Clark Glymour

In "The Epistemology of Geometry" Glymour proposed a necessary structural condition for the synonymy of two space-time theories. David Zaret has recently challenged this proposal, by arguing that Newtonian gravitational theory with a flat, non-dynamic connection (FNGT) is intuitively synonymous with versions of the theory using a curved dynamical connection (CNGT), even though these two theories fail to satisfy Glymour's proposed necessary condition for synonymy. Zaret allowed that if FNGT and CNGT were not equally well (bootstrap) tested by the relevant phenomena, the two theories would in fact not be synonymous. He argued, however, that when electrodynamic phenomena are considered, the two theories are equally well tested. We show that it is not FNGT and CNGT which are equally well tested when the electrodynamic phenomena are considered, but only suitable extensions of FNGT and CNGT. Thus, there is good reason to consider FNGT and CNGT to be non-synonymous. We further show that the two extensions of FNGT and CNGT which are equally well tested when electrodynamic phenomena are considered (and which could be considered intuitively synonymous) not only satisfy Glymour's original proposed necessary condition for the synonymy of space-time theories, they satisfy a plausible stronger condition as well

Halpern's Actual Causality is an extended development of an account of causal relations among individual events in the tradition that analyzes causation as difference making. The book is notable for its efforts at formal clarity, its exploration of "normality" conditions, and the wealth of examples it uses and whose provenance it traces. Unfortunately, the various normality conditions considered undermine the capacity of the basic theory to plausibly treat various cases Halpern considers, and the unalloyed basic theory yields implausible results in simple cases of overdetermination, which are not remedied by Halpern's probabilistic version of his theory or unambiguously by the variety of normality conditions Actual Causality entertains.

The second edition of a unique introductory text, offering an account of the logical tradition in philosophy and its influence on contemporary scientific disciplines. Thinking Things Through offers a broad, historical, and rigorous introduction to the logical tradition in philosophy and its contemporary significance. It is unique among introductory philosophy texts in that it considers both the historical development and modern fruition of a few central questions. It traces the influence of philosophical ideas and arguments on modern logic, statistics, decision theory, computer science, cognitive science, and public policy. The text offers an account of the history of speculation and argument, and the development of theories of deductive and probabilistic reasoning. It considers whether and how new knowledge of the world is possible at all, investigates rational decision making and causality, explores the nature of mind, and considers ethical theories. Suggestions for reading, both historical and contemporary, accompany most chapters. This second edition includes four new chapters, on decision theory and causal relations, moral and political theories, “moral tools” such as game theory and voting theory, and ethical theories and their relation to real-world issues. Examples have been updated throughout, and some new material has been added. It is suitable for use in advanced undergraduate and beginning graduate classes in philosophy, and as an ancillary text for students in computer science and the natural sciences.

Nearly all accounts of the genesis of special relativity unhesitatingly assume that the theory was worked out in a roughly five week period following the discovery of the relativity of simultaneity. Not only is there no direct evidence for this common presupposition, there are numerous considerations which militate against it. The evidence suggests it is far more reasonable that Einstein was already in possession of the Lorentz and field transformations, that he had applied these to the dynamics of the electron, and that portions of the 1905 paper had actually been drafted well before the epistemological analysis of time.

The ultimate focus of the current essay is on methods of “creative abduction” that have some guarantees as reliable guides to the truth, and those that do not. Emphasizing work by Richard Englehart using data from the World Values Survey, Gerhard Schurz has analyzed literature surrounding Samuel Huntington’s well-known claims that civilization is divided into eight contending traditions, some of which resist “modernization” – democracy, civil rights, equality of rights of women and minorities, secularism. Schurz suggests an evolutionary model of modernization and identifies opposing social forces. In a later essay, citing Englehart’s work as an example, Schurz identifies factor analysis as an example of “creative abduction”. The theories of Englehart and his collaborators are reviewed again in the current essay. Published simulations and standard statistical desiderata for causal inference show the methods Englehart used, factor analysis in particular, are not guides to truth for the kind of data Schurz recognizes as common in political science. Recent work in statistics, philosophy and computer science that makes advances towards such methods is briefly reviewed.

The use of ceteris paribus clauses in philosophy and in the sciences has a long and fascinating history. Persky (1990) traces the use by economists of ceteris paribus clauses in qualifying generalizations as far back as William Petty’s Treatise of Taxes and Contributions (1662). John Cairnes’ The Character and Logical Method of Political Economy (1857) is credited with enunciating the idea that the conclusions of economic investigations hold “only in the absence of disturbing causes”.1 His Leading Principles (1874) contains the classic example of a ceteris paribus law: “The rate of wage, other things being equal, varies inversely with the supply of labour”. Carines’ ideas were popularized by Alfred Marshall in his Principles of Economics (1890) where he argued for a methodology that involved holding disturbing causes “in a pound called Caeteris Paribus”. It is unclear when the notion of ceteris paribus laws made its appearance in the philosophical literature; but in the nineteenth century it is to be found in Mill’s System of Logic (1843), and in the twentieth century it gained prominence in the Hempel-inspired debates of the 1950’s over the role of general laws in historical explanations, albeit under other labels such as quasi-laws (Rescher) or grounded generalizations (Scriven).

Through their transcript products genes regulate the rates at which an immense variety of transcripts and subsequent proteins occur. Understanding the mechanisms that determine which genes are expressed, and when they are expressed, is one of the keys to genetic manipulation for many purposes, including the development of new treatments for disease. Viewing each gene in a genome as a distinct variable that is either on or off, or more realistically as a continuous variable, the values of some of these variables influence the values of others through the regulatory proteins they express, including, of course, the possibility that the rate of expression of a gene at one time may, in various circumstances, influence the rate of expression of that same gene at a later time. If we imagine an arrow drawn from each gene expression variable at a given time to a gene variable whose expression it influences a short while after, the result is a network, technically a directed acyclic graph. For example, the DAG in Figure 1 is a representation of a system in which the expression level of gene G1 at time 1 ) causes the expression level of G2, which in turn causes the expression level of G3. The arrows in Figure 1 which do not have a variable at their tails are “error terms” which represent all of the causes of a variable other than the ones explicitly represented in the DAG. The DAG describes more than associations—it describes causal connections among gene expression rates. A shock to a cell—by mutation, heating, chemical treatment, etc. may alter the DAG describing the relations among gene expressions, for example by activating a gene that was otherwise not expressed, producing a cascade of new expression effects. Although “knockout” experiments can reveal some of the underlying causal network of gene expression levels, unless guided by information from other sources, such experiments are limited in how much of the network structure they can reveal, due to the sheer number of possible combinations of experimental manipulations of genes necessary to reveal the complete causal network. Recent developments have made it possible to compare quantitatively the expression of tens of thousands of genes in cells from different sources in a single experiment, and to trace gene expression over time in thousands of genes simultaneously. cDNA microarrays are already producing extensive data, much of it available on the web. Thus there are calls for analytic software that can be applied to microarray and other data to help infer regulatory networks. In this paper we will review current techniques that are available for searching for the causal relations between variables, describe algorithmic and data gathering obstacles to applying these techniques to gene expression levels, and describe the prospects for overcoming these obstacles

The notion of reduction in the natural sciences has been assimilated to the notion of inter-theoretical explanation. Many philosophers of science (following Nagel) have held that the apparently ontological issues involved in reduction should be replaced by analyses of the syntactic and semantic connections involved in explaining one theory on the basis of another. The replacement does not seem to have been especially successful, for we still lack a plausible account of inter-theoretical explanation. I attempt to provide one