Abstraction, Analogy and Induction: Toward a General Account of Ampliative Inference

Dissertation, University of California, San Diego (1997)
Abstract
My central concern is with the epistemological status of ampliative inference. Three sorts of ampliative inference are initially distinguished: enumerative induction, analogical reasoning, and abstraction. Philosophers of science have generally treated these separately, and in particular have often divorced the familiar problem of induction from equally fundamental questions concerning the use of analogy and abstraction: What kinds of similarity can support inference? How can we pick out those features of a system that are essential for the purposes of understanding, and in virtue of what are they essential? ;I argue that these three forms of inference can only be understood together. They are not different in kind, nor is there one among the three to which the others may be reduced. Rather, they differ quantitatively with respect to three factors: The amount of experience we have of cases similar to the target; The degree of similarity deemed to connect the target to cases previously experienced; and The degree to which this similarity relationship supports inference, as evaluated according to background belief. ;The account I develop of the relations among the three forms of ampliative inference provides a context for the reconsideration of a number of important questions concerning the relation between theory and observation: In what sense can analogical or abstract inferences be justified? What is the relationship between apparently incompatible abstract models of the same system? What is the epistemological role of background belief? In addition, the account provides a framework within which a broad range of theories of inference or projection can be integrated. ;The account is informed by an examination of the diverse views on generalizing inference reflected in the theories and material practices of late 19th and early 20th century biology
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