LEO 2019 Survey Papers for SPSA

The first paper, “The Problems of Minimal Support: Considerations for an Establishment Survey of Local Election Officials”, is co-authored by Jay Lee and Paul Gronke.

Here is the abstract (click https://blogs.reed.edu/earlyvoting/spsa_sampling_paper/ to view the full paper).

In this paper, we provide evidence to support the use of a specific sampling algorithm for drawing random samples of local election officials (LEOs) in the United States, using the sampling package in the R statistical package. The paper is part of a larger project that examines the backgrounds, professional orientations, and opinions of LEOs in order to better characterize their role as “stewards of democracy.” The enormous diversity of local jurisdictions and the hyperfederalized institutional structure of American elections combine to create methodological challenges to drawing a random sample that allows generalizations both about LEOs and also about the American voting experience. The paper explores the statistical foundations of a number of unequal inclusion probability sampling methods implemented in the sampling package. We show using simulations that the extremely skewed distribution of jurisdictions (by population size) causes anomalies in the sampling method, resulting in overly variant samples and extreme values for sampling weight when using the minimal support sampling algorithn. We further show that the “random systematic” sampling method is superior, resulting in lower variance estimates, and is just as easy to implement as “minimal support”.

The second paper, “Staffing the Stewards of Democracy: the Demographic and Professional Profile of America’s Local Election Officials”, is co-authored by Paul Manson, Natalie Adona, and Paul Gronke.

Here is the abstract (click https://blogs.reed.edu/earlyvoting/staffing-the-stewards/ to view the full paper):

Drawing on the results of two national surveys of local election officials (LEOs) in 2018 and 2019, we explore the demographic and professional profile of America’s “stewards of democracy” and compare our data to other surveys of the local bureaucracy and civil service. Our demographic findings are consistent with prior surveys of LEOs, in which we find that the typical LEO in the United States is female, white, over 55, and earns just over $50,000 a year. We are interested in comparing the demographic profile of the typical LEO to other local officials and government employees. We want to understand if there is something unique about election administration that leads females to advance to leadership positions, and in many cases, choose to run for office, in order serve as the local official administer- ing elections and supporting our democratic system. We compare our results with employment data from the Equal Employment Opportunity Commission (EEOC) and the U.S. Bureau of Labor Statistics (BLS) as a first step into answering these questions as well as exploring larger questions of representative bureaucracy. We also offer a first look at LEO job satisfaction and data that provide a glimpse into how people enter into the profession of election administration.

538.com Story on AVR and Turnout Quotes EVIC Director

There’s a good story at 538.com by Nathaniel Rakich on the turnout effects of automatic voter registration. He does a good job identifying the boundaries of the potential effects, and is sensitive to the difficult problem of identifying the counter-factual.

Gronke quote about behavioral economics and opt-in / opt-out implementation:

And then there’s the behavioral economics of it all. Reed College professor Paul Gronke told FiveThirtyEight that social science research has generally found that an opt-out system (like AVR) is more effective than an opt-in one (like having to actively register yourself).

The research continues!

Early Voting and the Iowa Caucus: Can They Coexist? Early Voting and the Iowa Caucus: Can They Coexist?

A great article in Salon by the always insightful Steven Rosenfeld illustrates the difficulties of implementing national party mandates for a fully inclusive primary system while retaining the unique in-person and face to face features of the Iowa caucus.

The immediate takeaway from the article is that the phone-based system for “virtual voting” that was proposed in Iowa and Nevada has severe security risks, and it’s been abandoned. The bigger question, it seems to me, is whether or not requiring absentee (and presumably early) voting in Iowa will fundamentally alter the dynamics of this contest, with reverberations down the line in our sequential nominating process.

In Why Iowa, Professors David Redlawsk, Caroline Tolbert, and Todd Donovan provide a full-throated defense of Iowa’s first in the nation caucus. Two parts of their argument are distinct from caucus rules–they defend a sequential process and Iowa’s position in that process.

The bulk of the book, however, focuses on the caucus itself, and how the caucus rules; public learning, information, deliberation and participation levels; and media coverage are unique to the caucus.

From an election administration and electoral process perspective, it’s not clear to me that a requirement for some kind of “absentee voting” can be squared with the caucus as it is currently designed.

It seems to me–and Dave, Caroline, and Todd will surely correct me if I’m wrong–that their argument about the merits of the Iowa caucus is largely one driven by locality and place. You need to be in Iowa, experiencing the candidate visits, canvassing, media scrutiny, and engaging in conversations with your fellow citizens. We may cynically dismiss the role of face to face politics in this day and age, but their results show that face to face politics really matters in Iowa.

How can one participate in a caucus if the ballot is cast by phone or over the internet, weeks before the event? Isn’t this fundamentally a different kind of voting?

We might have had an answer in 2020 (yay research!) but for now, virtual voting in Iowa looks like it’s not in the cards.

Reporting Results from the 2018 DF/RC LEO Survey: The "Bin" Question Reporting Results from the 2018 DF/RC LEO Survey: The “Bin” Question

We are nearing a final release of the 2018 Democracy Fund / Reed College Local Election Official survey. Our current discussion is all about the “bins”. In other words, what is the best way to categorize local election officials, and by implication local election jurisdictions, so as to provide some meaningful categories for comparison but not lump together very disparate locations.

There’s no magic formula for making this choice, as David Kimball and Brady Baybeck showed so effectively in the 2013 Election Law Journal article,”Are All Jurisdictions Equal? Size Disparity in Election Administration.” As of 2008, Kimball and Baybeck showed how the population of local election officials is dominated by small jurisdictions, yet the majority of registered voters live in larger jurisdictions (see Figures 1 and 2, reproduced from their article).

Kimball and Baybeck chose to report their results by “small”, “medium”, and “large” as shown in the figures, because they argued these categories reflected fundamental distinctions in the nature of election administration:

To simplify some of the analyses that follow, we divide the universe of local jurisdictions into three size categories: small (serving less than 1,000 voters), medium (serving between 1,000 and 50,000 voters), and large jurisdictions (serving more than 50,000 voters). We chose 1,000 voters as one divid- ing line because jurisdictions with fewer than 1,000 voters are generally small towns that have no more than a couple of polling places and a handful of poll workers. We expect these jurisdictions to have a different election administration experience than larger jurisdictions. In addition, roughly one-third of the jurisdictions served less than 1,000 voters in recent presidential elections, so this serves as a natural break in the data.

We chose 50,000 voters as the other dividing line because jurisdictions serving more than 50,000 vot- ers tend to be in densely populated metropolitan areas with a large central city. Thus, the largest jurisdictions have different infrastructure and transportation networks than the medium-sized jurisdictions, which are mostly rural and exurban counties. Together, these dimensions characterize what we define as small, medium, and large jurisdictions in a variety of analyses below. The smallest jurisdictions are primarily in the upper Midwest and New England, with a smaller number in the Plains. Large jurisdictions are concentrated in the major metropolitan centers of the United States.

Our 2018 distributions look quite similar to what David and Brady found. Below, we’ve reproduced histograms displays of jurisdictions, first counties and then townships, by populations of registered voters. Most notable is how very many local election officials serve in townships in the United States (predominantly in Michigan, Wisconsin, and in New England) yet how very few (comparatively) voters there are in those jurisdictions (note that we have excluded jurisdictions that serve 100,000 or more registered voters, for the purposes of making the display readable–those jurisdictions administer elections for 35% of all registered voters).


While the final report is not yet complete (coming attractions!), we have tentatively decided to split the difference, in hopefully what is an instructive and not Solomonic division.

We will report our results in these bins:

  1. 0-5,000 registered voters. These jurisdictions comprise 25% of our LEO respondents and 2.9% of registered voters
  2. 5,001 – 25,000 registered voters. These jurisdictions comprise 30%of our respondents and serve 12.7% of registered voters.
  3. 25,001 – 100,000 registered voters. 30% of respondents and 18.5% of voters
  4. 100,001 – largest. 15% of responses and 66.9% of voters.

The discerning reader will notice that the last category covers a lot of voters. This is unavoidable, because this category includes not very many LEOs, relatively speaking, and our survey guarantees confidentiality to our respondents. We can report some results with the final bin broken into two smaller bins, but we must honor the commitment we made to our respondents.

This is the reality of American election administration. It’s a classic case where diversity and decentralization are both a source of strength but also can create inequities in funding and voter access.

How Geospatial Mapping Can Improve Election Audits How Geospatial Mapping Can Improve Election Audits

Today’s electionline story describes 25 houses in Hamden, CT that have been incorrectly assigned to election districts since the last redistricting cycle in 2011, and have been the wrong ballots. There are charges that voters have been “disenfranchised” though it’s unclear whether the ballots were counted for the “wrong” race, or only some races were counted.

The process obviously needs to be investigated, and Secretary of State Denise Merrill is calling not just for a detailed investigation of Hamden’s procedures, but a statewide audit when it became clear that there were additional districting errors, including candidates who were elected in districts where they were not residents.

There are a lot of moving parts here and a quick scan of the various stories show an early tendency on the part of journalists to move quickly to use a partisan lens. It appears to be more an accident of unfortunate events that a Democratic registrar in Hamden has been on medical leave during the election, leaving a single person in charge, who happened to be a Republican, and the district was won by a Republican in a relatively close race (though one where the winning margin of 77 votes exceeded the number of voters who were misassigned).

While we will all need to wait to see the outcome of the audit, election scientists have been aware of this mis-mapping problem for a while because of a series of presentations that Dr. Michael McDonald and Dr. Brian Amos have given at our recent conferences.  McDonald and Amos show that mis-assignments are seldom intentional, and most often result from out of date shape files (the geo-spatial files that are used to assign geolocations to larger geographical entities, such as election precincts and districts) and mis-alignments between “street files” (the lists that jurisdictions use to match street addresses to precincts / districts) and the actual geographic boundaries of the district.

There are illustrative examples of these mis-assignments in the paper that McDonald and Amos presented at a the MIT Election Data and Sciences Lab “Election Audits Summit” in December.

I urge interested readers to follow this link to learn more about the great work being done by McDonald and Amos, and how their technology can help to improve election accuracy.