Early Election Problems

Last week, I gave a public presentation at Caltech, “Can American Have a Safe and Secure Presidential Election?” You can now watch it on YouTube!

One of the things I discussed in the talk were the many real issues that are likely to arise in this fall’s general election, things like long lines in early and Election day voting, administrative snafus, and voter mistakes. We are now starting to see some of these issue arising, as many Americans are now voting in-person, by mail, or using ballot drop boxes.

For example, last week there were reports of a ballot printing error in Los Angeles County, in which an estimated 2100 voters received ballots in the mail that did not have the presidential race.. Also in California, there are reports of unofficial ballot drop boxes being deployed in a number of counties throughout the state, including in Los Angeles, Fresno, and Orange Counties. And with the opening of early voting in Georgia came reports of very long lines, and very long voter wait times.

Keeping in mind that we are just really starting to enter the final weeks of the general election, and that there is a great deal of scrutiny on election administration and voting technology this year, my opinion is that we are really just seeing early signs of things to come. Voters need to be patient, and need to be very careful to check that they have received the right ballot (whether by mail or in person). And check your ballot carefully, making sure to return it to an official ballot drop box, or send it by mail using an official mail drop inside a USPS office.

VTP launches voter guide for November 2020

The Caltech/MIT Voting Technology Project has just launched a voter guide for November 2020. You can download the pdf of the voter guide from the VTP website.

Or here’s fun animated graphic (just click on the image, and it’ll launch the interactive voter guide in an informative and fun animated image)!

Special thanks to Silvia Kim for the great suggestion that we get a professional to make the animated graphic!

What to Make of President Trump’s Tweets?

Charles Stewart III

President Trump is apparently exercised that some states, especially battleground states, might be mailing absentee ballot applications to all their voters, so that they can request a mail ballot be sent to them. In fairness to the president, many of these states are new to the large-scale mail-ballot game, and have been struggling to keep up with demand.

But, notice the problem. He is angry at states for nudging their registered voters to take advantage of their absentee voting laws, and yet calls absentee voting good, because it involves an application.

Where do they mail ballots to all residents, which the president apparently hates? In five states, none of which is a battleground state, and each of which has a reputation for clean elections. In fairness, two of these, Hawaii and Utah, are new to the mail-ballot party in 2020. But say what you want about 100% mail balloting, Colorado, Oregon, and Washington have not been beset with nonstop election-fraud allegations since they adopted their systems.

Not only that, but some of the most prominent proponents of mail balloting in these western states have been Republicans. These include Sam Reed, the three-term Washington Secretary of State who ushered in that’s state’s adoption of all-mail balloting. Republican Kim Wyman has vigorously defended the system since she succeeded Reed. Since losing his 2018 re-election fight in Colorado, former-Secretary of State Wayne Williams has been defending his state’s system against all comers.

What is going on here? It’s obvious. For some reason, President Trump (and many national Republican leaders generally) have gotten it in their heads that Democrats are inherently advantaged by mail balloting. In fairness, I think that Democrats believe this, too. Both are wrong. Nonetheless, bowing to conventional wisdom, from a strategic perspective, he believes that mail balloting needs to be limited.

But, the logic doesn’t work, even if you twist it in Escherian ways.

The problem, of course, is that President Trump himself votes by mail, as does his family. The distinction, as I understand it, is that he has requested the ballots; the ballots haven’t been mailed to him automatically.

Yet, this is precisely what is happening—or might happen—in the battleground states he seems so worried about.

What President Trump is railing about it not happening—or at least not in the states that will decide his political future.

One final thing. Despite the fact that President Trump says he votes absentee, that’s not what the State of Florida—where he is registered—says he is doing. Florida changed its election code several years ago, getting rid of the term “absentee balloting,” replacing it with the term “vote-by-mail.”

There is plenty to do to prepare for the upcoming election. Getting mail ballots to the right people and protecting in-person polling place is where attention to should be paid right now. All of us need to avoid the chaos and keep to the serious work.

Oh.  One last thing.  Most of the news today has focused on the last line of the President’s tweet, asking about whether we should postpone the election.  That’s such a ridiculous idea, and so easily debunked on a bipartisan basis (as it has been), that I don’t think it deserves any more comment than what I’ve just given it.

Nine Thoughts about Lost Votes by Mail

By Charles Stewart III

A “lost vote” occurs when a voter does all that is asked of her, and yet her vote is uncounted in the final tally. Estimating the magnitude of lost votes in American presidential elections has followed the work of the Caltech/MIT Voting Technology Project (VTP), which initially estimated the magnitude of lost votes in the 2000 presidential election—due to failures of voter registration, polling-place management, and voting technologies—to be between 4 and 6 million out of 107 million cast that year.

Because of data and conceptual limitations, lost vote estimates have tended to focus on in-person voting, ignoring lost votes due to mail ballots. In a paper I recently finished, I revisited an article I wrote in 2010 that attempted to fill the hole in our understanding of lost votes, by considering mail votes in the 2008 election. That paper estimated that as many as 22% of mail ballots were “lost”—as defined by the VTP—in that election. Despite the fact that I opined in the article that this was clearly an over-estimate, this 22% statistic has been repeated without the caveats that appear in the article. (For examples, see here, here, here, and here.)

Over the past decade, it has been suggested that I should reconsider that earlier article, for two reasons. First, mail balloting has become much more complicated, with states adopting a variety of approaches to mail balloting. Each approach, from excuse-required absentee balloting to vote-by-mail, creates unique risks for and protections against lost votes. I owe it to the evolving policy to align my thinking with the new reality. Second, the data have become better than they were in 2010. A reconsideration should reflect that new data.

I encourage you to take a look at a draft of the paper, which is slated to be published in the Harvard Data Science Review before the election. Below are the take-aways from the article, as a preview.

  1. “Lost vote” is a term of art that draws our attention to the gap between a voter’s intention to vote—in this case by mail—and the completion of the intention. In no way does it refer to ballots that have been physically lost, in the literal sense that there are millions of ballots sitting in a trash heap somewhere.
  2. The number of lost mail votes in 2016 was more like 4% of mail ballots, not 22%. The principal source was rejected ballots, which has garnered plenty of attention in the 2020 primaries, for instance, because they arrived late. The next-largest cause was a heightened residual vote rate, that is, over- and undervotes. The smallest contributor, which is also the most difficult to estimate, is problems with the postal service and the non-delivery of requested ballots.
  3. The states that have the most expansive vote-by-mail laws have the lowest lost-vote rates. This is because no requests for absentee ballots are lost in the mail in these states and because vote-by-mail states reject a much smaller fraction of returned mail ballots than states that require voters to explicitly request them.
  4. Conversely, states that require voters to request absentee ballots have higher lost-vote rates, mostly because these states are more likely to reject them when received.
  5. The fact that 22% of the ballots that were mailed to voters in the vote-by-mail states in 2016 were not returned for counting is due almost entirely to voter abstention, nothing more.
  6. The biggest empirical puzzle remains why 7% of voters in excuse-required states and 14% of voters in no-excuse states who requested a mail ballot never returned one. If 99.5% of the mail gets delivered within the window of postal service standards, this can’t be because ballots are getting lost by the USPS. But, these percentages seem too high to be explained simply by ballot requesters getting cold feet.
  7. The states that will expand the use of mail ballots the most in 2020 will be among those with the greatest ballot-rejection rates in 2016. New York’s 2016 rejection rate was over 10%, which is entirely consistent with reports currently coming out of the state from the primary.
  8. One sign of hope is that the heightened scrutiny of mail ballot rejections, including some court-case settlements, may keep rejection rates in check in November. Georgia is a good example. In 2016, its mail-ballot rejection rate was 6.9%. In the recent primary, it was closer to 1%.
  9. Voting by mail is risky.  So is voting in person, especially in the age of COVID-19.  The risks are of a different nature.  It is the responsibility of election officials to try and minimize voting risks as much as they can.  It is the responsibility of voters to weigh the risks of voting, and to vote using the mode they feel the most comfortable with.

LA County March 2020 Primary Election Vote Center Evaluation Study

Today we are releasing our preliminary report that looks at the performance of vote centers in the March 2020 primary election in LA County. Our study, the “Preliminary Evaluation of Los Angeles County Vote Center Performance in the March 2020 Primary Elections”, was researched and written by Daniel Guth, Claudia Kann, Seo-young Silvia Kim, and myself.

The report presents the results of a large data analysis project we’ve done in collaboration with the Los Angeles County Registrar Recorder/County Clerk, in which we use a number of unique datasets and dive deeply into many aspects of vote center operations in LA County’s March 2020 primary election. This new preliminary report gives a detailed data-driven analysis of the performance of LA County’s vote centers in the March 2020 primary election, paralleling our qualitative observations in our Election Day observation study, which was released on March 30, 2020.

The key recommendations from our detailed study of vote center performance in the March 2020 primary election are:

  1. We recommend that LACRR/CC strengthen and emphasize the process where real-time wait times data is collected for each vote center, and have them made available to voters and vote center staff in real-time.
  2. We recommend that additional independent evaluation of PollPad malfunctions be undertaken, especially with regard to the Internet connectivity and syncing of PollPads.
  3. We recommend that several datasets not analyzed in this report be made available to better assess the issues that arose in the March primary. These include evaluation of vote center locations, trouble ticket logs, and surveys of vote center staff.
  4. We recommend that LACRR/CC continue to study the functionality of BMDs in the
    March primary. Our research group will also continue to study the available data on
    BMD performance in the March primary. We suggest the following measures for the November general election:

    1. Provide clear, visible guidelines to the voter on how to correctly insert the ballot into the BMD at every BMD to reduce the paper jam rates.
    2. Train the vote center lead to quickly fix a malfunctioning BMD.
    3. Have a technical help backup team ready, especially late on Election Day.

We note that some of our recommendations parallel those in the recently released VSAP Board Report, and we welcome the opportunity to continue our collaboration with the LA County Registrar Recorder/County Clerk, Dean Logan, and his team. We want to thank Dean Logan and his team for providing us with this unparalleled opportunity to have access to the data we used in this report, and for their willingness to answer our questions and help us understand the data and vote center operations in the March primary election.

Mail Ballot Watch

By Charles Stewart III

The MIT branch of the Stanford-MIT Healthy Elections Project has started a time series to follow the fraction of ballots cast by mail in the primaries.  We will be updating on a regular basis and posting the graph to Twitter and here.  Here is the most recent graph, as of July 6, 2020.  Please let me know if you find any errors, have questions, or have leads on data.  Below the graph are some notes on data sources.

About data sources:  In general, we relied on the official state election returns or other state records (such as voter files) to record the data.  The following are exceptions:

  • Texas.  In 2016, the state did not report percentage of votes cast by mail, although some counties did.  The data for 2016 and 2020 reflect the percentage of votes cast by mail in the counties that reported the data in 2016.
  • Arizona.  Data are only from Maricopa County, which constitutes 61% of the state’s population.  
  • Pennsylvania.  Data from 2016 are general election rates, taken from the Election Administration and Voting Survey.

The following states are excluded because they held caucuses in 2016:  Colorado, Maine, Minnesota, Utah, North Dakota, Alaska, Kansas, and Hawaii.

States that are normally all-mail are excluded.

Vermont is excluded because 2016 data are unavailable.

The other states not on the graph, but which have held primaries, await the release of data from the state.

Resilient Elections

I’m excited to announce that I’ve started a video series with Paul Gronke, who runs the Early Voting Information Center (EVIC) up at Reed College. We just posted our first video, in which Paul and I give a brief introduction to the series. Please watch our intro, subscribe to our YouTube channel, and let us know your comments and questions.

As we discuss in the introductory video, we are going to focus on topics that we know are going to be important to researchers and election officials as we get closer to the November 2020 presidential elections in the U.S. Paul and I will are working on a number of different videos — some will be the two of us discussing important election science and administration topics. Some will be conversations with other academics who are working on important research questions like voting by mail, election forensics, election integrity, and voter confidence. And finally, we are going to have conversations with election officials, in particular those on the West Coast, who have extensive experience with early and remote voting.

If you are interested in suggesting certain topics, let us know in the YouTube channel comments.

Five Wisconsin Take-Aways

By Charles Stewart III, MIT

The following is a list of take-aways from the Wisconsin primary. I will be elaborating on these points in the following days, but I wanted to get these down before the day got too far out of hand.

  1. It is possible to rapidly expand vote-by-mail even when you’re not prepared for it, but don’t try this at home. The state was in about as bad a bind as one could imagine—a shifting, uncertain health crisis, conflicting court decisions, a deadlocked state election commission, a history of little vote-by-mail, and the most decentralized election administration system in the nation. And yet, 1.1 million mail ballots were received in time to be counted—a record for any election in the history of Wisconsin.
  2. In-person voting is still necessary. The collapse of in-person voting in Green Bay (Brown County) and Milwaukee City (Milwaukee County)—and perhaps in other municipalities, as well—had a measurable effect on turnout. A simple statistical model suggests that Milwaukee County came in 19,000 votes below expected, Green Bay at 10,000 votes below expectations.
  3. The first act of the primary is an amazingly good start, but it doesn’t mean we are out of the woods yet. We do not know yet how many absentee ballots were rejected because they arrived too late, or because of other infirmities.
  4. A surprisingly good primary does not guarantee a surprisingly good general election. The electorate in a general election is different from the primary election. It’s less experienced and has more difficulties at the polls. It will be less capable of jumping through the hoops to get ballots, and it will be more reliant on election-day registration to be able to vote in the first place. The primary is a good start, but it’s just a start.
  5. Wisconsin’s electoral landscape is shifting. First, even with the difficulties, turnout was well above what a statistical model would have predicted, given the lack of a challenger in one party and the un-competitiveness in the other. Second, the shift in votes that gave rise to the liberal’s victory in the supreme court race—a proxy for partisan politics more broadly—show a pull-back in support for conservative politicians in suburban Milwaukee counties, in counties of the Twin-City exurbs, and in the small “Obama-Trump” counties throughout the state.

What “Should” We Expect Turnout to Be in Wisconsin?

By Charles Stewart III, MIT

While we wait for the election results to be released later tonight, it would be useful to predict a priori what we would expect turnout to end up being. With an expectation established, based on past voting patterns in Wisconsin, it will be easier to assess how the unusual circumstances surrounding the primary may have affected turnout and the vote shares for candidates.

The exercise here is entirely empirical. There are too few data points—18 in all—to build an elaborate model. The main explanatory variable I will explore is the competitiveness of the presidential nomination fight.


A simple two-variable model of turnout

To start, I look at turnout in the presidential preference primary from 1948 to 2016, as a percentage of the voting-age population. Turnout is taken from the Wisconsin Elections Commission website, as is voting-age population, with the exception of 2012 and 2016, which I got from Michael McDonald’s United States Elections Project website.

There are two notable patterns in the accompanying figure. (Click on any of the figures in this post to enbiggen.)  First, there is a steep drop in turnout between the 1980 and 1984 primary.  I’m not certain what caused this—it’s not due to the passage of the 26th Amendment to the U.S. Constitution, which gave 18-year-olds the right to vote, because that took effect with the 1972 election.

It has been suggested to me (thanks, Barry Burden) that prior to 1980, Wisconsin was typically early in the primary season, compared to other states, and thus a much more significant event in the hunt for the nomination. In any event, it is clear that 1984 and onward constituted a different turnout regime than the pre-1984 period. Whether the years prior to 1960 properly belongs to an even different period is an interesting question, but isn’t obviously relevant to the exercise of creating an expectation for turnout in 2020.

The exception to this simple periodization is 2016, where the turnout level of 47% was nearly twenty points higher than the average of the 1984 – 2012 period (29%). I will return to this point below.

The second pattern in the time series is the increase in turnout in years when the incumbent was not running for president, in other words, was precluded by the constitution from running for a third term. (Open-seat years are indicated with the open circles in the graph.) With the exception of 2000, the existence of a presidential open seat is associated with an increase in turnout in the primary, compared to the prior presidential election year. (And, one could possible even argue that Al Gore’s candidacy as Bill Clinton’s heir in 2000 meant that Gore was considered to be the de facto incumbent in the Democratic primary that year.)

The mechanism here is clear. With an incumbent president running for reelection, the in-party’s primary battle is typically subdued compared to the out-party’s. Absent another reason to come to the polls, the in-party’s partisans are likely to stay away to come degree. Conversely, in years where the incumbent cannot run for reelection, both parties tend to have hard-fought contests, drawing voters from both parties to the polls.

For starters, then, this suggests a simple regression model, where the dependent variable is turnout as a percentage of VAP and the independent variables are two dummy variables indicating (1) whether the year is 1984 or after and (2) whether the incumbent president is term-limited from running again. The results are in the accompanying table.

This allows for a simple prediction for 2020. With Trump not term-limited out, we would expect turnout in 2020 to be 40.6 – 13.2 = 27.4 percent of voting-age population. With VAP at 4,573,223, this works out to 1,253,063.

Adding competition

There is something unsatisfactory with models that rely solely on dummy variables, especially dummy variables demarking time periods, because they essentially say that nothing changes during the period in question, beyond random noise. Further examination of the graph above suggests there may be another dynamic at work, beyond whether the president is term-limited out, and that is the actual competitiveness of the races at hand.

For instance, in the post-war period, there were three elections in which both parties had hot nomination contests when the primary rolled around to Wisconsin—1980, which featured Kennedy and Carter duking it out on the Democratic side and Reagan and Bush locked in a tight race on the Republican side; 2008, with Clinton v. Obama and McCain v. Hckabee; and 2016, with Clinton v. Sanders and Cruz v. Trump and Kasich.

We can extend the previous regression model by adding the “effective number of candidates” measure to the mix. (See the end of this post to see a discussion of the effective number of candidates measure.  In this case, I add the effective number of candidates in the two parties to create a unified variable. I do this to preserve degrees of freedom.)

Doing so reveals the results in the accompanying table.

With the 2020 Republican primary uncontested and the Democratic primary down to two candidates, one of whom was already the presumptive nominee by primary day, the effective number of candidates for the 2020 primary was already among the lowest in the time series. In the best of cases, if Biden and Sanders tie, the effective number of candidates across the two parties would be precisely three—one for the Republicans plus two for the Democrats. As the following graph shows, the 2020 primary will likely be the least competitive Wisconsin presidential primary, considering the two parties together, since 1964.

 

To make a prediction from the regression model model, we have to estimate the results of the Democratic primary, while simplifying things by setting the effective number of Republican candidates to 1, ignoring scattering votes on the Republican side. The following table shows the range of estimates, varying the percentage of the vote for Biden from 30% to 70%, ignoring the vote for the other candidates.


The high-end estimate, with a Biden-Sanders tie, is 23.9% of VAP, four points below what we predict without taking the non-competitive nature of the primary into account.

What about the 2016 outlier?

The one thing that makes me uneasy about these predictions is the 2016 primary turnout of 47%, the highest since 1980. Several commentators have suggested that 2016 had an especially high turnout because of the fiercely fought race for Wisconsin Supreme Court, between the liberal JoAnne Kloppenburg and the conservative Rebecca Bradley. (Wisconsin’s supreme court elections are non-partisan.) With the recent escalation of partisan rancor in the state, much of which has focused on Supreme Court decisions, the explanation for the turnout surge in 2016 could rest on the Supreme Court race, not the presidential primary.

The fact that 2016 is truly an outlier is reinforced when we generate predicted values from the two regressions conducted above. The accompanying graph shows the actual time series, along with the two sets of predicted values from the regressions above. The 2016 values are 12 points greater than either regression would have predicted. This is similar in magnitude to the other outlier, 2000, where turnout was 13 points below what the model predicted.

On the issue of state supreme court races providing a turbo-boost to turnout in Wisconsin in general: if it did in 2016, it was the first time ever, at least in the post-war era. When I add variables intended to gauge the presence of contested supreme court races to the regression models above, nothing comes close to statistical significance. For instance, not all years have a supreme court race on the ballot. Adding a variable to account for supreme court races on the ballot along with the presidential primary adds nothing to the explanatory power of the two regression models, nor does adding a variable measuring how closely contested the supreme court race was.

The question, then, is whether 2016 was a true outlier, as was 2000, or whether 2016 ushered in a new partisan era. If it did, then we would expect turnout in 2020 to be about 15 points above what was predicted in the two regressions above. That is, we would expect turnout to be in the range of 1.8 and 1.9 million voters, depending on which regression model above is preferred. My political scientist training makes me skeptical about declaring new eras based on a single election, and so I would not expect turnout in 2020 to be nearly this high. Of course, with the confusion surrounding the primary, we may not know what the “new normal” is until 2024.

A conclusion (of sorts)

As of this writing, 1.1 million absentee ballots have been returned for counting. This guarantees that turnout based on absentee ballots alone with be in the ballpark of the predictions from the two regression models reviewed here. We still don’t know what total turnout is, because municipal clerks have hewed closely to the U.S. District Court order not to release any election results until Monday evening.

The Milwaukee City clerk has reported that about 20,000 voters cast ballots in person, anticipating that around 80,000 absentee ballots would eventually be returned. If these percentages hold for the whole state, then we’d anticipate for turnout to be around 1.4 million. Of course, Milwaukee’s in-person voting on Election Day was seriously hampered by the closing of over 90% of its Election Day precincts. I would expect that Wisconsin overall will see something less than 80% of its ballots cast by mail. If so, then turnout will be well above 1.4 million.

Either way, it seems reasonable to expect at this point that turnout will exceed what we should have expected, given the recent history of primaries in the state. Some may say that we should have expected much greater turnout, given the nature of the supreme court race also on the ballot, but one (or two) data points is a thin reed to hang such expectations on.

In any event, the fact that Wisconsin will likely see a much larger turnout for an uncompetitive presidential primary in the midst of a frightening pandemic says a lot about the persistence of the state’s voters and election workers, as it also says a lot about the likely level of turnout in November, when the obstacles to getting to the polls will (one hopes) not be so great.

Epilogue:  The “Effective Number of Candidates” Measure

The “effective number of candidates” measure is analogous to the “effective number of parties” measure used in electoral studies to study the number of political parties in a system.  Essentially, the effective number of candidates measure gauges how many candidates were on the ballot, weighting each candidate by the number of votes each received.  If two candidates receive equal votes, the effective number of candidates is 2.0.  If one candidate receives 90% and the other 10%, the effective number of candidates is 1.2.  For the Democrats, the effective number of candidates was 1.5 when the incumbent Democrat was running for reelection, 1.8 when the seat was open, and 2.9 when a Republican was running for reelection.  For the Republicans, the effective number of candidates was 1.3 when the incumbent Republican was running for reelection, 2.0 when the seat was open, and 2.5 when the Democrat was running for reelection.

Seo-young Silvia Kim: The Benefits of In-Person Election Observation

Guest Blog by Seo-young Silvia Kim

Silvia Kim is a PhD candidate at Caltech, currently finishing her dissertation research on American Politics and Political Methodology. Silvia has been a key collaborator on the Monitoring the Election project. She’ll be starting her new position as an Assistant Professor in the Department of Government at American University in August 2020.

On Super Tuesday, I drove more than 170 miles alone in my tattered old car, zigzagging through both Los Angeles and Orange County for election observations, visiting nine vote centers from noon to 10pm. Usually our team policy is to go out in pairs, but this year I was determined to roam the new vote centers far and wide all day, so I volunteered to go alone.

I am a quantitative data analyst—that is to say, I revel in gathering and analyzing numbers. Qualitative research, which focuses on unquantifiable, non-numerical data, is usually not my turf and out of my interest. Yet ever since I jumped into the world of elections and election administration, I have been observing elections every primary and general Election Day. And I would never underestimate the importance of in-person observations in research.

The benefit of in-person observations are numerous. One gets to observe the election take place out in the open, the street-level bureaucrats and voters at their natural “habitat.” Once I arrive, I observe the exterior of the location, ask permission from the center lead to observe, stand still in a corner so that I do not get in the way of voter, and then observe for 10 to 30 minutes. When there is not much traffic at the center and there are no notable troubles, ten minutes could be enough. When there are long lines and apparent trouble at the location, sometimes even 30 minutes is not enough.

If time and place allow, I may also be able to chat with various vote center staff. This did not happen as much as in 2016 or 2018, as there was high turnout and the staff were busy. But during the early voting period, or in locations with less voters, or when a staff is biting into cold pizza slices, I get to ask questions about what is going on at the voting location. Are all check-in devices working properly? Did they receive all necessary equipment on time? Were communications with the Registrar smooth and readily available? Were there any particular spikes in provisional voting or voter information edits, and if so, why? In most cases, they are happy to provide answers, as I consolidate these into recommendations for the Registrar, as in the Los Angeles Vote Center Observation Report.

While these anecdotes may not necessarily be generalizable, they provide important intuition as to what to look for when numerical data actually arrives. For instance, I personally observed thousands of students milling in a line to vote, a vote center in Los Angeles County. Did the same happen in Orange County, where I did not get to see any college locations? When I analyzed the wait time data, as reported in our Orange County Vote Center Observation and Wait Time Report, I did indeed see long wait time at UCI, CSUF, and Chapman University’s data. Based on the intuition built from my observations, I can look for common patterns in the data more quickly. In other words, the qualitative analysis that I undertake provides direction and guidance.


With COVID-19, the administrators all around the United States are scrambling to prepare for the voting experience in the midst of a pandemic. It may not be possible to “observe” the election as I usually have. It will still be beneficial if alternatives can be implemented—for example, researchers talking directly to staff that have worked on the in-person voting locations via the phone. If not, we still hope that the intuition that we have gathered for Los Angeles and Orange County improve the voting experience of Southern California’s electorate in future elections.