Anna Alexandrova

Well–being, health and freedom are some of the many phenomena of interest to science whose definitions rely on a normative standard. Empirical generalizations about them thus present a special case of value-ladenness. I propose the notion of a ‘mixed claim’ to denote such generalizations. Against the prevailing wisdom, I argue that we should not seek to eliminate them from science. Rather, we need to develop principles for their legitimate use. Philosophers of science have already reconciled values with objectivity in several ways, but none of the existing proposals are suitable for mixed claims. Using the example of the science of well-being, I articulate a conception of objectivity for this science and for mixed claims in general. _1_ Introduction _2_ What Are Mixed Claims? _3_ Mixed Claims Are Different _3.1_ Values as reasons to pursue science _3.2_ Values as agenda-setters _3.3_ Values as ethical constraints on research protocols _3.4_ Values as arbiters between underdetermined theories _3.5_ Values as determinants of standards of confirmation _3.6_ Values as sources of wishful thinking and fraud _4_ Mixed Claims Should Stay _4.1_ Against Nagel _5_ The Dangers of Mixed Claims _6_ The Existing Accounts of Objectivity _6.1_ The perils of impartiality _7_ Objectivity for Mixed Claims _8_ Three Rules _8.1_ Unearth the value presuppositions in methods and measures _8.2_ Check if value presuppositions are invariant to disagreements _8.3_ Consult the relevant parties _9_ Conclusion.

What makes a measure of well-being valid? The dominant approach today, construct validation, uses psychometrics to ensure that questionnaires behave in accordance with background knowledge. Our first claim is interpretive—construct validation obeys a coherentist logic that seeks to balance diverse sources of evidence about the construct in question. Our second claim is critical—while in theory this logic is defensible, in practice it does not secure valid measures. We argue that the practice of construct validation in well-being research is theory avoidant, favoring a narrow focus on statistical tests while largely ignoring relevant philosophical considerations.

Rational choice modeling originating in economics is sweeping across many areas of social science. This paper examines a popular methodological proposal for integrating formal models from game theory with more traditional narrative explanations of historical phenomena, known as “analytic narratives”. Under what conditions are we justified in thinking that an analytic narrative provides a good explanation? In this paper I criticize the existing criteria and provide a set of my own. Along the way, I address the critique of analytic narratives by Jon Elster.

Judgments of well-being across different circumstances and spheres of life exhibit a staggering diversity. Depending on the situation, we use different standards of well-being and even treat it as being constituted by different things. This is true of scientific studies as well as of everyday life. How should we interpret this diversity? I consider three ways of doing so: first, denying the legitimacy of this diversity, second, treating well-being as semantically invariant but differentially realizable, and, third, adopting contextualist semantics for well-being expressions. I reject the first option on the grounds that it is unable to make sense of much of everyday and scientific linguistic practices, and also because it makes the category of well-being insignificant or even otiose for practical purposes. We should thus pick between the second and the third options. I argue that contextualism about well-being is more plausible and faces fewer objections than the differential realization view. I conclude with a discussion of other features of contextualism: it does not imply that well-being is relative to individual taste, it need not result in eliminativism about well-being, nor in scepticism about a general theory of well-being. It does not commit us to an “anything goes” approach, nor does it threaten anarchy and miscommunication.

This article is a mutual introduction of the science of well-being to philosophy of science and an explanation of how the two disciplines can benefit each other. In the process, I argue that the science of well-being is not helpfully viewed as a social or a natural, but rather as a mixed, science. Hence, its methodology will have to attend to its specific features. I discuss two of its methodological problems: justifying the role of values, and validating measures. I suggest that tackling them calls for developing mid-level rather than high theories of well-being.

What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account. *Received July 2006; revised August 2008. †To contact the author, please write to: Department of Philosophy, University of Missouri, St. Louis, 599 Lucas Hall (MC 73), One University Blvd., St. Louis, MO 63121-4400; e-mail: [email protected].

The burgeoning science of well-being makes no secret of being value laden: improvement of well-being is its explicit goal. But in order to achieve this goal its concepts and claims need to be value adequate; that is, they need, among other things, to adequately capture well-being. In this article I consider two ways of securing this adequacy—first, by relying on philosophical theory of prudential value and, second, by the psychometric approach. I argue that neither is fully adequate and explore an alternative. This alternative requires thorough changes in the way philosophers theorize about well-being.

Can social phenomena be understood by analyzing their parts? Contemporary economic theory often assumes that they can. The methodology of constructing models which trace the behavior of perfectly rational agents in idealized environments rests on the premise that such models, while restricted, help us isolate tendencies, that is, the stable separate effects of economic causes that can be used to explain and predict economic phenomena. In this paper, I question both the claim that models in economics supply claims about tendencies and also the view that economics, when successful, necessarily follows this method. When economics licenses successful policy interventions, as it did in the case of the Federal Communications Commission spectrum auctions, its method is not to study tendencies but rather to study the phenomenon as a whole. Key Words: economic models • tendencies • economic experiments • policy making • John Stuart Mill.