Abstract

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.

Highlights

  • Are our lives happier than those of our predecessors thirty years ago (e.g. Easterlin 1995; Hagerty and Veenhoven 2003; Easterlin et al 2010)? Are people in Finland happier than they are in the United States, of any other country on earth (Helliwell et al 2019)? To answer these and similar questions researchers1 3 Vol.:(0123456789)Synthese and statistical agencies today routinely measure happiness

  • We take onboard the assumption that researchers today can measure happiness, and instead we focus on the epistemic status of happiness measurement

  • We have argued that calibration matters to happiness measures, but that the calibration of happiness is made difficult by the Two Unknowns Problem

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Summary

Introduction

Are our lives happier than those of our predecessors thirty years ago (e.g. Easterlin 1995; Hagerty and Veenhoven 2003; Easterlin et al 2010)? Are people in Finland happier than they are in the United States, of any other country on earth (Helliwell et al 2019)? To answer these and similar questions researchers. Proponents of happiness measures typically agree that the measures currently are inexact and rough As a reply, they claim that the measures have passed tests of validity (Diener et al 2013), and they expect that the measures will improve as the field matures. A central epistemic question for happiness research should be: to what extent can measurements of happiness be calibrated? Our concluding claim is that continued calibration poses a pernicious challenge in the context of happiness measurement, since it depends on getting around the Two Unknowns problem. Fleurbaey and Blanchet are concerned with “calibrating” the response scale of happiness-questionnaires, so that the meaning of each category is unambiguous Calibration in their sense is important and probably crucial, we are not directly concerned with interpreting the meaning of categories of happiness-data. Whenever we refer to researchers or others measuring happiness, we use the term “researcher”

A tripartite distinction
What happiness is
Quantitative evaluations of happiness
How happiness is measured
The epistemic role of calibration
Calibration and validation
Calibration and the problem of nomic measurement
The importance of calibration for happiness research
The two unknowns problem
Implications for calibration
Objections and ways around the problem
Absence of evidence objection
Behavioral and neural measures of happiness
Scope and proving too much
Conclusion
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