disparities in Criminal Justice Outcomes

    Posted 08-10-2016 09:21

    A 100 word version of the long article, with statistics related questions or comments may result in receiving some constructive feedback to specific questions

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    Raid Amin
    Professor
    University of West Florida



  • 3.  RE: Racial Disparities in Criminal Justice Outcomes

    Posted 08-10-2016 16:40
    > James,
    >
    > Correct me if I am wrong, but it seems that your main point is that at the same time as the advantaged-disadvantaged (AD) group discrepancy in rates of positive outcomes improves, the AD discrepancy in rates of negative outcomes worsens. But perhaps what is most important is not the AD rates of negative outcomes but the absolute number of negative outcomes for disadvantaged group members, which goes down when the rate of positive outcomes goes up. If so, your strongly worded concern seems completely misplaced, even though it is mathematically correct.
    >
    > Joel
    >
    >
    >
    > --
    > Joel P. Wiesen, Ph.D., Director
    > Applied Personnel Research
    > 62 Candlewood Road
    > Scarsdale, NY 10583-6040
    > http://www.linkedin.com/in/joelwiesen
    > (617) 244-8859
    > http://appliedpersonnelresearch.com




  • 4.  RE: Racial Disparities in Criminal Justice Outcomes

    Posted 08-11-2016 14:46

    Joel, 

    It is true that reducing the frequency of adverse outcomes reduces the absolute number of adverse outcomes for the disadvantaged group (and, in the rate ranges at issue for most criminal justice outcomes, tends to reduce the absolute difference between the adverse, and favorable, outcome rates of the advantaged and disadvantaged groups). But reducing the frequency of adverse outcome will tend to increase each of the measures/indicators cited by the President as a basis for African American mistrust of law enforcement (subject, of course, to the qualifications noted in the article and treated at somewhat greater length at pages 8-9 of the July 25, 2016 letter to American Statistical Association (ASA) leadership).

    With regard to lending, school discipline, and criminal justice outcomes (and various other things), the government has commonly proceeded on the belief that generally reducing adverse outcomes will tend to reduce (a) relative differences in rates of experiencing the outcomes and (b) the proportions disadvantaged groups make up of persons experiencing the outcomes. The opposite is the case.

    But, unaware that reducing the frequency of an outcome tends to increase (a) and (b), the government continues to monitor the fairness of practices on the basis of the size of (a) and (b). Thus, we have many situations where an entity’s complying with government encouragements or pressures to reduce the frequency of adverse outcomes tends to increase the chances that the government will sue the entity for discrimination. We also have situations where agreements are reached – as in the case of the consent decree entered against Ferguson, Missouri in April 2016 and the settlement agreement reached between the Department of Education and Oklahoma City schools the same month – that require entities to modify practices in ways that (unbeknownst to the government or the entities) will tend to increase (a) and (b), while also requiring that the entities reduce (a) and (b). See pages 6-7 of the July 25 ASA letter. See also the treatment of the massive monetary settlements in fair lending cases in reference 1.

    We also have many situation where provocative statistics about rare outcomes receive great attention (as in the recent attention to racial disparities in preschool suspensions) creating the anomaly whereby the less consequential a matter is, the more consequential it is perceived to be.[2] That is a pretty longstanding pattern.[3]

     Be mindful that I am not maintaining that by reducing the frequency of adverse outcomes the government is increasing the comparative disadvantage of racial minorities. Rather, I am faulting the government for failing to understand that reducing the frequency of an outcome tends to increase, not decrease, (a) and (b) and for the perverse consequence of this failure of understanding.

    Any unfairness in my treatment of the government rests in my failing to point out often enough that the government’s failure of understanding is a consequence of a like failure of understanding on the part of the scientific community. I have been urging the scientific community, by means of the July 25 ASA letter and my October 5, 2015 ASA letter,[4] as well as similar letters to entities like the Population Association of America (PAA) and the Association of Population Centers (APC),[5] to correct the government’s misunderstanding. Notably, PAA and APC declined to explain the matter to the government, potentially postponing for decades the understanding of a crucial issue by their own members as well as by the government. So it may be that the scientific community, which even more so than the government ought to know better, deserves severer criticism than the government.

    But unless one tells the government in very explicit terms how poorly it understands a matter, the government will never figure that out. The government may never figure it out anyway unless an entity like ASA takes action of the type I recommended in the letters of October 5, 2015, and July 25, 2016.

     Jim

     1. “Misunderstanding of Statistics Leads to Misguided Law Enforcement Policies,” Amstat News (Dec. 2012)Misunderstanding of Statistics Leads to Misguided Law Enforcement Policies

    Letter to Department of Health and Human Services and Department of Education (Aug. 24, 2015)http://jpscanlan.com/images/Letter_to_HHS_and_DOE_re_Preschool_Discipline_Aug._24,_2015_.pdf

     3. “The Perils of Provocative Statistics,” Public Interest (Winter 1991)http://jpscanlan.com/images/The_Perils_of_Provocative_Stat.pdf

    4. Letter to American Statistical Association (Oct. 8, 2015)http://jpscanlan.com/images/Letter_to_American_Statistical_Association_Oct._8,_2015_.pdf

    5. Letter to Population Association of America and Association of Population Centers (Mar. 29, 2016)http://jpscanlan.com/images/Letter_to_PAA_and_APC_Mar._29,_2016_.pdf

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    James Scanlan
    James P. Scanlan Attorney At Law



  • 5.  RE: Racial Disparities in Criminal Justice Outcomes

    Posted 08-11-2016 15:55

    Believing in proportionality comes naturally and easily.  If ten percent of humans were green, then ten percent of all welders, ten percent of all doctors, ten percent of the homeless, ten percent of all college athletes, and ten percent of all statisticians should be green, or something must be wrong.  Many years ago, a math colleague and good friend, Ewa Wojcicka, came to my office to share something that puzzled her.  As background, Ewa, as a child, had been groomed in her native Poland to play volleyball.  That never came to be.  As an adult, she became a U.S. citizen and got a Ph.D. in mathematics.  As a superb athlete, she played competitive tennis as much as her math career allowed.  In tennis, she could beat most men easily.  The hot topic in pro tennis at the time was the disparity between how much money women earned and how much men earned.  What puzzled Ewa was that Vitas Gerulaitis, a player on the men’s circuit had just said that the reason for the disparity was that the quality of play was different – that even the 200th ranked man could easily beat Martina Navratilova, the top ranked woman at the time.  She told me that he was right, and that it troubled her.  “How could the top 200 players all be men?” she asked.

    I looked at the question statistically.  Suppose that on a continuous numerical scale, each person’s tennis ability could be assigned a number.  In order to work with a concrete distribution, I asked her to suppose that a normal distribution described the tennis ability of all men and that a normal distribution also described the tennis ability of all women.  Further suppose that the men’s mean exceeds the women’s mean because, as a group, men hit harder, faster shots.  There are plenty of examples of women who can beat men, so if you like, suppose the difference in means is very slight.  Further suppose that the standard deviation for men is the same as that for women.  Something interesting happens.  For a tennis ability value t, let M(t) be the area under the men’s normal curve to the right of t, and W(t) be the area under the women’s normal curve to the right of t.  I showed Ewa that M(t)/W(t) increases without bound as t tends to infinity.  In other words, so long as one group has the slightest edge, that group increasingly monopolizes the right tail at the highest levels of play.  Something that would keep this from happening is if the standard deviation for women exceeds that of men, which is counter-intuitive.  The exercise was enough to convince Ewa. 

    Symmetric results apply to the left tail for the group that has even the slightest of a disadvantage.  The motivation was a question about the tennis ability of men and women, but the conclusion would be the same for any metric applied to two or more groups.  Further, even though the exercise was limited to normal distributions, there is an indication that what naturally accrues in the tail is not proportionality.

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    Mick Norton