Nanay writes:
Some pairs of property-tokens are closer together in the property-space; they resemble each other more than others. But property-types are our arbitrary ways of delineating regions of this property-space. The property-space does not have joints: it consists of lots of property-tokens, some close together, some further away from each other. (2013, p. 377)
His approach seems to be more deeply metaphysical than mine. Nanay is most centrally concerned with whether a natural kind is a thing in the world that exists. I am concerned centrally with the extent to which the world constrains scientific categorization. I am happy to say that categories which uniquely allow successful science would be natural kinds regardless of whether there is an entity the deep ontology of the world which corresponds to that category. I am also willing to allow that kinds can be more or less natural, to the degree that the world condemns alternative taxonomies to failure.
Nevertheless, Nanay argues that singularist semirealism coheres with scientific practice. The reason is "that the two main tools of actual scientific practice, experimentation and measurement, are practices involving property-tokens and not property-types" (2011, p. 189; 2013, p. 383). This seems wrong to me for at least two reasons.
First: If a scientist were given a table of data which was just numbers or magnitudes, she'd have no use for it. Measurements necessarily have units. So measuring the masses and lengths of 10 samples necessarily requires measuring the masses as masses and the lengths as distances. Each singular property property must fit into a category scheme, and so measurement is impossible without kinds.
Second: It ignores the distinction between what Bogen and Woodward call data and phenomena. Singular measurements are data which are always subject to error and variation. Although data play an important evidential role, scientists don't primarily care about data. They care about phenomena which data instantiate. The phenomena are the curves or patterns which we think the data would trace out if it weren't for noise and error. When scientists repeat an experiment, they do not expect to produce precisely the same data as earlier experiments. Rather, they expect to get data which (once reduced by standard formal methods) will yield the same phenomena. So measurement and experiment are about general phenomena-types rather than singular data-tokens.
References
Bogen and Woodward 1988. Saving the Phenomena. PhilRev, 97(3): 303-352.
Chakravartty 2007. A Metaphysics for Scientific Realism, Cambridge University Press.
Nanay 2011. What If Reality Has No Architecture? The Monist, 94(2): 181-197.
Nanay 2013. Singularist Semirealism. BritJPhilSci. 64: 371-394.
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