- Dispositions in the Philosophy of Science
Goals of this chapter: to show how the framework in Part I of Scientific Ontology (a sliding scale for metaphysical inferences indexed to differing degrees of epistemic risk) applies to actual work in scientific ontology (in this case, dispositions).
- What is a disposition?
A disposition is “a causal power” (100) that is only manifested under certain conditions.
- For example, salt is soluble = salt, when immersed in water, dissolves.
- So, salt has a disposition to dissolve in water.
Dispositional properties are contrasted with categorical properties, which are not manifested under specific conditions.
- For example, salt’s property of being a sodium compound is categorical.
- Dispositional realism
Realists about dispositional properties justify their position via metaphysical inference: dispositions are alleged to best explain a number of things including:
- Empirical generalizations,
- The overlap between different realist positions,
- Scientific practices of explanation, extrapolation, and the use of inconsistent models.
- Dispositional antirealism
Some find dispositional properties too mysterious. They might even be realists about instances of dissolving salt while denying that there is a dispositional property, solubility, standing over and above these instances. Or they might hold that salt’s molecular structure (a categorical property) exists and that solubility is just a way of describing that structure, but once again, this doesn’t require an extra commitment to solubility.
- Explanatory Power I: Unifying Scientific Realism
Chakravartty uses dispositional realism to provide a unified account of several theses and concepts in the metaphysics of science. As he notes, however, whether one is moved by this depends on one’s stance.
- Unifying Entity and Structural RealismBackground.
Let’s begin with a brief history of scientific realism.
Scientific realism holds that our best scientific theories provide approximately true descriptions of both the observable and unobservable world.
Its chief challenge is the Pessimistic Induction, which roughly stated, runs as follows holds that today’s most successful theories are false because our most successful theories in the past were subsequently discovered to be false. Typical realist responses involve two moves:
- To raise the standards of “most successful.” Two “high-grade successes” are:
- Experimental intervention. Intervening to produce an effect in a well-designed experiment.
- Novel prediction. Making a bold prediction, unique to the theory, that is borne out.
- To narrow which parts of a theory are “approximately true.” Only those parts of the theory indispensable to the high-grade success warrant realist commitment.
This is called selective realism. The two most prominent kinds of selective realism are:
- Entity realism. This holds that specific entities are real (typically the ones that figure in successful experimental interventions). It frequently denies that other parts of a theory—including many of the descriptions of entities—are accurate.
- Structural realism. This holds that we should be realists about the relations between entities, but should be agnostic about the entities that stand in those relations. Furthermore, it is only the abstract (mathematical) structure of these relationships that gets preserved over time in science, and this is the only thing we should be realists about.
- Unifying entity and structural realism.
On the face of it, entity realists should be pessimistic about structures, and structural realists should be skeptical about entities. But this needn’t be so. Chakravartty argues as follows:
U1. If entity realism is true, then entities can be detected or manipulated.
U2. If an entity is detected or manipulated, then scientists have knowledge of the detector or the manipulation’s causal powers.
U3. Causal powers = dispositions.
U4. If scientists have knowledge of dispositions, then dispositional realism is true.
U5. So, if entity realism is true, then dispositional realism is true.
U6. If dispositional realism is true, then there is a relation between that entity, the effect it produces when its causal power is manifested, and the conditions in which that power is manifested, and that relation is typically expressible in mathematics.
U7. If there is a relation between that entity, the effect it produces when its causal power is manifested, and the conditions in which that power is manifested, and that relation is typically expressible in mathematics, then structural realism is true.
U8. If dispositional realism is true, then structural realism is true.
Comment: This is a pretty unorthodox “unification.” Typically, A unifies B and C if B and C follow from A. (Think of how Newtonian mechanics gives a unified account of the tides and planetary orbits.) In this case, dispositional and structural realism follow from entity realism. So, entity realism should be the unifying framework!
Possible reply: The reasoning offered here doesn’t capture the fact in greatest need of explanation—namely how both entity and structural realism could simultaneously be true.
- Unifying Properties, Causation, Laws of Nature, and Scientific Categories
C1. Entities participate in causal processes.
C2. That entities have disposition-conferring properties best explains why they participate in causal processes.
C3. So, entities have disposition-conferring properties.
K1. Science routinely succeeds in categorizing entities in ways that allow for reliable generalizations (laws) and predictions using those categories (natural kinds).
K2. That entities have disposition-conferring properties best explains this success.
K3. So, entities have disposition-conferring properties.
- Stances Enter the Fray
These unifying arguments only have force if one subscribes to entity and structural realism (in §2.1) and causation, laws, and natural kinds.
Furthermore, one might be unimpressed by how empirically unconstrained (no “empirical answerability”) these explanations/unifications are.
This is a matter of one’s stance.
- Explanatory Power II: Giving Scientific Explanations
- Transcendental Argument for Dispositions: Big Picture
P1. Science explains many phenomena.
P2. That science explains many phenomena presupposes the existence of dispositional properties.
C. Therefore, dispositional properties exist.
- Dispositional Regress Argument
- If C is a categorical property and D is a dispositional property, then for every explanation of D in terms of C, C causes D under some circumstances but not in others.
- For all X and Y, if X causes Y under some conditions and not others, then X is disposed to cause Y.
- So, every explanation of a dispositional property presupposes another dispositional property.
- Dispositional Exercise Argument
- It sometimes appears that no disposition is being exercised when there is good reason to believe that it is. (see electron example from Cartwright, p. 116)
- The explanation of such phenomena presuppose counteracting dispositions.
- Argument from Abstraction
- Science abstracts away some parts of a system in order to explain how a system would behave if the remaining parts were the only operant causes.
- So, abstract explanations presuppose dispositions.
- Stances, Again
The dispositional antirealist will claim that these arguments only show the indispensability of dispositional language, not of dispositional properties.
Many of these arguments beg the question against the dispositional antirealist.
In many cases, disposition-talk can be swapped out for non-disposition-talk. For example, putative dispositions of an isolated system are not manifested in more complex systems. So, abstraction might merely be a useful tool for guiding research, but it need not be construed as describing dispositions.
However, are dispositions even necessary here? “Behaviors like [those of enzymes] are surely amenable to dispositional description, but they are also surely amenable, if one is that way inclined, to description simply in terms of entities with categorical properties.”
- Explanatory Power III: Consolidating Scientific Knowledge
- Science uses inconsistent models of the same phenomenon.
- That these phenomena have dispositional properties (i.e., that they behave differently under different circumstances) best explains why science can use inconsistent models effectively.
This, too, runs into the typical stance-y treatments. Among other things, empiricists don’t think that theories need to accurately describe unobservables, so they won’t be bothered by models that are inconsistent about unobservables. (It will kind of be like using a Philips and flathead screwdriver under different circumstances.)
- Property Identity
Chakravartty suggests that dispositional realism will only work with certain kinds of empiricism:
- Either dispositions determine a property’s quiddity, i.e., why that property is what it is, or quiddities are fundamentally unknowable.
- In science, quiddities are assumed to be knowable.
- So, if dispositional antirealism is true, then science regularly fails to produce knowledge of scientific properties.
Chakravartty suggests that dispositional antirealists who hold that scientists produce knowledge of scientific properties are guilty of self-sabotage. A more promising dispositional antirealist should deny that questions about quiddities should be answered.