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The docket sheet of a court case contains a wealth of information about the progression of a case, the parties’ and judge’s decision-making along the way, and the case’s ultimate outcome that can be used in analytical applications. However, the unstructured text of the docket sheet and the terse and variable phrasing of docket entries require the development of new models to identify key entities to enable analysis at a systematic level. We developed a judge entity recognition language model and disambiguation pipeline for US District Court records. Our model can robustly identify mentions of judicial entities in free text (~99% F-1 Score) and outperforms general state-of-the-art language models by 13%. Our disambiguation pipeline is able to robustly identify both appointed and non-appointed judicial actors and correctly infer the type of appointment (~99% precision). Lastly, we show with a case study on in forma pauperis decision-making that there is substantial error (~30%) attributing decision outcomes to judicial actors if the free text of the docket is not used to make the identification and attribution.more » « less
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Basdere, Mehmet; Caniglia, Gabriel; Collar, Charles; Rozolis, Christian; Chiampas, George; Nishi, Michael; Smilowitz, Karen (, INFORMS journal on applied analytics)This paper describes Situational Awareness for Events (SAFE), a comprehensive data visualization system for mass-participation endurance events. Working in partnership with the Bank of America Chicago Marathon and the Chevron Houston Marathon, and their public safety partners, we developed SAFE to enhance logistics, medical preparedness, and response for mass-participation endurance events such as marathons. The system incorporates critical data into a user-friendly dashboard to serve as a centralized source of information during the events. SAFE uses historical and real-time data to provide pre-event and on-site analytics via descriptive, predictive, and prescriptive models. These models help race organizers and relevant stakeholders effectively manage and oversee all participants, monitor the dynamic location of race participants, and manage health and safety resources throughout the event. The system was deployed successfully at the Chicago Marathon (2014–2018), the Shamrock Shuffle (2014–2018), and the Houston Marathon (2016–2018.more » « less
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