5
observable variables. The name is ‘valid’ only to the extent that it accurately describes the
kinds of observables being studied to others. […] The words that scientists use to denote
constructs (e.g., ‘anxiety’ and ‘intelligence’) have no real counterparts in the world of
observables; they are only heuristic devices for exploring observables. Whereas, for example, the scientist might find it more comfortable to speak of anxiety than of [item] set A,
only set A and its relations objectively exist, research results relate only set A, and, in the
final analysis, only relations within members of set A and between set A and members of
other sets can be unquestionably documented”.
This use of a term such as “heuristic devices” again seems to imply that claims
about measurement in the human sciences are best understood as being metaphorical rather than literal; alternatively, one might conclude that the term “measurement” simply has irreducibly different meanings in the physical sciences and the
human sciences, which was indeed the conclusion of some human scientists like
Stanley Smith Stevens (see, e.g., McGrane, 2015).
5
But, to us, such conclusions seem unsatisfactory: again, measurement is regarded
as integral to science and society on the basis of its epistemic authority, and so the
question remains of what, exactly, justifies claims to such authority. As Kuhn asked:
“what [is] the source of [the] special efficacy” of measurement? (1961: p. 162).
Stated alternatively, what are the necessary elements of trustworthy measurement
processes, independent of domain or area of application? We hope, in this book, to
address exactly this question: What could be a common foundation of measurement
across the sciences?
1.2 Some familiar and not-so-familiar contexts for
measurement
In the sections below, we introduce two examples of the sorts of measurement that
we had in mind when writing this book. Each will appear later at several points in
the text, along with other examples when they are more pertinent. In particular, we
recognize that many of our readers might not have experience with measurement
across both the physical sciences and the human sciences, and hence the accounts
are each designed to be quite basic, starting from a very low expectation of expertise
in their respective topic areas. These basic accounts will be expanded, deepened,
and updated at appropriate places in the text. We have also included a third section,
5 A more nuanced variation of this conclusion is that there are different kinds of measurement that
share common properties; this was the conclusion reached in particular by Ludwik Finkelstein,
who argued for a distinction between “strongly defined measurement” and “weakly defined measurement”, where the former “follows the paradigm of the physical sciences [and] is based on: (1)
precisely defined empirical operations, (2) mapping on the real number line on which an operation
of addition is defined, (3) well-formed theories for broad domains of knowledge”, and the latter is
“measurement that [...] lacks some, or all, of the above distinctive characteristics of strong measurement” (Finkelstein, 2003: p. 42).
1.2 Some familiar and not-so-familiar contexts for measurement
observable variables. The name is ‘valid’ only to the extent that it accurately describes the
kinds of observables being studied to others. […] The words that scientists use to denote
constructs (e.g., ‘anxiety’ and ‘intelligence’) have no real counterparts in the world of
observables; they are only heuristic devices for exploring observables. Whereas, for example, the scientist might find it more comfortable to speak of anxiety than of [item] set A,
only set A and its relations objectively exist, research results relate only set A, and, in the
final analysis, only relations within members of set A and between set A and members of
other sets can be unquestionably documented”.
This use of a term such as “heuristic devices” again seems to imply that claims
about measurement in the human sciences are best understood as being metaphorical rather than literal; alternatively, one might conclude that the term “measurement” simply has irreducibly different meanings in the physical sciences and the
human sciences, which was indeed the conclusion of some human scientists like
Stanley Smith Stevens (see, e.g., McGrane, 2015).
5
But, to us, such conclusions seem unsatisfactory: again, measurement is regarded
as integral to science and society on the basis of its epistemic authority, and so the
question remains of what, exactly, justifies claims to such authority. As Kuhn asked:
“what [is] the source of [the] special efficacy” of measurement? (1961: p. 162).
Stated alternatively, what are the necessary elements of trustworthy measurement
processes, independent of domain or area of application? We hope, in this book, to
address exactly this question: What could be a common foundation of measurement
across the sciences?
1.2 Some familiar and not-so-familiar contexts for
measurement
In the sections below, we introduce two examples of the sorts of measurement that
we had in mind when writing this book. Each will appear later at several points in
the text, along with other examples when they are more pertinent. In particular, we
recognize that many of our readers might not have experience with measurement
across both the physical sciences and the human sciences, and hence the accounts
are each designed to be quite basic, starting from a very low expectation of expertise
in their respective topic areas. These basic accounts will be expanded, deepened,
and updated at appropriate places in the text. We have also included a third section,
5 A more nuanced variation of this conclusion is that there are different kinds of measurement that
share common properties; this was the conclusion reached in particular by Ludwik Finkelstein,
who argued for a distinction between “strongly defined measurement” and “weakly defined measurement”, where the former “follows the paradigm of the physical sciences [and] is based on: (1)
precisely defined empirical operations, (2) mapping on the real number line on which an operation
of addition is defined, (3) well-formed theories for broad domains of knowledge”, and the latter is
“measurement that [...] lacks some, or all, of the above distinctive characteristics of strong measurement” (Finkelstein, 2003: p. 42).
1.2 Some familiar and not-so-familiar contexts for measurement