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Author Topic: Wake Diversity Experiment  (Read 2211 times)
glarson
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Posts: 476


« on: November 22, 2016, 02:11:40 PM »


Within the long Wake tradition of attempting to rigorously test potential innovations in our debate tournament management procedures, we adopted a different system this year to improve diversity within judge assignments given the general failure of opt-in to achieve its goals.

After the completion of pref sheets but prior to the first round (124 teams / 152 judges / 18,848 data points), I calculated the overall population mean for the tournament (48.59) and sample means for 4 subpopulations within the tournament judging pool.

                Overall (152) – 48.59

                Non-black cis males (100) – 47.60 (0.90 better than the overall mean)
                Black cis males (11) – 48.66 (0.27 worse than the overall mean)
                Non-black non-cis males (31) – 49.90 (1.31 worse than the overall mean)
                Black non-cis males (10) – 53.32 (4.73 worse than the overall mean)

My first observation is that these sample means are actually very close, resulting in only a very modest impact on paneling.  As I noted in the FAQ, the difference in judge means represents one of the four terms in presets and one of six in elims.  But the difference overall in the judging folks received was even more minimal.  The chart indicates aggregate results at Wake for each of the last five years with this year’s results actually being slightly better for “in-it” teams than last year.  A bigger change actually happened in previous years as the community has generally attempted to run tournaments with tighter pools with fewer individuals being preffed out and greater diversity in the rounds that people hear.  But even those impacts have been quite slight with results better than the average tournaments that most everyone attends.  I’ll be glad to answer questions.

                                   2016           2015           2014           2013           2012
All In-it (including presets)   16.39   16.54   14.63   14.85   13.62
Out-of-it                           27.67   25.77   23.13   19.42   21.55
All Debates                   17.93   17.85   15.87   15.47   14.75
Round 8 in-it                     12.5   12.5           11.4           13           9.46
               
Going forward, I think there are several questions worthy of discussion.  While I strongly prefer using algorithms as opposed to manual swaps, some may believe differently.  I believe it is a genuine question as to how many categories there should be and how they get defined.  Regarding ethnicity it is possible to divide white/non-white if the question is simply diversity OR it is possible to divide black/non-black if the primary question is “anti-blackness.”  I think it’s an open question as to which direction that should go.  Perhaps similar questions arise regarding definitions of gender identity or gender expression.  In having those discussions, I should note, however, that any discussion of the comparison of means requires larger sub-populations with the 10 and 11 member sub-groups at Wake probably on the low end of reliability.  So while it would be interesting to multiply categories, it probably isn’t feasible from a statistical perspective.
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CouldaBeenaContenda
Jr. Member
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Posts: 73


« Reply #1 on: November 29, 2016, 03:49:27 PM »

(housekeeping)
Code:
                        2016         2015         2014         2013         2012
All In-it (including presets) 16.39         16.54         14.63         14.85         13.62
Out-of-it                 27.67         25.77         23.13         19.42         21.55
All Debates                 17.93         17.85         15.87         15.47         14.75
Round 8 in-it                 12.5         12.5         11.4         13          9.46

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