The practice of ‘management euthanasia’, in which zoos kill otherwise healthy surplus animals, is a controversial one. The debate over the permissibility of the practice tends to divide along two different views in animal ethics—animal rights and animal welfare. Traditionally, those arguments against the practice have come from the animal rights camp, who see it as a violation of the rights of the animal involved. Arguments in favour come from the animal welfare perspective, who argue that as the animal does (...) not suffer, there is no harm in the practice and it is justified by its potential benefits. Here, I argue that an expansion of the welfare view, encompassing longevity and opportunities for positive welfare, give stronger considerations against management euthanasia, which then require greater benefits to justify its use. (shrink)

A ubiquitous argument against mental-state accounts of well-being is based on the notion that mental states like happiness and satisfaction simply cannot be measured. The purpose of this paper is to articulate and to assess this “argument from measurability.” My main thesis is that the argument fails: on the most charitable interpretation, it relies on the false proposition that measurement requires the existence of an observable ordering satisfying conditions like transitivity. The failure of the argument from measurability, however, does not (...) translate into a defense of mental-state accounts as accounts of well-being or of measures of happiness and satisfaction as measures of well-being. Indeed, I argue, the ubiquity of the argument from measurability may have obscured other, very real problems associated with mental-state accounts of well-being – above all, that happiness and satisfaction fail to track well-being – and with measures of happiness and satisfaction – above all, the tendency toward reification. I conclude that the central problem associated with the measurement of, e.g., happiness as a subjectively experienced mental state is not that it is too hard to measure, but rather that it is too easy to measure. (shrink)

The science of well-being studies an evaluative kind, well-being, which raises natural worries about the ability of empirical research to deliver. This paper argues that well-being research can provide important information about how people are doing without entangling itself very deeply in controversial normative claims. Most life satisfaction research, for instance, purports only to tell us how people see their lives going relative to what they care about ? something most people can agree is important, whatever their theory of well-being. (...) At the same time, such research can mislead if it does not in fact have the significance it seems to have. Life satisfaction measures in fact have this problem: life satisfaction attitudes have deep in-principle limitations in their ability to reflect the subjective quality of people's lives, for instance because they are only weakly constrained by the facts about how people see their lives going. You might, e.g., reasonably be satisfied with your life even if you think it's going badly for you. I propose largely replacing such measures with aggregate life evaluation measures, which dispense with both the global judgment and ?satisfaction? elements of life satisfaction. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...) models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

Patient-reported outcomes are increasingly used as dependent variables in studies regarding the effectiveness of clinical interventions. But patient-reported outcome measures (PROMs) do not provide intuitively meaningful data. For instance, it is not clear what a five point increase or decrease on a particular scale signifies. Establishing ‘interpretability’ involves making changes in outcomes meaningful. Attempts to interpret PROMs have led to the development of methods for identifying a minimum important difference (MID). In this paper, however, I draw on Charles Taylor’s distinction (...) between weak and strong evaluations to suggest that identifying a MID, specifically, a MID that uses a patient-reported reference group, may not provide an adequate interpretation of these measures. Moreover, I argue that the difficulty with interpreting these measures is tied to a larger problem concerning their validity. If researchers wish to interpret PROMs, they may first need to know more about the constructs they attempt to measure, namely, quality of life. (shrink)