Online research in philosophy

These comments consist of reflections on the papers Anastasios Brenner and R. N. D. Martin presented at the Conference on Pierre Duhem: Historian and Philosopher of Science. I argue they present nicely complementary accounts of Duhem's turn to history of science: Brenner emphasizes reasons internal to Duhem's philosophical concern with scientific methodology while Martin highlights reasons derived from the broader context of Duhem's engagement with religious controversies of his culture. I go on to suggest that seeing Duhem in this broader perspective can help us cope with the conflicts between science and religion in our own culture.

has proposed an interesting and novel Bayesian analysis of the Quine-Duhem (Q–D) problem (i.e., the problem of auxiliary hypotheses). Strevens's analysis involves the use of a simplifying idealization concerning the original Q–D problem. We will show that this idealization is far stronger than it might appear. Indeed, we argue that Strevens's idealization oversimplifies the Q–D problem, and we propose a diagnosis of the source(s) of the oversimplification. Some background on Quine–Duhem Strevens's simplifying idealization Indications that (I) oversimplifies Q–D Strevens's argument for the legitimacy of (I).

Duhem first expounds the holistic thesis, according to which an experimental test always involves several hypotheses, in articles dating from the 1890s. Poincaré's analysis of a recent experiment in optics provides the incentive, but Duhem generalizes this analysis and develops a highly original methodological position. He is led to reject inductivism. I will endeavor to show the crucial role history of science comes to play in the development of Duhem's holism.

Going back at least to Duhem, there is a tradition of thinking that crucial experiments are impossible in science. I analyse Duhem's arguments and show that they are based on the excessively strong assumption that only deductive reasoning is permissible in experimental science. This opens the possibility that some principle of inductive inference could provide a sufficient reason for preferring one among a group of hypotheses on the basis of an appropriately controlled experiment. To be sure, there are analogues to Duhem's problems that pertain to inductive inference. Using a famous experiment from the history of molecular biology as an example, I show that an experimentalist version of inference to the best explanation (IBE) does a better job in handling these problems than other accounts of scientific inference. Furthermore, I introduce a concept of experimental mechanism and show that it can guide inferences from data within an IBE-based framework for induction. Introduction Duhem on the Logic of Crucial Experiments ‘The Most Beautiful Experiment in Biology’ Why Not Simple Elimination? Severe Testing An Experimentalist Version of IBE 6.1 Physiological and experimental mechanisms 6.2 Explaining the data 6.3 IBE and the problem of untested auxiliaries 6.4 IBE-turtles all the way down Van Fraassen's ‘Bad Lot’ Argument IBE and Bayesianism Conclusions CiteULike Connotea Del.icio.us What's this?

This paper examines the standard Bayesian solution to the Quine–Duhem problem, the problem of distributing blame between a theory and its auxiliary hypotheses in the aftermath of a failed prediction. The standard solution, I argue, begs the question against those who claim that the problem has no solution. I then provide an alternative Bayesian solution that is not question-begging and that turns out to have some interesting and desirable properties not possessed by the standard solution. This solution opens the way to a satisfying treatment of a problem concerning ad hoc auxiliary hypotheses.

This paper addresses a central interpretive problem in understanding Pierre Duhem`s philosophy of science. The problem arises because there is textual support for both realist and antirealist readings of his work. I argue that his realist and antirealist claims are different. For Duhem, scientific reasoning leads straight to antirealism. But intuition (reasons of the heart) motivates, without justifying, a kind of realism. I develop this idea to suggest a motivational realist interpretation of Duhem`s philosophy.

This paper addresses a central interpretive problem in understanding Pierre Duhem's philosophy of science. The problem arises because there is textual support for both realist and antirealist readings of his work. I argue that his realist and antirealist claims are different. For Duhem, scientific reasoning leads straight to antirealism. But intuition (reasons of the heart) motivates, without justifying, a kind of realism. I develop this idea to suggest a motivational realist interpretation of Duhem's philosophy.

I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or "blamed" when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing auxiliary hypotheses from that of appraising a primary hypothesis. By discriminating patterns of error, this approach can at least block, if not also severely test, attempted explanations of an anomaly. I illustrate how this approach directs progress with Duhemian problems and explains how scientists actually grapple with them.