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Statistically Valid Inferences from Privacy Protected Data (Microsoft) Thursday, November 21, 2019:
Slides
Unprecedented quantities of data that could help social scientists understand and ameliorate the challenges of human society are presently locked away inside companies, governments, and other organizations, in part because of worries about privacy violations. We address this problem with a general-purpose data access and analysis system with mathematical guarantees of privacy for individuals who may be represented in the data, statistical guarantees for researchers seeking insights from it, and protection for society from some fallacious scientific conclusions. We build on the standard of ``... Read more about Statistically Valid Inferences from Privacy Protected Data (Microsoft)
Statistically Valid Inferences from Privacy Protected Data (University of Chicago) Friday, November 8, 2019:
Slides
The vast majority of data that could help social scientists understand and ameliorate the challenges of human society is presently locked away inside companies, in part because of worries about privacy violations. We address this problem with a general-purpose data access and analysis system with mathematical guarantees of privacy for individuals who may be represented in the data, statistical guarantees for researchers seeking insights from it, and protection for society from some fallacious scientific conclusions. We build on the standard of ``differential privacy'' but, unlike most such... Read more about Statistically Valid Inferences from Privacy Protected Data (University of Chicago)
How to Measure Legislative District Compactness If You Only Know it When You See it (University of Chicago) Thursday, November 7, 2019:
Slides

To deter gerrymandering, many state constitutions require legislative districts to be "compact." Yet, the law offers few precise definitions other than "you know it when you see it," which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct -- that compactness is complex and multidimensional, but a common understanding exists across people. We develop a survey to elicit this understanding, with high reliability (in data where...

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Simplifying Matching Methods for Causal Inference (University of Minho) Tuesday, October 22, 2019:
Slides
We show how to use matching methods for causal inference to ameliorate model dependence -- where small, indefensible changes in model specification have large impacts on our conclusions. We introduce methods that are simpler, more powerful, and easier to understand than existing approaches. We also show that propensity score matching, an enormously popular approach, often accomplishes the opposite of its intended goal -- increasing imbalance, inefficiency, model dependence, and bias -- and should be replaced with other matching methods in applications.  See ... Read more about Simplifying Matching Methods for Causal Inference (University of Minho)
How the news media activate public expression and influence national agendas (University of Minho) Monday, October 21, 2019:
Slides
This talk reports on the results of first large scale randomized news media experiment. We demonstrate that even small news media outlets can cause large numbers of Americans to take public stands on specific issues, join national policy conversations, and express themselves publicly—all key components of democratic politics—more often than they would otherwise. After recruiting 48 mostly small media outlets, and working with them over 5 years, we chose groups of these outlets to write and publish articles on subjects we approved, on dates we randomly assigned. We estimate the... Read more about How the news media activate public expression and influence national agendas (University of Minho)
Simplifying Matching Methods for Causal Inference Thursday, October 10, 2019:
Slides
We show how to use matching methods for causal inference to ameliorate model dependence -- where small, indefensible changes in model specification have large impacts on our conclusions. We introduce methods that are simpler, more powerful, and easier to understand than existing approaches. We also show that propensity score matching, an enormously popular approach, often accomplishes the opposite of its intended goal -- increasing imbalance, inefficiency, model dependence, and bias -- and should be replaced with other matching methods in applications.  See ... Read more about Simplifying Matching Methods for Causal Inference
How to Measure Legislative District Compactness If You Only Know it When You See it, at University of Minnesota, Thursday, September 12, 2019:
Slides

To deter gerrymandering, many state constitutions require legislative districts to be "compact." Yet, the law offers few precise definitions other than "you know it when you see it," which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct -- that compactness is complex and multidimensional, but a common understanding exists across people. We develop a survey to elicit this understanding, with high reliability (in data where...

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How to Measure Legislative District Compactness If You Only Know it When You See it, at University of Michigan, Statistical Learning Workshop, Thursday, April 18, 2019:
Slides
To deter gerrymandering, many state constitutions require legislative districts to be "compact." Yet, the law offers few precise definitions other than "you know it when you see it," which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct -- that compactness is complex and multidimensional, but a common understanding exists across people. We develop a survey to elicit this understanding, with high reliability (in data where the... Read more about How to Measure Legislative District Compactness If You Only Know it When You See it
How to Measure Legislative District Compactness If You Only Know it When You See it, at University of Pittsburgh, Center for Research Computing, Friday, March 8, 2019:
Slides.pdf
To deter gerrymandering, many state constitutions require legislative districts to be "compact." Yet, the law offers few precise definitions other than "you know it when you see it," which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct -- that compactness is complex and multidimensional, but a common understanding exists across people. We develop a survey to elicit this understanding, with high reliability (in data where the... Read more about How to Measure Legislative District Compactness If You Only Know it When You See it
How to Measure Legislative District Compactness If You Only Know it When You See It, at Nuffield College, Oxford University, Thursday, February 14, 2019:
Slides

To deter gerrymandering, many US state constitutions require legislative districts to be geographically "compact" (and a similar requirement holds explicitly or implicitly for numerous political jurisdictions around the world). Yet, the law offers few precise definitions other than "you know it when you see it," which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct -- that compactness is complex and multidimensional, but...

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