A dominant strand of philosophical thought holds that natural kinds are clusters of objects with shared properties. Cluster theories of natural kinds are often taken to be a late twentieth-century development, prompted by dissatisfaction with essentialism in philosophy of biology. I will argue here, however, that a cluster theory of kinds had actually been formulated by William Whewell (1794-1866) more than a century earlier. Cluster theories of kinds can be characterized in terms of three central commitments, all of which are (...) present in Whewell’s work on classification. Like contemporary cluster theorists, Whewell claims that kinds are united by similarity, that many kinds do not have essences, and that there are “gaps” between kinds. Moreover, Whewell advises taxonomists to look for consilience (roughly, convergence) between different classificatory schemes, a recommendation that reinforces the identification of natural classes with property clusters. Thus Whewell was not only an early cluster theorist, but one with important insights into what a cluster theory of kinds means for the practice of classification. (shrink)

William Whewell’s philosophy of science is often overlooked as a relic of 19th century Whiggism. I argue however that his view – suitably modified – can contribute to contemporary philosophy of science, particularly to debates around scientific progress. The reason Whewell’s view needs modification is that he makes the following problematic claim: as science progresses, it reveals necessarily truths and thereby grants a glimpse of the mind of God. Modifying Whewell’s view will involve reinventing his notion of necessary truth as (...) the pragmatist notion of superassertibility. And, if scientific progress does not uncover necessary truths, then it does not reveal the mind of God. The result is an outline of an account of scientific progress that is piecemeal and fallibilist in nature, yet at the same time maintains key Whewellian themes of consilience and the unity of science. (shrink)

In this paper I demonstrate that, contrary to the standard interpretations, William Whewell's view of scientific method is neither that of the hypothetico-deductivist nor that of the retroductivist. Rather, he offers a unique inductive methodology, which he calls "discoverers' induction." After explicating this methodology, I show that Kepler's discovery of his first law of planetary motion conforms to it, as Whewell claims it does. In explaining Whewell's famous phrase about "happy guesses" in science, I suggest that Whewell intended a distinction (...) between "inductions," which can be empirically verified, and "mere hypotheses"--or guesses--which cannot. Finally, I argue that Whewell's discoverers' induction is a view worthy of our attention today, because it avoids a number of problems faced by prominent alternative methodologies. (shrink)

Copernicus claimed that his system was preferable in part on the grounds of its superior harmony and simplicity, but left very few hints as to what was meant by these terms. Copernicus’s pupil, Rheticus, was more forthcoming. Kepler, influenced by Rheticus, articulated further the nature of the virtues of harmony and simplicity. I argue that these terms are metaphors for the structural features of the Copernican system that make it more able to effectively exploit the available data. So it is (...) a mistake to conclude that early Copernicans could only offer aesthetic or pragmatic arguments; they could and did offer evidential ones as well. Moreover, the evidential arguments they offered parallel current arguments in the philosophical literature.Keywords: Nicolaus Copernicus; Georg Joachim Rheticus; Johannes Kepler; Simplicity; Bayesianism; Hirotsugu Akaike. (shrink)

In this paper, I examine William Whewell’s (1794–1866) ‘Discoverer’s Induction’, and argue that it 21 supplies a strikingly accurate characterization of the logic behind many statistical methods, exploratory 22 data analysis (EDA) in particular. Such methods are additionally well-suited as a point of evaluation of 23 Whewell’s philosophy since the central techniques of EDA were not invented until after Whewell’s death, 24 and so couldn’t have influenced his views. The fact that the quantitative details of some very general 25 methods (...) designed to suggest hypotheses would so closely resemble Whewell’s views of how theories 26 are formed is, I suggest, a strongly positive comment on these views. (shrink)

Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied “methodological triangulation”. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than (...) it could have been by any single method. Against this, methodological purists believe that one should choose a single appropriate method and stick with it. Using tools from voting theory, we show Du Boisian methodological triangulation to be more likely to yield the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This holds even when in fact only one of the methods is appropriate for the given research question. (shrink)

I have always been a philosopher at heart. I write history of science and history of its philosophy primarily as a philosopher wary of his abstractions and broad conceptualizations. But that has not always been the case. Lakatos famously portrayed history of science as the testing ground for theories of scientific rationality. But he did so along the crudest Hegelian lines that did injury both to Hegel and to the history and methodology of science. Since science is ultimately rational, he (...) argued, rival methodologies can prove their mettle by competing for whose tendentiously reconstructed account of the history of science renders more of it rational! My own approach to the relationship between history and philosophy of science started out perhaps a little more open-mindedly than Lakatos’s, but in a manner no less crude. Over the years the relationship between the history I wrote and the philosophy to which I was committed took on a firmer and more reciprocal shape. It did so in the course of a process that I now realize exemplified the philosophical position it eventually yielded. I would like to trace that development in the following pages and reflect as best I can on where it has lead and left me. (shrink)

Primarily between 1833 and 1840, William Whewell attempted to accomplish what natural philosophers and scientists since at least Galileo had failed to do: to provide a systematic and broad-ranged study of the tides and to attempt to establish a general scientific theory of tidal phenomena. I document the close interaction between Whewell’s philosophy of science and his scientific practice as a tidologist. I claim that the intertwinement between Whewell’s methodology and his tidology is more fundamental than has hitherto been documented.Keywords: (...) William Whewell; Tidology; History of HPS; Scientific methodology; Whewell papers. (shrink)

Traditionally, cognitive values have been thought of as a collective pool of considerations in science that frequently trade against each other. I argue here that a finer-grained account of the value of cognitive values can help reduce such tensions. I separate the values into groups, minimal epistemic criteria, pragmatic considerations, and genuine epistemic assurance, based in part on the distinction between values that describe theories per se and values that describe theory-evidence relationships. This allows us to clarify why these values (...) are central to science and what role they should play, while reducing the tensions among them. (shrink)

The aim of this work is to elucidate John F. W. Herschel’s distinctive contribution to nineteenth-century British inductivism by exploring his understanding of experimental methods. Drawing on both his explicit discussion of experiment in his Preliminary Discourse on Natural Philosophy and his published account of experiments he conducted in the domain of electromagnetism, I argue that the most basic principle underlying Herschel’s epistemology of experiment is that experiment enables a particular kind of lower-level experimental understanding of phenomena. Experimental practices provide (...) knowledge of a particular phenomenon as a genuine effect produced under precise material conditions whose connections with other phenomena can be traced by variations in experimental parameters. The orienting concern of experimental inquiry seems to be the production of a secure understanding of phenomena even if it has no direct theoretical significance. Insofar as one can generate this lower-level understanding, it can function both as a fertile source for explanatory principles about phenomena and as a body of evidence against which one can test the adequacy of an explanatory hypothesis. This project provides evidence of Herschel’s inductivism not merely as a philosophical approach to understanding the sciences but as a methodological commitment in scientific practice. (shrink)

One of the arguments advanced in favor of scientific realism is the 'miracle argument'. It says that for the anti-realist the predictive success of science appears as an utter miracle. This argument indeed has some prima facie plausibility, provided that it is sharpened by construing "predictive success" as prediction of previously unknown laws and the occurrence of a consilience of inductions. Still, the history of science teaches us that it is possible to arrive at predictive success in this sense by (...) employing radically non-referring theoretical mechanisms. The 'miracle argument' is thus unsound. Rather, the capacity of a theory to generate predictive success can be traced back to its "classificativity correspondence.". (shrink)

The goal of this dissertation is to contribute to the epistemology of science by addressing a set of related questions arising from current discussions in the philosophy and science of climate change: (1) Given the imperfection of computer models, how do they provide information about large and complex target systems? (2) What is the relationship between consilient reasoning and robust evidential support in the production of scientific knowledge? (3) Does taking the mean of a set of model outputs provide epistemic (...) advantages over using the output of a single ‘best model’? Synthesizing research in philosophy and science, the thesis analyzes connections among consilient inductions, robustness analysis, and the aggregation of various sources of evidence, including computer simulations, by investigating case studies of climate change that exemplify the strength of consilient reasoning and the security of robust evidential support. It also explains the rationale and epistemic conditions for improving estimates by averaging multiple estimates, comparing a simple case of averaging estimates to practices in multi-model ensemble studies. I argue: (A) the concepts of consilience and robustness account for the strength and security of inferences that rely on imperfect computer modelling methods, (B) consilient reasoning is conducive to attaining robust evidential support, and (C) an analogy can explain why averaging the outputs of multiple models can improve estimates of a target system, given that conditions of model independence, skill and unequal weighting are taken into account. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2012.