The evolution of the myxoma virus in Australia has been presented for many years as a test case for the hypothesis that group selection can function effectively ‘in the wild.’ This paper critically examines the myxoma case, and argues that its failure as a test case for this hypothesis has broader implications for debates over the levels of selection.

Treating species as individuals and not classes has been crucial to the integration of evolutionary theory with modern systematics. Despite the theoretically important role the concept of individuality plays in modern phylogenetic systematics and in evolutionary theory more generally, many have been content to rely on common-sense intuitions about what counts as an individual. One of the most often cited intuitions is that individuals should be defined intrinsically. Unfortunately, common-sense intuitions like this one have proven to be inadequate for identifying and characterizing historical individuals (like species). An examination of real-world biological examples shows that our common-sense intuitions are equally inadequate when applied to at least some biological organisms—the paradigm individuals.

Introduction. Topology (sometimes called analysis situs) is the most general and most fundamental branch of geometry. Logically its study should precede that of other kinds of geometry. But mathematical knowledge, whether regarded as part of our cultural heritage or as the possession of an individual, does not come into being like a building, from a completed foundation to a limited superstructure, but rather grows like a tree with ever-deepening roots as well as ever-spreading branches. So, historically, systematic studies in topology lagged behind Euclid's elements some 2000 years and were unknown a century ago. There has, however, been considerable activity in this field by the present generation, and a number of modern treatments are available for the specialist. In spite of its fundamental nature, the subject is difficult, and many of its problems remain unsolved even today. This difficulty makes it pedagogically advisable to avoid questions of topology germane to other branches of mathematics and there is a distinct scarcity of material available even to the mathematician, whose main interest lies outside this field.

The demonstration that slow transport of clocks can be used to define simultaneity in inertial frames of reference leads to the question of whether clock transport can similarly be used in noninertial frames. It is shown that there are certain types of reference frames in which the clock-transport method cannot be used in a self-consistent manner. It is also shown that there are other types of noninertial frames in which the clock-transport method will succeed. The discussion includes noninertial frames in flat space-time as well as the case of curved space-times.

Some scientists believe that although evolutionary theory is explanatory, it does not have, in contrast to the theories of physics, any predictive power. This raises the question of its testability. The analysis given shows that there are good reasons to claim the unpredictability of evolutionary events; nevertheless, the evolutionary theory has potential predictive power. It is argued that the difference between biology and physics lies not in the predictive power of the theories involved, but in the different weight which is lent to the forecasting of particular events in these sciences. A second source of confusion derives from the ambiguity of the term ‘prediction’. In order to define ‘prediction’ for cases in which the term is used to refer to a part of testing procedure, the reference to the time-point “now” is quite irrelevant. Prediction of unknown observational data is sufficient for testing a hypothesis, but such prediction may or may not be identical with forecasting of future events. Different factors that may cause particular difficulties met by biologists in forecasting future events are analyzed subsequently in the second part of the paper. The conclusion is drawn that although particular cognitive situations limiting the ability of forecasting are very frequent in biological sciences, the claim about the peculiar logical status of biological theories is not thereby justified.

Scholars belong to multiple communities of credit simultaneously. When these communities disagree about a scholarly achievement’s credit assignment, this raises a puzzle for decision and game theoretic models of credit seeking in science. The reference class problem for credit valuation in science is the problem of determining to which of an agent’s communities—which reference class—credit determinations should be indexed for an act under some state of nature. Solving this problem requires developing rich, mutually informed theories of community and credit that are sensitive to the structure and status systems of complex, heterogeneous scholarly networks.

Synthetic biology has a strong modal dimension that is part and parcel of its engineering agenda. In turning hypothetical biological designs into actual synthetic constructs, synthetic biologists reach toward potential biology instead of concentrating on naturally evolved organisms. We analyze synthetic biology’s goal of making biology easier to engineer through the combinatorial theory of possibility, which reduces possibility to (re)combinations of individuals and their attributes in the actual world. While the last decades of synthetic biology explorations have shown biology to be much more difficult to engineer than originally conceived, synthetic biology has not given up its combinatorial approach.

This article defends a version of the Westermarck Effect, integrating existing clinical, biological, and philosophical dimensions to incest avoidance. By focusing on care-based attachment in primates, my formulation of the effect suggests the power of a phylogenetic argument widely accepted by primatologists but not by cultural anthropologists. Identifying postadoption incest as a phenomenon with underexplored evidential value, the article sketches an explanatory strategy for reconciling the effect with the clinical reality of incest, concluding with an explicit argument against culture-first or conventionalist accounts of incest avoidance prevalent in anthropology.

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites’ conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality, and doing so may improve the predictive and explanatory power of extant models.

A theory of true observation is developed as a generalization of the method of inter-observer agreement that scientists use to determine the objectivity and reliability of observations. A true observation is defined as a statement included in a set of statements in which there is statistical dependence and perfect agreement between the statements made by a universe of experimentally independent persons. Meaningfulness—the existence of an objective referent—for each form of statement included in the set is inferred from statistical dependence, correct meaning within the universe of observers from the absence of disagreement. In this theory truth is inferred from a spatio-temporal pattern of statements as behavior rather than from the traditional correspondence between observation and object or logical relationships among statements.

Computer simulations of the formation and evolution of large-scale structure in the universe are integral to the enterprise of modern cosmology. Establishing the reliability of these simulations has been extremely challenging, primarily because of epistemic opacity. In this setting, robustness analysis defined by requiring converging outputs from a diverse ensemble of simulations is insufficient to determine simulation validity. We propose an alternative path of structured code validation that applies eliminative reasoning to isolate and reduce possible sources of error, a potential path that is already being explored by some cosmologists.

Bas van Fraassen in [4] has recently tried to use modal logic to solve the measurement problem of quantum mechanics. His model is based on a method of expressing quantum states developed by Hugh Everett [1] called the “relative state formulation.” Unfortunately, Everett's mathematics cannot be generalized as van Fraassen requires. The difficulty itself is elementary enough. But a revision of van Fraassen's postulates (such as the one he adopted on p. 341 after he had been told of the problem) can save the mathematics only on pain of making the whole study irrelevant to the physics. I shall explain the dilemma in this note. In a later paper [5], van Fraassen avoids this dilemma by developing an abstract modal interpretation which does not rely on any expression for quantum states.

Itamar Pitowsky's book (1989), published in the Springer-Verlag Lecture Notes in Physics series, brings together several extremely interesting component investigations concerning the foundations of quantum mechanics. All deal with issues of probability including, in one case, the relation of probability to logic. It is a significant contribution, offering both new, nontrivial mathematical results, and provocative philosophical remarks about their significance.

Recently in this journal Sherrilyn Roush (2004) defends positive relevance as a necessary (albeit not a sufficient) condition for evidence by rejecting two of the counterexamples from my earlier (2001) work. In this reply I argue that Roush's critique is not successful.

This paper is partly a tribute to Richard Jeffrey, partly a reflection on some of his writings, The Logic of Decision in particular. I begin with a brief biography and some fond reminiscences of Dick. I turn to some of the key tenets of his version of Bayesianism. All of these tenets are deployed in my discussion of his response to the St. Petersburg paradox, a notorious problem for decision theory that involves a game of infinite expectation. Prompted by that paradox, I conclude with some suggestions of avenues for future research.

Statistical decision theory, whether based on Bayesian principles or other concepts such as minimax or admissibility, relies on minimizing expected loss or maximizing expected utility. Loss and utility functions are generally treated as unit-less numerical measures of value for consequences. Here, we address the issue of the units in which loss and utility are settled and the implications that those units have on the rankings of potential decisions. When multiple currencies are available for paying the loss, one must take explicit account of which currency is used as well as the exchange rates between the various available currencies.

Will a synthesis of developmental and evolutionary biology require a focus on the role of nongenetic resources in evolution? Nongenetic variation may exist but be hidden because the phenotypes are stable (developmentally canalized) under certain background conditions. In this case, those differences may come to play important roles in evolution when background conditions change. If this is so, then a focus on the way that developmental resources are made reliable, and the ways in which reliability fails, may prove to be of crucial importance to linking developmental and evolutionary biology.

Jonah N. Schupbach and Jan Sprenger have proposed conditions of adequacy for measures of explanatory power. They derive and defend a measure of explanatory power satisfying their conditions of adequacy. This article furthers the development of their measure. The requirement that the measure be multidimensional analytic (in the sense of the mathematics of several complex variables) is avoided. Several proofs are simplified, and gaps in proofs are filled.

Scientists are becoming increasingly aware of a “replicability crisis” in the behavioral, social, and biomedical sciences. Researchers have made progress identifying statistical and methodological causes of the crisis. However, the social structure of science is also to blame. In the fields affected by the crisis, nobody is explicitly responsible and rewarded for doing confirmation and replication work. This article makes the case for a social structural reform to address the problem. I argue that we need to establish a reward system that supports a dedicated group of confirmation researchers and formulate a proposal that would achieve this.