For better or worse, one of the biggest stories in US politics today is the detection of election fraud, or in many cases the lack of election fraud. But determining whether fraud happened in an election can be difficult, even while proving the validity of elections for some has become increasingly important. Wouldn’t it be incredible if we could just plug a set of data from an election into a toolkit that could give us an answer if fraud occurred?

Well, one political scientist from the University of Michigan, Walter Mebane believes he may have developed just such a toolkit. It’s called “election forensics”. Much like machine learning algorithms, when tested in the field it does seem to perform fantastically well, but figuring out exactly how it works can be a complicated web to untangle. We give it a shot on this episode.

An Algorithm for Detecting Election Fraud

With all the noise created by a 24/7 news cycle, it can be hard to really grasp what's going on in politics today. We provide a fresh perspective on the biggest political stories not through opinion and anecdotes, but rigorous scholarship, massive data sets and a deep knowledge of theory. Understand the political science beyond the headlines with Harris School of Public Policy Professors William Howell, Anthony Fowler and Wioletta Dziuda. Our show is part of the University of Chicago Podcast Network.

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The Supreme Court is supposed to be our non-political branch of government, making decisions solely on the constitutional soundness of laws. But in recent years it appears as though the Court has taken a shift to the right, most notably in the Dobbs decision in 2022. Which raises a question: does the public still the view the Court as legitimate?

Those are the questions explored in a new paper from UPenn political scientist Matthew Levendusky in a paper titled “Has the Supreme Court become just another political branch? Public perceptions of court approval and legitimacy in a post-Dobbs world”.

Does The Public View The Supreme Court As Legitimate In A Post-Dobbs World ?

If the media is to be believed, the US public has a tenuous at best grasp on accurate political news. They’re either consuming disinformation and fake news on social media or following biasedly inaccurate news outlets. Either journalistic truth is as good as dead or we’re living in separate informational universes. But is this too alarmist, could the real story be more nuanced?

That’s what Columbia professor of economics Andrea Prat finds in his recent paper “Is Journalistic Truth Dead? Measuring How Informed Voters Are About Political News”. But what are we to make of these results, and how do we square them with claims of political polarization?

How Good Are We At Spotting Fake News?

There is a fact of our political discourse so agreed upon that nobody thinks to question it: affective polarization…democrats and republicans disliking each other...has been getting worse, much worse. But what if that belief is actually based on polls measuring the wrong thing?

That’s the argument made by Northwestern Political Scientist James Druckman in his paper “What Do We Measure When We Measure Affective Polarization?”

Is Partisan Animosity Directed At Fellow Citizens Or Elites?

How do we know if our democracy is healthy? For political scientist, the answer often comes down to things we can measure like responsiveness to voter’s wishes. But is that really the right thing to measure?

There are two camps in this debate. The empiricists want to focus on what and how we can measure things like the health of our democracy, often focusing on indicators like responsiveness, while the normative theorists want to focus on what we even mean…and what we should mean…by democratic health.

If you’ve listened to our show before, you can probably guess that we fall more into the empiricists camp, but we wanted to bring on someone who could challenge our assumptions.

Andrew Sabl is a political scientist from the University of Toronto and the author of “The Two Cultures of Democratic Theory: Responsiveness, Democratic Quality, and the Empirical-Normative Divide” in which he argues that the empiricists need to pay more attention to what they’re measuring and why.

Should Policy Match Voters' Preferences?

When it comes to our federal bureaucracy, there are two schools of thought. One says that an insulated group of career bureaucrats have created a deep state that corrupts the performance of government. The other says that our bureaucracy is dysfunctional because there is too much turnover or positions left vacant. Both rest on an underlying feature of our democracy: many of the positions in the federal bureaucracy are appointed by the President and approved by Congress. But, could having less politically selected appointments give us a more functional government?

In this episode, we’re doing things a bit different. The Center for Effective Government at the University of Chicago, headed by our very own William Howell, has developed a series of primers that each focus on the available scholarship about the pros and cons of a particular governmental reform. Each primer is written by a scholar who has also done research in that area. On this episode, we speak with David Lewis from Vanderbilt University who wrote a primer on this question: should we have more politically appointed bureaucrats or less?

An Algorithm for Detecting Election Fraud

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