Measures of happiness are increasingly being used throughout the social sciences. While these measures have attracted numerous types of criticisms, a crucial aspect of these measures has been left largely unexplored—their calibration. Using Eran Tal’s recently developed notion of calibration we argue first that the prospect of continued calibration of happiness measures is crucial for the science of happiness, and second, that continued calibration of happiness measures faces a particular problem—The Two Unknowns Problem. The Two Unknowns Problem relies on the (...) claim that individuals are necessarily a part of the measurement apparatus in first person measures of happiness, and the claim that we have no reason to believe that the evaluation standards people employ are invariant across individuals and time. We argue that calibrating happiness measures therefore involves solving an equation with two unknowns—an individual’s degree of happiness, and their evaluation standards—which is, generally, not possible. Third, we consider two possible escape routes from this problem and we suggest that the most promising route requires yet unexplored empirical and theoretical work on linking happiness to behavioral or neural evidence. (shrink)

This paper provides a philosophical assessment of leading theory-based, evidence-based and coherentist approaches to the definition and the measurement of well-being. It then builds on this assessment to articulate a reformed division of labor for the science of well-being and argues that this reformed division of labor can improve on the proffered approaches by combining the most plausible tenets of theory-based approaches with the most plausible tenets of coherentist approaches. This result does not per se exclude the possibility that theory-based (...) and coherentist approaches may be independently improved or amended in the years to come. Still, together with the challenges that affect these approaches, it strengthens the case for combining the most plausible tenets of those approaches. (shrink)