Off the Kuff Rotating Header Image

December 19th, 2022:

Precinct analysis: Beto versus the spread

Beto versus Abbott

So last time we saw the numbers for the 2022 Governor’s race. But what numbers need in order to be meaningful is context, and that means other numbers to compare them to. We’re going to do that in a few different ways, and we’ll start with the numbers from the Texas Redistricting Council for these new districts. Specifically, the numbers from 2018 and 2020.

Dist    Abbott    Beto     Cruz    Beto
HD126   35,835  23,627   38,851  26,028
HD127   39,102  26,791   40,573  28,326
HD128   31,983  13,915   32,586  15,892
HD129   37,118  27,144   38,281  29,112
HD130   44,983  20,891   42,747  20,968
HD131    5,963  25,387    5,628  33,440
HD132   35,079  25,603   32,220  23,431
HD133   33,195  26,971   34,930  30,329
HD134   29,592  51,010   32,114  54,514
HD135   16,443  24,121   16,162  27,762
HD137    7,860  13,421    8,713  19,309
HD138   31,077  25,464   32,754  28,778
HD139   11,643  32,115   11,599  38,842
HD140    5,717  13,400    5,393  19,532
HD141    4,549  20,922    4,459  28,096
HD142    8,666  25,793    8,265  29,705
HD143    8,420  16,047    8,751  23,602
HD144   11,566  14,683   12,511  21,278
HD145   12,631  32,765   12,101  37,672
HD146    8,511  33,610    9,227  40,111
HD147    8,952  37,366    9,575  45,020
HD148   15,451  21,460   16,281  26,815
HD149   12,068  19,844   12,097  27,142
HD150   33,857  23,303   33,084  23,466

Dist   Abbott%   Beto%    Cruz%   Beto%
HD126   59.37%  39.14%   59.40%  39.80%
HD127   58.50%  40.08%   59.30%  40.00%
HD128   68.66%  29.87%   66.80%  32.60%
HD129   56.80%  41.53%   56.30%  42.80%
HD130   67.29%  31.25%   66.60%  32.70%
HD131   18.78%  79.96%   14.30%  85.20%
HD132   57.06%  41.64%   57.50%  41.80%
HD133   54.41%  44.21%   53.10%  46.10%
HD134   36.16%  62.34%   36.80%  62.40%
HD135   39.97%  58.63%   35.00%  64.40%
HD137   36.32%  62.01%   30.90%  68.40%
HD138   54.09%  44.32%   52.80%  46.40%
HD139   26.25%  72.41%   22.90%  76.50%
HD140   29.36%  68.82%   21.50%  78.00%
HD141   17.61%  80.98%   13.60%  85.80%
HD142   24.79%  73.80%   21.60%  77.80%
HD143   33.86%  64.53%   26.90%  72.50%
HD144   43.34%  55.02%   36.80%  62.50%
HD145   27.31%  70.85%   24.10%  75.00%
HD146   19.95%  78.80%   18.60%  80.70%
HD147   19.04%  79.49%   17.40%  81.90%
HD148   41.18%  57.19%   37.50%  61.70%
HD149   37.31%  61.36%   30.60%  68.70%
HD150   58.34%  40.15%   58.10%  41.20%

Greg Abbott got 490K votes in 2022, whereas Ted Cruz got 498K in 2018. It’s therefore not a surprise that Abbott generally matched Cruz’s vote totals in the districts, with a bit of variation here and there. Beto, meanwhile, got 595K votes in 2022 after getting 700K in 2018, a significant drop. You can clearly see that in the district data. What’s interesting to me is that Beto was pretty close to his 2018 performance for the most part in Republican districts. His dropoff was almost entirely in strong Democratic districts, which accounts for the decrease in vote percentage he got. This is consistent with reports that Republicans had the turnout advantage nationally, due in part to weaker Democratic turnout among Black voters.

You can shrug your shoulders about this or freak out for What It All Means for 2024 as you see fit. I tend to lean towards the former, but I will readily acknowledge that the job of working to get turnout back to where we want it for 2024 starts today. I’ll have more to say about this in future posts as well, but let me open the bidding by saying that the target for Democratic turnout in Harris County in 2024, if we want to make a serious run at winning the state for the Democratic Presidential nominee, is one million Democratic votes; it may actually need to be a little higher than that, but that’s the minimum. It’s doable – Biden got 918K in 2020, after all. Ed Gonzalez got 903K in his re-election for Sheriff. Really, we may need to aim for 1.1 million, in order to win the county by at least 300K votes, which is what I think will be needed to close the statewide gap. Whether we can do that or not I don’t know, but it’s where we need to aim.

I also want to emphasize the “Abbott got more or less the same number of votes in each district as Cruz did” item to push back as needed on any claims about Abbott’s performance among Latino voters. His improvement in percentage is entirely due to Beto getting fewer votes, not him getting more. That’s cold comfort from a big picture perspective for Democrats, and as we saw in 2020 a greater-than-expected share of the lower-propensity Latino voters picked Trump, so we’re hardly in the clear for 2024. All I’m saying is that claims about Abbott improving his standing with Latino voters need to be examined skeptically. Remember that if we compared Abbott to Abbott instead of Beto to Beto, he got 559K votes in 2018, so he dropped off quite a bit as well. He got fewer votes in each of the Latino districts in 2022 than he did in 2018:

HD140 – Abbott 6,466 in 2018, 5,717 in 2022
HD143 – Abbott 10,180 in 2018, 8,420 in 2022
HD144 – Abbott 13,996 in 2018, 11,566 in 2022
HD145 – Abbott 15,227 in 2018, 12,631 in 2022
HD148 – Abbott 18,438 in 2018, 15,541 in 2022

So yeah, perspective. I suppose I could have done the Governor-to-Governor comparison instead, but I was more interested in Beto’s performance, so that’s the route I took. Beto would look better from a percentage viewpoint if I had done it that way. There’s always more than one way to do it.

One last thing on turnout: In 2014, Wendy Davis led the Democratic ticket with 320K votes in Harris County. Beto was at over 401K even before Election Day. His total is almost twice what Davis got. We can certainly talk about 2022 being “low turnout”, but we’re in a completely different context now.

Dist    Abbott    Beto    Trump   Biden
HD126   35,835  23,627   50,023  35,306
HD127   39,102  26,791   53,148  38,332
HD128   31,983  13,915   46,237  21,742
HD129   37,118  27,144   51,219  38,399
HD130   44,983  20,891   58,867  29,693
HD131    5,963  25,387   10,413  42,460
HD132   35,079  25,603   46,484  35,876
HD133   33,195  26,971   42,076  40,475
HD134   29,592  51,010   38,704  66,968
HD135   16,443  24,121   26,190  40,587
HD137    7,860  13,421   12,652  24,885
HD138   31,077  25,464   42,002  37,617
HD139   11,643  32,115   17,014  49,888
HD140    5,717  13,400   10,760  24,045
HD141    4,549  20,922    8,070  38,440
HD142    8,666  25,793   13,837  41,332
HD143    8,420  16,047   15,472  28,364
HD144   11,566  14,683   20,141  25,928
HD145   12,631  32,765   18,390  45,610
HD146    8,511  33,610   12,408  51,984
HD147    8,952  37,366   14,971  55,602
HD148   15,451  21,460   24,087  34,605
HD149   12,068  19,844   21,676  35,904
HD150   33,857  23,303   45,789  34,151

Dist   Abbott%   Beto%   Trump%  Biden%
HD126   59.37%  39.14%   57.80%  40.80%
HD127   58.50%  40.08%   57.30%  41.30%
HD128   68.66%  29.87%   67.10%  31.60%
HD129   56.80%  41.53%   56.20%  42.20%
HD130   67.29%  31.25%   65.50%  33.00%
HD131   18.78%  79.96%   19.50%  79.60%
HD132   57.06%  41.64%   55.60%  42.90%
HD133   54.41%  44.21%   50.30%  48.40%
HD134   36.16%  62.34%   36.10%  62.50%
HD135   39.97%  58.63%   38.70%  59.90%
HD137   36.32%  62.01%   33.20%  65.40%
HD138   54.09%  44.32%   52.00%  46.60%
HD139   26.25%  72.41%   25.10%  73.70%
HD140   29.36%  68.82%   30.60%  68.30%
HD141   17.61%  80.98%   17.20%  81.80%
HD142   24.79%  73.80%   24.80%  74.10%
HD143   33.86%  64.53%   34.90%  64.00%
HD144   43.34%  55.02%   43.20%  55.60%
HD145   27.31%  70.85%   28.30%  70.10%
HD146   19.95%  78.80%   19.00%  79.80%
HD147   19.04%  79.49%   20.90%  77.60%
HD148   41.18%  57.19%   40.50%  58.10%
HD149   37.31%  61.36%   37.20%  61.70%
HD150   58.34%  40.15%   56.50%  42.10%

Obviously, the vote totals don’t compare – over 1.6 million people voted in 2020, a half million more than this year. But for the most part, Beto was within about a point of Biden’s percentage, and even did better in a couple of districts. Abbott did best in the Republican districts compared to Trump. As we’ll see when we look at the other statewide races, Abbott (and Dan Patrick and Ken Paxton) was one of the lower performers overall among Republicans, as was the case for Trump in 2020, but maybe there were slightly fewer Republican defectors this year.

It will take an improvement on the 2020 Biden and 2018 Beto numbers for Dems to put any State Rep districts into play, with HD138 being the first in line; remember that HD133 was a bit of an outlier, with a lot of Republican crossovers for Biden. Incumbency has its advantages, and as we have seen Dem performance can be a lot more variable downballot than at the top, especially when the top has the most divisive Republicans, so it will take more than just (say) Biden getting 50.1% in HD138 for Rep. Lacy Hull to really be in danger. It’s more that this will be another incentive to really work on boosting overall turnout. Having a good candidate in place, which I think Stephanie Morales was this year, and making sure that person has the financial and logistical support they need (which she didn’t have) will be key.

I’ll have more to say as we go along. Please let me know what you think and ask any questions you may have.

More on the limits of social media monitoring for school violence prevention

Some good stuff from the DMN.

When Social Sentinel representatives pitched their service to Florida’s Gulf Coast State College in 2018, they billed it as an innovative way to find threats of suicides and shootings posted online. But for the next two years, the service found nothing dangerous.

One tweet notified the school about a nearby fishing tournament: “Check out the picture of some of the prizes you can win – like the spear fishing gun.”

Another quoted the lyrics from a hit pop song from 2010: “Can we pretend that airplanes in the night sky are like shooting stars? I could really use a wish right now.”

As police and administrators fielded a flood of alerts about posts that seemed to pose no threat, the company told the school in emails that it had eliminated more than half of all irrelevant alerts. Months later, they said the number had decreased by 80%. By January 2019, the company told schools its service flagged 90% fewer irrelevant posts.

But at Gulf Coast, the problem continued.

One alert from March 2019 read, “Hamburger Helper only works if the hamburger is ready to accept that it needs help.”

“Nothing ever came up there that was actionable on our end,” David Thomasee, the executive director of operations at Gulf Coast, said in an interview earlier this year. The college stopped using the service in April 2021.

Gulf Coast was not the only college inundated with irrelevant alerts. Officials from 12 other colleges raised concerns about the performance of Social Sentinel in interviews and emails obtained by The Dallas Morning News and the Investigative Reporting Program at UC Berkeley’s Graduate School of Journalism.

Only two of the 13, North Central Texas College and the University of W Connecticut, still use the service.

As schools and universities confront a worsening mental health crisis and an epidemic of mass shootings, Social Sentinel offers an attractive and low-cost way to keep students safe. But experts say the service also raises questions about whether the potential benefits are worth the tradeoffs on privacy.

Records show Social Sentinel has been used by at least 38 colleges in the past seven years, including four in North Texas. The total number is likely far higher — The company’s co-founder wrote in an email that hundreds of colleges in 36 states used Social Sentinel.

The News also analyzed more than 4,200 posts flagged by the service to four colleges from November 2015 to March 2019. None seem to contain any imminent, serious threat of violence or self-harm, according to a News
analysis, which included all of the posts obtained through public records requests.

Some schools contacted by The News said the service alerted them to students struggling with mental health issues. Those potential success stories were outweighed by complaints that the service flagged too many irrelevant tweets, interviews and emails between officials show. None of the schools could point to a student whose life was saved because of the service.


For one former Social Sentinel employee, it only took three days before they had serious doubts about the effectiveness of the service.

The worker estimated that 99.9% of the flagged posts sent to clients were not threatening. The service often crashed because it flagged too many posts. At least 40% of clients dropped the service every year, the employee said.

Over the course of several months, the employee repeatedly raised concerns with supervisors and fellow employees about flaws in the system, but those complaints were often ignored, the worker said.

The employee, who asked not to be named for fear of retribution, said problems with the service were an open secret at the company, and described it as “snake oil” and “smoke and mirrors.”

The News also contacted more than two dozen other former company employees, who either did not respond or said they had signed nondisclosure agreements preventing them from speaking publicly about their time at the company.

At the University of Texas at Dallas, which started using the service in 2018, campus police officers in charge of the service also grew increasingly skeptical of its performance, emails obtained through a records request show.

“Does the company have any data (not anecdotal) to show its success rate in mitigating harm or disaster through its alert system?” UT Dallas Police Lieutenant Adam Perry asked his chief in an email obtained by The News. The chief forwarded the email to a company employee who didn’t answer the question.

Perry said that while the school used the service, the technology never alerted police to legitimate threats of suicide or shootings.

“I think in concept, it’s not a bad program,” Perry said. “I just think they need to work on distinguishing what a real threat is.” UT Dallas ended its use of the service last year.

Ed Reynolds, police chief at the University of North Texas, defended the system, but also estimated that “99.9 percent (of the alerts) were messages we didn’t need to do anything with.” After using the service for about three years, UNT ended its contract with the company in November 2018.

As noted before, the Uvalde school district was among the ISDs in Texas that have used Social Sentinel. Putting my cybersecurity hat on for a minute, there are similar services in that space that do provide good value, but they have been around longer, there’s far more data on cyber threats, and it’s much easier to configure alerts for these services to very specific things, which greatly reduces the noise factor. I do think a service like this could be useful, but what we have now is not mature enough. More data and more analysis to help eliminate likely false positives before they show up in a customer’s alert feed are needed. Even with that, it’s still likely to be noisy and to require fulltime human analysis to get value out of it. For now, the best use of this is probably for academics. After they’ve had some time with it, then school districts and colleges might make use of it.

True the Vote keeps on contempting

Here’s the latest filing from the plaintiffs in the defamation lawsuit against True the Vote and their lying grifter principles, Catherine Engelbrecht and Gregg Phillips. You may recall that Engelbrecht and Phillips spent a few days in the pokey for contempt having to do with their utter refusal to produce documents and other evidence that they were ordered to do. After a week, they were sprung by the Fifth Circuit, with the agreement/advisory that they really ought to, you know, comply with those orders.

Well, spoiler alert, they have not done so. Indeed, to the surprise of exactly no one who has been forced to pay any attention to this clown show, they have kept on being defiantly contemptuous. This filing goes into detail, and I’ll give you a taste:

Plaintiff Konnech, Inc. (“Konnech”) requests that this Court order Defendants True the Vote, Inc., Gregg Phillips, and Catherine Engelbrecht (“Defendants”) and their counsel of record to appear and show cause why they should not be held in contempt for violating the Court’s direct order from the bench at the prior October 27, 2022 show cause hearing and the Preliminary Injunction signed by this Court on October 31, 2022, based on the following grounds:

Defendants’ contempt is undeniable and inexcusable. For nearly three months, Defendants have defied this Court’s orders—including a TRO, Preliminary Injunction, and a direct order from the bench—requiring them to identify everyone who was involved in accessing the personal identifying information (“PII”) of U.S. poll workers on Konnech’s computers, to describe how they did it, and to identify everyone who has had possession of it. Defendants have treated compliance with the Court’s orders like a game of cat and mouse, and they have refused to comply with this Court’s orders even after being jailed for their contempt of the Court’s TRO.

Now, Defendants are in contempt of Sections 3, 4, 6 and 7 of the Preliminary Injunction signed on October 31, 2022, and entered by the clerk on November 3, 2022. Defendants violated Sections 3, 6 and 7 of the Preliminary Injunction for the same reasons that they violated Sections 5, 6 and 7 of the TRO, which are identical. There is evidence to suggest that Defendants also violated Section 4 of the Preliminary Injunction which required them to return all Konnech data in their possession to Konnech. On October 28, Defendants filed an affidavit signed by Defendant Engelbrecht which attached text messages of her alleged communications with the FBI about Konnech. Embedded in those text messages is a spreadsheet titled “Sort by State PII filter SSN Dupes DLN,” which, considering that this file is contained in text messages between Defendants and purported FBI agents with whom Defendants were in contact concerning Konnech, the data therein may include stolen Konnech data. Therefore, given Defendants’ testimony at the show cause hearing that they never had such PII, Defendants may be in further contempt of the
Preliminary Injunction by refusing to return the data contained in this file to Konnech, as required by Section 4 of the Preliminary Injunction. Additionally, Defendants also refused to comply with the Court’s direct order from the bench on October 27 to name every person in the hotel room where Defendants claimed to have accessed PII on Konnech’s computers.

The only appropriate description of Defendants’ conduct is contemptuous. Defendants are blatantly defying the Preliminary Injunction and a bench order for them to provide testimony—which renders them recalcitrant witnesses—and they should be held in contempt of Court for their misconduct.

It’s a long document, but most of that is the evidence that the plaintiffs present. There’s only about ten pages to read to understand their allegations, which includes social media mockery of the judge and threats against one of the Konnech principles. Konnech asks for TTV et al to be subject to “compensatory and coercive sanctions which the Court deems necessary to obtain Defendants’ compliance and to deter further contempt”, among other things. Jail didn’t work, so maybe that will. I’ll keep an eye on this going forward.