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David McCarthy
University of Hong Kong
  1. Probability in Ethics.David McCarthy - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Philosophy and Probability. Oxford University Press. pp. 705–737.
    The article is a plea for ethicists to regard probability as one of their most important concerns. It outlines a series of topics of central importance in ethical theory in which probability is implicated, often in a surprisingly deep way, and lists a number of open problems. Topics covered include: interpretations of probability in ethical contexts; the evaluative and normative significance of risk or uncertainty; uses and abuses of expected utility theory; veils of ignorance; Harsanyi’s aggregation theorem; population size problems; (...)
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  2. The Priority View.David McCarthy - 2017 - Economics and Philosophy 33 (2):215–57.
    According to the priority view, or prioritarianism, it matters more to benefit people the worse off they are. But how exactly should the priority view be defined? This article argues for a highly general characterization which essentially involves risk, but makes no use of evaluative measurements or the expected utility axioms. A representation theorem is provided, and when further assumptions are added, common accounts of the priority view are recovered. A defense of the key idea behind the priority view, the (...)
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  3.  51
    Utilitarianism with and Without Expected Utility.David McCarthy, Kalle Mikkola & Teruji Thomas - 2016 - MPRA Paper No. 79315.
    We give two social aggregation theorems under conditions of risk, one for constant population cases, the other an extension to variable populations. Intra and interpersonal comparisons are encoded in a single `individual preorder'. The individual preorder then uniquely determines the social preorder. The theorems have features that may be considered characteristic of Harsanyi-style utilitarianism, such as indifference to ex ante and ex post equality. If in addition the individual preorder satisfi es expected utility, the social preorder must be represented by (...)
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  4.  32
    Aggregation for General Populations Without Continuity or Completeness.David McCarthy, Kalle Mikkola & Teruji Thomas - 2017 - MPRA Paper No. 80820.
    We generalize Harsanyi's social aggregation theorem. We allow the population to be infi nite, and merely assume that individual and social preferences are given by strongly independent preorders on a convex set of arbitrary dimension. Thus we assume neither completeness nor any form of continuity. Under Pareto indifference, the conclusion of Harsanyi's theorem nevertheless holds almost entirely unchanged when utility values are taken to be vectors in a product of lexicographic function spaces. The addition of weak or strong Pareto has (...)
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  5.  31
    Continuity and Completeness of Strongly Independent Preorders.David McCarthy & Kalle Mikkola - 2018 - Mathematical Social Sciences 93:141-145.
    A strongly independent preorder on a possibly in finite dimensional convex set that satisfi es two of the following conditions must satisfy the third: (i) the Archimedean continuity condition; (ii) mixture continuity; and (iii) comparability under the preorder is an equivalence relation. In addition, if the preorder is nontrivial (has nonempty asymmetric part) and satisfi es two of the following conditions, it must satisfy the third: (i') a modest strengthening of the Archimedean condition; (ii') mixture continuity; and (iii') completeness. Applications (...)
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  6.  30
    Representation of Strongly Independent Preorders by Sets of Scalar-Valued Functions.David McCarthy, Kalle Mikkola & Teruji Thomas - 2017 - MPRA Paper No. 79284.
    We provide conditions under which an incomplete strongly independent preorder on a convex set X can be represented by a set of mixture preserving real-valued functions. We allow X to be infi nite dimensional. The main continuity condition we focus on is mixture continuity. This is sufficient for such a representation provided X has countable dimension or satisfi es a condition that we call Polarization.
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