186
Progressively, through empirical interaction with relevant phenomena, we may
arrive at a state of knowledge and technology such that a transduction effect can be
dependably reproduced under specified conditions, which brings us back to the
“starting point” referenced in the previous paragraph. Such a transduction effect
may become the basis of a direct method of measurement (see Sect. 7.3): through
the calibration of the transducer, the values of the output property (i.e., the instrument indication) are causally related to values of the input property (i.e., the property under measurement). For example, temperatures can be measured by means of
differences of expansion of mercury in a glass tube, and reading comprehension
abilities can be measured by means of differences in patterns of responses to questions about a particular text. Such cases presuppose the observability of a property
Y (e.g., shape, color, pattern of responses to test questions), whose differences are
accounted for as being causally dependent on differences in the property under consideration P, via an inference of the kind Y = f(P), where f is the function that models the cause-effect relation: the property P is the cause of observed changes of Y,
and therefore it exists.
All this said, if a property P is only known as the cause of observable effects in
the context of a single empirical situation (experimental setup, etc.)—that is, if there
is only a single known transduction effect of which instances of P are the input, and
where the transduction itself is understood only at a black box level—then knowledge of P is obviously highly limited; such a situation might be associated with an
operationalist perspective on measurement, and would thus inherit the limitations of
that perspective (see Sect. 4.2.2), or might simply be a very early phase in the identification of an empirical property, setting the stage for investigations of the causal
relevance of the property in situations other than this single transduction effect.
Indeed, in general, absent the availability of multiple, independent sources of
knowledge about P, in particular about its role in networks of relationships with
other phenomena (properties, outcomes, events, etc.), knowledge about P might be
considered vacuous or trivial.
For example, a claim about the existence of hardness as a property of physical
objects can be justified in a simple way by the observation that one object scratches
another: hardness (P) is what causes (f) observable scratches (Y) to appear given an
appropriate experimental setup. Were this the only source of knowledge about hardness, the correct name for P would arguably be something like “the property that
causes the effect Y”, rather than a label as semantically rich as “hardness”.
51
But, of
terminology. This is easily illustrated by the historical example of phlogiston (as also discussed in
Box 5.1): although contemporary theories deny the existence of the substance referred to as “phlogiston” by seventeenth- and eighteenth-century theorists, contemporary theories would not deny
the existence of the causal forces responsible for the putative effects of phlogiston (e.g., flammability, oxidation, rusting), but instead offer more nuanced explanations for the identity and mechanisms of these causal forces.
51 The same reasoning applies to the case of educational tests, which would in general not be valued
unless the competencies they purport to measure are demonstrably valuable in contexts beyond the
immediate testing situation.
6 Values, scales, and the existence of properties
Progressively, through empirical interaction with relevant phenomena, we may
arrive at a state of knowledge and technology such that a transduction effect can be
dependably reproduced under specified conditions, which brings us back to the
“starting point” referenced in the previous paragraph. Such a transduction effect
may become the basis of a direct method of measurement (see Sect. 7.3): through
the calibration of the transducer, the values of the output property (i.e., the instrument indication) are causally related to values of the input property (i.e., the property under measurement). For example, temperatures can be measured by means of
differences of expansion of mercury in a glass tube, and reading comprehension
abilities can be measured by means of differences in patterns of responses to questions about a particular text. Such cases presuppose the observability of a property
Y (e.g., shape, color, pattern of responses to test questions), whose differences are
accounted for as being causally dependent on differences in the property under consideration P, via an inference of the kind Y = f(P), where f is the function that models the cause-effect relation: the property P is the cause of observed changes of Y,
and therefore it exists.
All this said, if a property P is only known as the cause of observable effects in
the context of a single empirical situation (experimental setup, etc.)—that is, if there
is only a single known transduction effect of which instances of P are the input, and
where the transduction itself is understood only at a black box level—then knowledge of P is obviously highly limited; such a situation might be associated with an
operationalist perspective on measurement, and would thus inherit the limitations of
that perspective (see Sect. 4.2.2), or might simply be a very early phase in the identification of an empirical property, setting the stage for investigations of the causal
relevance of the property in situations other than this single transduction effect.
Indeed, in general, absent the availability of multiple, independent sources of
knowledge about P, in particular about its role in networks of relationships with
other phenomena (properties, outcomes, events, etc.), knowledge about P might be
considered vacuous or trivial.
For example, a claim about the existence of hardness as a property of physical
objects can be justified in a simple way by the observation that one object scratches
another: hardness (P) is what causes (f) observable scratches (Y) to appear given an
appropriate experimental setup. Were this the only source of knowledge about hardness, the correct name for P would arguably be something like “the property that
causes the effect Y”, rather than a label as semantically rich as “hardness”.
51
But, of
terminology. This is easily illustrated by the historical example of phlogiston (as also discussed in
Box 5.1): although contemporary theories deny the existence of the substance referred to as “phlogiston” by seventeenth- and eighteenth-century theorists, contemporary theories would not deny
the existence of the causal forces responsible for the putative effects of phlogiston (e.g., flammability, oxidation, rusting), but instead offer more nuanced explanations for the identity and mechanisms of these causal forces.
51 The same reasoning applies to the case of educational tests, which would in general not be valued
unless the competencies they purport to measure are demonstrably valuable in contexts beyond the
immediate testing situation.
6 Values, scales, and the existence of properties