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        "event_title":"Imagine Doing Better: Actions to Make a Better World Possible",
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        "combined_title":"Imagine Doing Better: Actions to Make a Better World Possible: Dr. Paul Fleming",
        "event_subtitle":"Dr. Paul Fleming",
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        "description":"In this interactive presentation, Dr. Paul Fleming will discuss how to think about and approach creating communities where all people can thrive. In his work, he partners with community-based organizations and community organizers to help bring equity and anti-racism principles into practice.  Dr. Fleming will highlight key themes from his book Imagine Doing Better: Why policies backfire and how prevention thinking can change everything, which will help participants reflect on the status quo, imagine better futures, and learn strategies for being a changemaker to create a new future in their communities and the world.  \n\nDr. Fleming is an Associate Professor at the University of Michigan's School of Public Health and co-founder of the Collaborative for Transformative Public Health. His research and teaching focus on the root causes of racial health inequities and strategies to address them. He is a sought-after thought leader on how to advance health equity and create communities and organizations that enable all people to thrive.\n\n*The Osher Lifelong Learning Institute (OLLI) at U-M provides educational opportunities for older adults, designed by older adults. Membership is intended for all enthusiastic learners aged 50 and older, regardless of previous education or affiliation with U-M. *",
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        "room":"Pond Room (ML 150)",
        "location_name":"Washtenaw Community College Morris Lawrence Building",
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        "cost":"$15 Members| $25 non-members",
        "tags":["Lifelong Learning","Inclusion","Leadership","Lecture","Public Health","Social Justice","Talk","Activism","aging","Education","Geriatrics","In Person"],
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        "event_title":"Beyond Rankings: Bayesian Learning of Parity, Tiers, and Dynamic Regimes",
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        "combined_title":"Beyond Rankings: Bayesian Learning of Parity, Tiers, and Dynamic Regimes: Guanyu Hu",
        "event_subtitle":"Guanyu Hu",
        "event_type":"Workshop \/ Seminar",
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        "description":"Rankings are widely used to summarize comparative information, but they can suggest differences that the data do not strongly support. In paired-comparison data, two competitors may receive different ranks even when their underlying abilities are very similar. This raises a fundamental statistical question: when should competitors be ranked separately, and when should they be regarded as statistically tied?\n\nIn this talk, I will present a Bayesian framework for learning rank structure and competitive balance directly from paired-comparison data. A geometric constraint on latent abilities controls the extent of ability differences and allows rank tiers to emerge naturally when competitors are not meaningfully distinguishable. I will then extend the framework to longitudinal data using a hidden Markov model, allowing competitive balance and rank structure to change across persistent historical regimes.\n\nI will discuss the statistical formulation, computation, and theoretical properties of the model, and illustrate the approach with applications to the National Basketball Association and the English Premier League. These applications show how the framework can identify changes in competitive balance, recover meaningful rank tiers, and quantify uncertainty in rankings. More broadly, the framework provides a way to ask not only who ranks higher, but how much separation the data actually support.\n\n*Department reception in 450 West Hall after the seminar at 11:00 AM*",
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