: Bayesians and error statisticians have relied heavily upon examples from physics in developing their accounts of scientific inference. The present essay demonstrates it is possible to analyze H.B.D. Kettlewell's classic study of natural selection from Deborah Mayo's error statistical point of view (Mayo 1996). A comparison with a previous analysis of this episode from a Bayesian perspective (Rudge 1998) reveals that the error statistical account makes better sense of investigations such as Kettlewell's because it clarifies how core elements in (...) the design of experiments are used to minimize erroneous inferences rather than dwelling on whether the strategies used are reasonable. (shrink)

: Where there are cases of underdetermination in scientific controversies, such as the case of the molecular clock, scientists may direct the course and terms of dispute by playing off the multidimensional framework of theory evaluation. This is because assessment strategies themselves are underdetermined. Within the framework of assessment, there are a variety of trade-offs between different strategies as well as shifting emphases as specific strategies are given more or less weight in assessment situations. When a strategy is underdetermined, scientists (...) can change the dynamics of a controversy by making assessments using different combinations of evaluation strategies and/or weighting whatever strategies are in play in different ways. Following an underdetermination strategy does not end or resolve a scientific dispute. Consequently, manipulating underdetermination is a feature of controversy dynamics and not controversy closure. (shrink)

Science is about conceptualizing the natural world in a way that can be understood by human beings while at the same time reflecting as much as possible what we can empirically infer about how the world actually is. Among the crucial tools that allow scientists to formulate hypotheses and to contribute to a progressive understanding of nature are the use of imagery and metaphors, on the one hand, and the ability to assume certain starting points on which to build new (...) avenues of inquiry on the other hand. The premise of this work is that, in the words of philosopher of science Daniel Dennett, "There is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination." The purpose here is precisely to examine some of this philosophical baggage, and to see where such analysis may lead us. Obviously, it is not possible for a single project to take on science as a whole, or even an entire discipline such as physics, or ecology. Therefore, the core of this work is constituted by a series of eight case studies drawn from the field of evolutionary biology, with which I am particularly familiar as a practicing biologist. The hope is that combining expertise in both philosophy and science in one person, the resulting insights might be useful for the practicing scientist as well as because of their value as philosophical inquires. The dissertation is a combination of conceptual analysis and science criticism applied to specific questions in organismal biology, largely of an evolutionary nature, with the eight case studies grouped into three broad categories: Unexamined Baggage, Bad Habits, and Good and bad metaphors. (shrink)

Population genetics attempts to measure the influence of the causes of evolution, viz., mutation, migration, natural selection, and random genetic drift, by understanding the way those causes change the genetics of populations. But how does it accomplish this goal? After a short introduction, we begin in section (2) with a brief historical outline of the origins of population genetics. In section (3), we sketch the model theoretic structure of population genetics, providing the flavor of the ways in which population genetics (...) theory might be understood as incorporating causes. In sections (4) and (5) we discuss two specific problems concerning the relationship between population genetics and evolutionary causes, viz., the problem of conceptually distinguishing natural selection from random genetic drift, and the problem of interpreting fitness. In section (6), we briefly discuss the methodology and key epistemological problems faced by population geneticists in uncovering the causes of evolution. Section (7) of the essay contains concluding remarks. (shrink)

: This paper explores the calibration of laboratory models in population genetics as an experimental strategy for justifying experimental results and claims based upon them following Franklin (1986, 1990) and Rudge (1996, 1998). The analysis provided undermines Coyne et al.'s (1997) critique of Wade and Goodnight's (1991) experimental study of Wright's (1931, 1932) Shifting Balance Theory. The essay concludes by further demonstrating how this analysis bears on Diamond's (1986) claims regarding the weakness of laboratory experiments as evidence, and further how (...) the calibration strategy fits within Lloyd's (1987, 1988) account of the confirmation of ecological and evolutionary models. (shrink)

Prediction is more than testing established theory by examining whether the prediction matches the data. To show this, I examine the practices of a community of scientists, known as threaders, who are attempting to predict the final, folded structure of a protein from its primary structure, i.e., its amino acid sequence. These scientists employ a careful and deliberate methodology of prediction. A key feature of the methodology is calibration. They calibrate in order to construct better models. The construction leads to (...) knowledge of how to construct or build an object. Thus, prediction serves a cognitive goal of model construction and not just model or theory testing. The kind of knowledge that results is relevantly different than theoretical knowledge. (shrink)