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Precinct analysis: State courts

We return to our tour of the precinct data with a look at the statewide judicial races. These tend to be interesting mostly as proxies for base partisan support, but there are variations that reflect qualities about the candidates. That’s what I’m going to focus on here.


Dist    Green    Garza   Guzman Robinson  R SJ Avg  D SJ Avg
============================================================
CD02  156,800  107,513  163,092  100,247   158,852   103,416
CD07  135,310  108,540  144,087   99,977   138,618   104,011
CD09   25,906  103,431   27,993  101,594    26,242   102,489
CD10   79,113   34,926   80,104   33,297    79,337    33,927
CD18   45,665  149,521   50,198  144,817    46,814   146,929
CD29   34,618   91,898   40,381   85,592    35,849    88,188
						
SBOE6 329,707  253,583  346,471  235,776   335,602   243,912
						
HD126  34,635   24,431   35,565   23,230    34,861    23,735
HD127  47,208   23,767   48,074   22,592    47,409    23,032
HD128  40,567   16,310   40,856   15,756    40,513    15,989
HD129  40,578   25,159   42,100   23,578    41,139    24,193
HD130  57,460   20,405   58,131   19,372    57,638    19,776
HD131   6,812   38,016    7,565   37,395     6,923    37,668
HD132  36,509   29,355   37,394   28,250    36,716    28,697
HD133  46,810   25,780   49,559   23,138    47,911    24,387
HD134  44,064   41,029   49,468   35,686    46,233    38,348
HD135  31,226   26,170   32,263   25,003    31,496    25,523
HD137   8,568   17,074    9,165   16,546     8,743    16,774
HD138  26,600   22,314   27,842   20,926    26,972    21,525
HD139  11,909   38,459   12,907   37,412    12,132    37,903
HD140   6,219   20,336    7,324   19,129     6,430    19,617
HD141   4,993   32,192    5,391   31,834     4,982    32,006
HD142  10,070   33,520   10,763   32,789    10,208    33,091
HD143   8,718   22,970    9,933   21,652     8,927    22,196
HD144  10,592   15,528   11,318   14,623    10,689    14,987
HD145  10,584   22,300   12,511   20,273    11,063    21,133
HD146   9,618   36,999   10,637   36,067     9,928    36,519
HD147  11,536   43,516   13,478   41,685    12,147    42,533
HD148  17,146   27,893   19,709   25,140    18,013    26,352
HD149  15,245   26,292   15,875   25,657    15,370    25,934
HD150  47,406   25,632   48,229   24,488    47,624    24,911
						
CC1    70,859  232,823   78,886  225,102    73,125   228,635
CC2   122,115  119,904  129,022  112,013   123,728   115,261
CC3   187,552  151,403  196,274  142,372   190,521   146,507
CC4   204,547  151,305  211,872  142,722   206,690   146,412


Dist    Green    Garza   Guzman Robinson    R Avg%    D Avg%
===========================================================
CD02   56.81%   38.95%   59.09%   36.32%    57.28%   37.29%
CD07   53.24%   42.71%   56.70%   39.34%    54.00%   40.52%
CD09   19.42%   77.53%   20.98%   76.15%    19.34%   75.55%
CD10   66.72%   29.46%   67.56%   28.08%    66.96%   28.64%
CD18   22.47%   73.57%   24.70%   71.25%    22.82%   71.64%
CD29   26.39%   70.04%   30.78%   65.24%    26.88%   66.12%
						
SBOE6  54.15%   41.64%   56.90%   38.72%    54.62%   39.70%
						
HD126  56.39%   39.78%   57.90%   37.82%    56.72%   38.62%
HD127  64.08%   32.26%   65.25%   30.67%    64.37%   31.27%
HD128  68.85%   27.68%   69.34%   26.74%    67.98%   26.83%
HD129  58.89%   36.52%   61.10%   34.22%    59.05%   34.73%
HD130  71.00%   25.21%   71.83%   23.94%    71.16%   24.42%
HD131  14.80%   82.57%   16.43%   81.22%    14.88%   80.97%
HD132  53.12%   42.71%   54.41%   41.10%    53.35%   41.70%
HD133  62.02%   34.15%   65.66%   30.65%    63.04%   32.09%
HD134  49.46%   46.05%   55.52%   40.05%    51.07%   42.36%
HD135  52.28%   43.81%   54.01%   41.86%    52.30%   42.39%
HD137  31.93%   63.63%   34.16%   61.66%    31.92%   61.24%
HD138  52.08%   43.69%   54.51%   40.97%    52.34%   41.77%
HD139  22.82%   73.69%   24.73%   71.69%    23.05%   72.01%
HD140  22.65%   74.05%   26.67%   69.66%    23.03%   70.25%
HD141  13.06%   84.21%   14.10%   83.27%    12.95%   83.21%
HD142  22.41%   74.60%   23.95%   72.97%    22.57%   73.18%
HD143  26.59%   70.05%   30.29%   66.03%    26.61%   66.17%
HD144  39.06%   57.26%   41.73%   53.92%    38.95%   54.61%
HD145  30.76%   64.81%   36.36%   58.92%    31.52%   60.21%
HD146  19.91%   76.58%   22.02%   74.65%    20.26%   74.54%
HD147  19.94%   75.21%   23.29%   72.05%    20.71%   72.50%
HD148  35.91%   58.42%   41.28%   52.65%    37.16%   54.37%
HD149  35.46%   61.15%   36.92%   59.67%    35.03%   59.11%
HD150  62.31%   33.69%   63.39%   32.19%    62.52%   32.70%
						
CC1    22.48%   73.86%   25.03%   71.41%    22.93%   71.70%
CC2    48.48%   47.61%   51.23%   44.47%    48.46%   45.14%
CC3    53.16%   42.92%   55.63%   40.36%    53.51%   41.15%
CC4    55.12%   40.78%   57.10%   38.46%    55.47%   39.29%
Justice Dori Garza

Justice Dori Garza

The figures above represent the races with Dori Garza and Eva Guzman, who were the top Democratic and Republican vote-getters among judicial candidates. Guzman was actually the high scorer overall, while Garza has the second-best Democratic total, trailing Hillary Clinton but topping Barack Obama in 2008. The other numbers are aggregates of all the Supreme Court and Court of Criminal Appeals candidates, where “R SJ Avg” means “Republican statewide judicial average” and “D SJ Avg” is the same thing for Democrats. The percentages have been calculated to include the third parties, though I didn’t explicitly list them for the sake of saving space.

The differences in each district are small, but they add up. Dori Garza received 162K more votes statewide than Savannah Robinson, while Eva Guzman collected 124K more than Paul Green. As previously expressed for third party candidates, I believe being Latina was an advantage for both Garza and Guzman, as I suspect they got the votes of some people who didn’t have a strong partisan preference and were perhaps drawn to a familiar name in a race where they didn’t know anything about who was running. This advantage is not universal – I suspect if I looked around the state, the effect would be small and possibly even negative in places that have few Latino voters. You can certainly see a difference for Garza in HDs 140, 143, 144, 145, and 148 compared to other districts, where the gap between her and the average D is around four points. It also doesn’t hurt that Garza and Guzman were both strong candidates, who were widely endorsed and (at least in Garza’s case) ran actual campaigns. None of this mattered this year, but if this had been a year where the margin at the Presidential level had been two or three points instead of nine, this could have been the difference between a close win and a close loss. I don’t want to over-generalize here, as in any year there will be a high scorer and a low scorer, but it’s something to keep in mind when we start recruiting candidates for 2018 and 2020.

But also keep in mind the fact that despite getting nearly 300,000 more votes than President Obama in 2012, Garza only received 41.12% of the vote, which is less than what Obama got that year. This is because the Republican vote was up, too. Compare Garza’s race to the Supreme Court, Place 6 election in 2012. Garza outpolled Michelle Petty by 279K votes, but Paul Green outdid Nathan Hecht by 629K. Go back to 2008 and Supreme Court, Place 8, and it’s more of the same: Garza improved on Linda Yanez by 170K, while Green did 738K better than Phil Johnson. The preponderance of new voters in Harris County were Democrats. That was not the case statewide. That’s a problem, and we shouldn’t let Hillary Clinton’s performance against Donald Trump distract us from that.

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