So the U.S. Energy Information Administration (EIA), a part of the Department of Energy that collects and distributes data on energy and the economy, recruited Baumeister to develop an indicator for future energy demand.��

With a two-year, $120,000 grant, she’ll collect data on possible determinants of oil demand and create models to figure out which of those factors actually determine future demand. Having that information, she said, tells us about more than just oil.��

“Energy is one basic resource on which our economy thrives,” Baumeister said. “We need energy for any type of economic activity, for daily life. It’s a big factor in how well the economy is doing.” 

Baumeister, who , has studied energy markets and prices throughout her career. She specialized in oil markets as a principal researcher in the Bank of Canada’s International Economic Analysis Department, and she has collaborated with the EIA on studying oil prices.��

Previous work on oil price fluctuations, Baumeister said, relied on conventional indicators — dry cargo freight rates, prices of industrial commodities, or steel production — to determine demand.��

“The shortcoming of all these indicators is that they might be too narrow in scope since they are all based on a single category of variables,” she said. “The question my project tries to answer is whether we can improve upon existing indicators by combining information from a variety of data types. The goal is to be more comprehensive and consider all possible determinants of energy demand together in order to develop a novel indicator.” 

With the help of a research assistant, Baumeister will start with an extensive data search, collecting as much information from existing databases as she can on factors such as energy consumption, inventory buildup, stock prices of industries related to energy production, order books, and prices for other commodities.��

“Then, we’ll evaluate them based on past observations — how successful such an indicator has been in forecasting these variables — and then extrapolate that to the future,” she said.��

The EIA can then use Baumeister’s indicator in its short-term energy outlooks, giving policymakers and the public crucial insights into energy demand, efficiency and independence.��

“It’s a way of advising policymakers what course of action to take to ensure that supply and demand match,” she said.��

To develop this new indicator, Baumeister will also have the support and collaboration of economists and industry experts at the EIA.��

“It’s nice to work with people who are really on top of things in this field and have the exposure and contacts in the industry,” she said. “It’s great that they approached me and thought I was the right person for the job.”

Originally published by Emily McConville at on January 30, 2018.

Associate Professor of English is fascinated by the use of geography in literature over time. How, for example, did the Civil War affect the importance of certain places in American literature, and what can literature tells us about Americans’ sense of place?

The answer can be found in books written during that period — potentially thousands of them, many more than Wilkens could ever read and analyze himself.��

To consider the widest possible range of literary production, Wilkens turned to computation. He was recently awarded a $325,000 from the National Endowment for the Humanities to bolster Textual Geographies, a database and suite of tools he is developing that allow users to find, map and analyze more than 14 billion place name mentions from books and journals in English, Spanish, German and Chinese.  

“I’m very pleased to receive this grant,” he said. “It’s nice to be able to bring new partners into the project and to have the funds and resources to work with — things that would be much more difficult to do without that financial backing.”

This map of London, showing locations mentioned in British fiction published between 1880 and 1940, shows one potential use of Textual Geographies.

Textual Geographies draws its data from , a digital database of more than 100 institutions’ library holdings, many of which were originally scanned for Google Books. In 2014, with support from, Wilkens mined HathiTrust’s public domain texts — about 4 million volumes published before 1923 — for place name mentions.��

With the NEH grant, Wilkens is able to expand the project. Significantly, he’ll add an additional 6 million in-copyright volumes to the database. Collaborating with postdoctoral fellow Dan Sinykin and the Notre Dame , he’s also developing tools that make the terabytes of data accessible to scholars who don’t have backgrounds in programming or data analysis.

“They can quickly say, ‘show me how many mentions there are of locations in France in the following kinds of books written by women between 1940 and 1970, and compare that to the same demographic after 1970,” Wilkens said. “It’s an impossible question to answer by conventional means.” 

A map of U.S. states that were underrepresented in literature relative to their population around the time of the Civil War.

Charting changes in place name mentions across literary production can give scholars an even better picture of changes in culture over time — Wilkens is using the database to research a book on the literary geography of the United States, among other projects.��

He’s already used large-scale analysis to provide new insight on American literature after the Civil War. In a study of place name mentions in books published between 1851 to 1875, Wilkens found that literary interest in certain places didn’t change after the war as quickly as previously thought.��

“In the evidence we saw that America as a unified entity certainly didn’t emerge as quickly or as straightforwardly as that story might have led us to believe,” he said.��

Textual Geographies adds a new tool to a growing field within literary studies, of which Wilkens is a notable leader. He is also the president of the Digital Americanists Society and a co-investigator on “Text Mining the Novel,” a project that aims to understand the novel’s place in society through quantitative methods.��

This graph, developed with Textual Geographies, illustrates the lag time between changes in U.S. city populations and corresponding changes in literary usage rates. In other words, if a lot of people move west, how long does it take for authors to start writing about western locations en masse? In this case, about 30 years.

Those methods have become all the more important over the past few generations, as literature is increasingly thought of as “socially symptomatic,” Wilkens said.��

“If we say, ‘What does the fact that this book existed with these features, in this form, tell us about the culture that produced it,’ the obvious followup to that is, ‘What about all the books?’” Wilkens said.��

Combining computational analysis with traditional literary analysis, Wilkens said, allows scholars to more fully understand how literature reflects — or influences — the time and place in which it was published and the people who read it.��

“Those two kinds of evidence potentially play together really well, the kind of evidence that we get from close reading and literary hermeneutics coupled with this large scale, trend-based evidence,” Wilkens said. “I try to use both kinds of evidence in my own work. I think a lot of the best computational and quantitative work in the humanities likewise uses both.”

Originally published by Emily McConville at on December 01, 2017.

believed that conventional wisdom needed to be challenged.

In her book, ","��the Notre Dame professor of political science and her co-author, Western Michigan University political scientist J. Kevin Corder, investigated and often upended long-held assumptions about women’s suffrage and offered new insight into the largest expansion of the electorate in American history.

Their efforts earned them the American Political Science Association’s for the best book on women and politics published in the past year.

“People assume they know how the first women voted, but when you actually look at what they’re basing that on, it’s often literally just people saying, ‘Well, this is what I think happened,’” said Wolbrecht, who is also the director of the and the C. Robert and Margaret Hanley Family Director of the .

It is said, for example, that women simply did not turn out to vote, that they tended to vote for progressive candidates, and that they were not a significant factor in the electorate’s shift to the Democratic party in the 1930s. These myths persisted in part because women’s voting habits in the first few elections after 1920 went largely uninvestigated due to the poor availability of election data and surveys from the time.

To get around this problem, Wolbrecht and Corder employed a relatively new statistical approach to what is known as ecological inference. It involves gathering demographic data from small units, such as counties or townships in a state, as well as data on how many people voted for each party — or didn’t vote at all — in those same units, then combining those sets of data to infer how women voted on average in the state as a whole.

Wolbrecht and Corder used the method to determine how women voted in 10 states over five elections. To bolster their arguments, they had one source that could serve as a comparison — Illinois actually used different ballots for men and women in the 1916 and 1920 elections, meaning the authors could compare the results from their method to actual data.

“If you think of a poll as having an error of about 3 percentage points on either side of it, that’s how close we got,” Wolbrecht said.

They found that where women lived was a huge determinate of how they voted. Instead of voting primarily for progressive candidates, women tended to be disproportionately loyal to the dominant party in their state.

“Women who lived in Democratic states were even more likely to vote Democratic than men, and women who lived in states that were really Republican were even more likely to vote for the Republican Party,” Wolbrecht said.

How many women voted also varied from state to state. Women generally voted at lower rates than men, but turnout was particularly low in states dominated by one party or the other — or in states, such as Virginia, with restrictive voting laws such as literacy tests or poll taxes.

In more competitive states without such laws, such as Kentucky and Missouri in 1920, women boasted higher turnout.

“Parties and candidates likely put a lot of effort into turning people out to vote,” Wolbrecht said.

In the 1930s, Franklin Roosevelt’s promise of a New Deal won the Democratic Party millions of new votes. Women played a disproportionate role in the shift, switching parties at a higher rate than men.

“Of all the new votes that Democrats gained because of Franklin Roosevelt, about half of them came from women,” she said.

Wolbrecht said she hopes the book adds a new perspective to discussions about how women did or did not shape American elections. Winning the Victoria Schuck Award, she said, is a recognition that those discussions are important.

“There is lots of really exciting and great work being done on questions about gender and politics in political science that is inspiring and interesting to me, and to be chosen for this award is a huge honor,” Wolbrecht said.

Originally published by Emily McConville at on September 01, 2017.

The University unveiled this week the 2016 collection of Notre Dame Family Wines.

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