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  1.  7
    Algorithms as Folding: Reframing the Analytical Focus.Robin Williams, Claes-Fredrik Helgesson, Lukas Engelmann, Jeffrey Christensen, Jess Bier & Francis Lee - 2019 - Big Data and Society 6 (2).
    This article proposes an analytical approach to algorithms that stresses operations of folding. The aim of this approach is to broaden the common analytical focus on algorithms as biased and opaque black boxes, and to instead highlight the many relations that algorithms are interwoven with. Our proposed approach thus highlights how algorithms fold heterogeneous things: data, methods and objects with multiple ethical and political effects. We exemplify the utility of our approach by proposing three specific operations of folding—proximation, universalisation and (...)
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  2.  14
    Is There a Duty to Participate in Digital Epidemiology?Brent Mittelstadt, Justus Benzler, Lukas Engelmann, Barbara Prainsack & Effy Vayena - 2018 - Life Sciences, Society and Policy 14 (1):1-24.
    This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first describe traditional justifications for epidemiology that imply a duty to participate for the general public, which take account of the immediacy and plausibility of threats, and the identifiability of (...)
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  3.  2
    Digital Epidemiology, Deep Phenotyping and the Enduring Fantasy of Pathological Omniscience.Lukas Engelmann - 2022 - Big Data and Society 9 (1).
    Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, this (...)
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  4.  8
    Stefanos Geroulanos, Todd Meyers,Experimente im Individuum. Kurt Goldstein und die Frage des Organismus, Köln: August Verlag 2014.Lukas Engelmann - 2015 - Berichte Zur Wissenschaftsgeschichte 38 (1):98-100.
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  5.  1
    A Box, a Trough and Marbles: How the Reed-Frost Epidemic Theory Shaped Epidemiological Reasoning in the 20th Century.Lukas Engelmann - 2021 - History and Philosophy of the Life Sciences 43 (3):1-24.
    The article takes the renewed popularity and interest in epidemiological modelling for Covid-19 as a point of departure to ask how modelling has historically shaped epidemiological reasoning. The focus lies on a particular model, developed in the late 1920s through a collaboration of the former field-epidemiologists and medical officer, Wade Hampton Frost, and the biostatistician and population ecologist Lowell Reed. Other than former approaches to epidemic theory in mathematical formula, the Reed-Frost epidemic theory was materialised in a simple mechanical analogue: (...)
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