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Williams, David, von Ende, Samantha, Shanahan, James
Summary:
This week on Through the Gates, host Jim Shanahan is joined by David C. Williams, the executive director of the Center for Constitutional Democracy and the John S. Hastings Professor of Law in the Maurer School of Law.
Williams has written widely on constitutional law and consults with constitutional reform movements around the world. Presently, he advises elements of the Burma democracy movement on the constitutional future of the country. In today's interview, he will share some of how that process works.
Later in the episode, student Samantha von Ende will share some of her own work with the Center for Constitutional Democracy. As a Ph.D. student, von Ende has worked extensively on gender-related issues of democracy in the United States and around the world.
Folklorist Jon Kay made this short documentary for the exhibition, "Willow Work: Viki Graber, Basketmaker." The exhibit explored the work of Viki Graber a willow basketmaker from Goshen, Indiana. Viki learned willow basket weaving at the age of twelve from her father, who was recognized by the National Endowment for the Arts as a 2009 National Heritage Fellow. Where once her family plied their talents to make utilitarian workbaskets, Viki makes baskets for collectors and to sell at art shows and galleries. While using the same tools and methods as her great-grandfather, Viki's keen sense of color and innovative designs have elevated her family's craft to a new aesthetic level. Sponsored by the Indiana University College of Arts and Sciences as part of their Fall 2015 Themester @Work: The Nature of Labor on a Changing Planet, the exhibition and the video were on display at the museum from August 18 through December 20, 2015.
A man receives a distress call from someone stuck on the side of a cliff. The man race across difficult terrain in his Jeep. The man rescues the person from cliff by using the winch on his Jeep.
The commercial shows which Jeeps were used in the movie "Hatari!". The commercial portrays the different Jeeps as actors that were cast for specific roles and worked with the movie stars John Wayne, Red Buttons, and Elsa Martinelli. The Jeeps are shown in several movie clips driving across Tanzanian and herding animals.
Wilson, T. Kelly, Shanahan, James, Cummings, Janae
Summary:
“I have yet to meet the person I can’t teach to draw,” T. Kelly Wilson tells Through the Gates host Jim Shanahan in this week’s episode. Wilson is an architect and director of the Indiana University Center for Art and Design in Columbus.
Wilson talks about the importance of drawing on creativity and invention. “When you go to draw and you look to perceive … the world becomes suddenly very strange and complex,” he said, adding that common notions of what you’re seeing change and modify when translating them to pictures.
This episode also introduces Janae Cummings, a new Through the Gates podcast host, who will also be featured in upcoming “Five Questions” segments featuring campus visitors and faculty, staff, students, friends and alums of IU.
COVID-19 is among the most salient issues in the world presently, and for many current executives, it is likely to be among the greatest challenges they will face. Upon entering the U.S. context, the disease was immediately subject to the process of affective polarization, with clear partisan splits forming around perceptions of its risks that did not relate to science. We explore whether firms’ preexisting political positioning affected how they voluntarily disclosed to their investors on a novel, affectively polarized issue by examining whether firms’ disclosure of COVID-19 risks covaries with their partisan political giving. Analyzing conference call and campaign contribution data for the S&P 500, we find a positive association between a firm’s contributions to Democrats and its disclosure of COVID-19 risks.
This presentation starts by discussing how COVID-19 has affected job markets worldwide, key questions, methods, and data sources used. I will then focus on the research my colleagues and I have conducted in the last year, paying most attention to the focal paper using Current Population Survey monthly data from the US. In that paper, we make several contributions to understanding the socio-demographic ramifications of the COVID-19 epidemic and policy responses on employment outcomes of subgroups in the U.S., benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanics, younger workers, and those with high school degrees and some college. Between April and May, all the demographic subgroups considered regained some employment. Reemployment in May was broadly proportional to the employment drop that occurred through April, except for Blacks. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Third, we show that the extent to which workers in various demographic groups sort (pre-COVID-19) into occupations and industries can explain a sizeable portion of the gender, race, and ethnic gaps in recent unemployment. However, there remain substantial unexplained differences in employment losses across groups. We also demonstrate the importance of tracking workers who report having a job but are absent from work, in addition to tracking employed and unemployed workers. We conclude with a discussion of policy priorities and future research needs implied by the disparities in labor market losses from the COVID-19 crisis that we identify.
G. Elliott Morris is a data journalist at The Economist and writes mostly about American politics and elections, usually by engaging in a close study of political science, political polling and demographic data. He is responsible for many of The Economist’s election forecasting models, including their 2020 US presidential election forecast.
Over the past couple of decades, technical models, both statistical, machine learning and combinations of these methods, for forecasting various forms of political conflict, including protest, violent substate conflict, and even coups, have become surprisingly common in policy and NGO communities, particularly in Europe, though not, curiously, in US academia. These methods, working with readily available, if noisy, open source data, use a number of familiar predictive analytical approaches such as logit models in the statistical realm and random forests in the machine learning, and consistently outperform human analysts. This talk will first review the current state of the field, with a particular emphasis on why current models work whereas prior to 2005 there was little consistent success with the problems, and then present some challenges that remain unresolved. The talk will assume familiarity with general social science quantitative approaches, but not with the details of specific technical approaches: lots of graphics, a couple tables, no equations.
Textual data are central to the social sciences. However, they often require several pre-processing steps before they can be utilized for statistical analyses. This workshop introduces a range of Python tools to clean, organize, and analyze textual data. It is intended for researchers who are new to working with textual data, but are familiar with Python or have completed the Introduction to Python workshop. Python is best learned hands-on. Python packages: nltk, fuzzywuzzy, re, glob, sklearn, pandas, numpy, matplotlib
