Thick concepts, namely those concepts that describe and evaluate simultaneously, present a challenge to science. Since science does not have a monopoly on value judgments, what is responsible research involving such concepts? Using measurement of wellbeing as an example, we first present the options open to researchers wishing to study phenomena denoted by such concepts. We argue that while it is possible to treat these concepts as technical terms, or to make the relevant value judgment in-house, the responsible thing to (...) do, especially in the context of public policy, is to make this value judgment through a legitimate political process that includes all the stakeholders of this research. We then develop a participatory model of measurement based on the ideal of co-production. To show that this model is feasible and realistic, we illustrate it with a case study of co-production of a concept of thriving conducted by the authors in collaboration with a UK anti-poverty charity Turn2us. (shrink)

There is a widely held view on measurement inferences, that goes back to Stevens’s ([1946]) theory of measurement scales and ‘permissible statistics’. This view defends the following prohibition: you should not make inferences from averages taken with ordinal scales (versus quantitative scales: interval or ratio). This prohibition is general—it applies to all ordinal scales—and it is sometimes endorsed without qualification. Adhering to it dramatically limits the research that the social and biomedical sciences can conduct. I provide a Bayesian analysis of (...) this inferential problem, determining when measurements from ordinal scales can be used to confirm hypotheses about relative group averages. The prohibition, I conclude, cannot be upheld, even in a qualified sense. The beliefs needed to make average comparisons are less demanding than those appropriate for quantitative scales. I illustrate with the alleged paradigm ordinal scale, Mohs’ scale of mineral hardness, arguing that the literature has mischaracterized it. (shrink)