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Donal Khosrowi
Universität Hannover
  1. Three Ways in Which Pandemic Models May Perform a Pandemic.Philippe Van Basshuysen, Lucie White, Donal Khosrowi & Mathias Frisch - 2021 - Erasmus Journal for Philosophy and Economics 14 (1):110-127.
    Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of economic models, often under the label ‘performativity’, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the Covid-19 pandemic. After identifying three ways in which a model by the Covid-19 Response Team at Imperial College London may have influenced scientific advice, policy, and individual responses, (...)
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    Getting Serious about Shared Features.Donal Khosrowi - 2020 - British Journal for the Philosophy of Science 71 (2):523-546.
    In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model–world relation, which is the relation in virtue of which successful models are successful. Weisberg’s main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg’s account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models’ epistemic success. I consider three potential ways of concretizing the (...)
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  3. Extrapolation of causal effects – hopes, assumptions, and the extrapolator’s circle.Donal Khosrowi - 2019 - Journal of Economic Methodology 26 (1):45-58.
    I consider recent strategies proposed by econometricians for extrapolating causal effects from experimental to target populations. I argue that these strategies fall prey to the extrapolator’s circle: they require so much knowledge about the target population that the causal effects to be extrapolated can be identified from information about the target alone. I then consider comparative process tracing as a potential remedy. Although specifically designed to evade the extrapolator’s circle, I argue that CPT is unlikely to facilitate extrapolation in typical (...)
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    Trade-offs between Epistemic and Moral Values in Evidence-Based Policy.Donal Khosrowi - 2016 - Economics and Philosophy (1):49-78.
    Proponents of evidence-based policy (EBP) call for public policy to be informed by high-quality evidence from randomized controlled trials. This methodological preference aims to promote several epistemic values, e.g. rigor, unbiasedness, precision, and the ability to obtain causal conclusions. I argue that there is a trade-off between these epistemic values and several non-epistemic, moral and political values. This is because the evidence afforded by preferred EBP methods is differentially useful for pursuing different moral and political values. I expand on how (...)
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  5. Evidence-Based Policy: The Tension Between the Epistemic and the Normative.Donal Khosrowi & Julian Reiss - 2019 - Critical Review: A Journal of Politics and Society 31 (2):179-197.
    Acceding to the demand that public policy should be based on “the best available evidence” can come at significant moral cost. Important policy questions cannot be addressed using “the best available evidence” as defined by the evidence-based policy paradigm; the paradigm can change the meaning of questions so that they can be addressed using the preferred kind of evidence; and important evidence that does not meet the standard defined by the paradigm can get ignored. We illustrate these problems in three (...)
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    What’s (successful) extrapolation?Donal Khosrowi - forthcoming - Tandf: Journal of Economic Methodology:1-13.
  7.  3
    Decentring the discoverer: how AI helps us rethink scientific discovery.Elinor Clark & Donal Khosrowi - 2022 - Synthese 200 (6):1-26.
    This paper investigates how intuitions about scientific discovery using artificial intelligence can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred: they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as (...)
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    When Experiments Need Models.Donal Khosrowi - 2021 - Philosophy of the Social Sciences 51 (4):400-424.
    This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is ar...
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