2008
DOI: 10.1177/0952695108091414
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Facts, norms and expected utility functions

Abstract: In this paper we want to explore an argumentative pattern that provides a normative justification for expected utility functions grounded on empirical evidence, showing how it worked in three different episodes of their development. The argument claims that we should prudentially maximize our expected utility since this is the criterion effectively applied by those who are considered wisest in making risky choices (be it gamblers or businessmen). Yet, to justify the adoption of this rule, it should be proven t… Show more

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Cited by 19 publications
(9 citation statements)
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“…Equation (1) shows an example of a utility function in which an individual's expected utility ( U ) for disease ( i ) is described as a function of the sum of all the values of the possible overall impacts of the disease (possible disease states, u ij ) and the probability of occurrence of each of those possible disease states ( p j ). The axioms that describe rational choice – in particular, completeness and transitivity – have traditionally been used as the ‘gold standard’ to define rational choice, against which decisions are judged as logical; normative decision theory is the dominant underlying theory in decision science, particularly in economics [14]. In the context of disease prioritization actions need to be defensible, particularly in the face of disease events, when questions are asked such as, ‘given the impact of this event, were the actions justified and should resources have been directed differently?’ Using a decision-aid based on normative theory – therefore complying with the axioms of rational choice – gives rational results, inherently confirming that decisions were logical and that the process was transparent and therefore, auditable [15].…”
Section: Decision Theory and The Requirements Of Disease Prioritizationmentioning
confidence: 99%
“…Equation (1) shows an example of a utility function in which an individual's expected utility ( U ) for disease ( i ) is described as a function of the sum of all the values of the possible overall impacts of the disease (possible disease states, u ij ) and the probability of occurrence of each of those possible disease states ( p j ). The axioms that describe rational choice – in particular, completeness and transitivity – have traditionally been used as the ‘gold standard’ to define rational choice, against which decisions are judged as logical; normative decision theory is the dominant underlying theory in decision science, particularly in economics [14]. In the context of disease prioritization actions need to be defensible, particularly in the face of disease events, when questions are asked such as, ‘given the impact of this event, were the actions justified and should resources have been directed differently?’ Using a decision-aid based on normative theory – therefore complying with the axioms of rational choice – gives rational results, inherently confirming that decisions were logical and that the process was transparent and therefore, auditable [15].…”
Section: Decision Theory and The Requirements Of Disease Prioritizationmentioning
confidence: 99%
“…However, we emphasize the role of generalities in the agent's reflective process more than these authors do. 45 Jallais et al (2008) relate Allais's remarks to older ideas of prudence as pragmatic wisdom, and concomitantly of public recognition as a touchstone of prudence. Although this is an interesting direction to take, we doubt that the textual evidence supports it.…”
mentioning
confidence: 98%
“…The 'normative retreat' thesis appears in Guala (2000), Jallais et al (2008), Bourgeois- Gironde and Giraud (2008), and in a more subdued form in Heukelom (2015). It seems to belong to an oral tradition of decision theory; how it gained momentum is unclear.…”
mentioning
confidence: 99%
“…Cudd (1993) and Hollis and Sugden (1993)), and histories of consumer theory or microeconomics (Hands 2006;Mirowski and Hands 2006). For some work about specific aspects of the history of decision theory, see for example Guala (2000), Heukelom (2010), Jallais et. al.…”
Section: Disunity About Rational Choice Theorymentioning
confidence: 99%