David Lewis defends the thesis of the asymmetry of overdetermination: later affairs are seldom overdetermined by earlier affairs, but earlier affairs are usually overdetermined by later affairs. Recently, Carol Cleland has argued that since the distinctive methodologies of historical science and experimental science exploit different aspects of this asymmetry, the methodology of historical science is just as good, epistemically speaking, as that of experimental science. This paper shows, first, that Cleland's epistemological conclusion does not follow from the thesis of the (...) asymmetry of overdetermination, because overdetermination is compatible with epistemic underdetermination. The paper also shows, contra Cleland, that there is at least one interesting sense in which historical science is epistemically inferior to experimental science, after all, because local underdetermination problems are more widespread in historical than in experimental science. (shrink)

Today's climate models are supported in a couple of ways that receive little attention from philosophers or climate scientists. In addition to standard 'model fit', wherein a model's simulation is compared to observational data, there is an additional type of confirmation available through the variety of instances of model fit. When a model performs well at fitting first one variable and then another, the probability of the model under some standard confirmation function, say, likelihood, goes up more than under each (...) individual case of fit alone. Thus, two instances of fit of distinct variables of a global climate model using distinct data sets considered collectively will provide stronger evidence for a model than either one of the instances considered individually. This has consequences for model robustness. Sets of models that produce robust results will, if their assumptions vary enough and they each are observationally sound, provide reasons to endorse common structures found in those models. Finally, independent empirical support for aspects and assumptions of the model provides an additional confirmational virtue for climate models, contrary to what is implied by some current philosophical writing on this topic. (shrink)

One of the first questions that paleontologists ask when they identify a large-scale trend in the fossil record (e.g., size increase, complexity increase) is whether it is passive or driven. In this article, I explore two questions about driven trends: (1) what is the underlying cause or source of the directional bias? and (2) has the strength of the directional bias changed over time? I identify two underdetermination problems that prevent scientists from giving complete answers to these two questions.

This paper offers an account of the relationship between inference and explanation in functional morphology which combines Robert Brandon's theory of adaptation explanation with standard accounts of inference to the best explanation. Inferences of function from structure, it is argued, are inferences to the best adaptation explanation. There are, however, three different approaches to the problem of determining which adaptation explanation is the best. The theory of inference to the best adaptation explanation is then applied to a case study from (...) the history of functional morphology: the case of the crested duckbilled dinosaurs. (shrink)

Many scientists believe that there is a uniform, interdisciplinary method for the prac- tice of good science. The paradigmatic examples, however, are drawn from classical ex- perimental science. Insofar as historical hypotheses cannot be tested in controlled labo- ratory settings, historical research is sometimes said to be inferior to experimental research. Using examples from diverse historical disciplines, this paper demonstrates that such claims are misguided. First, the reputed superiority of experimental research is based upon accounts of scientific methodology (Baconian inductivism (...) or falsificationism) that are deeply flawed, both logically and as accounts of the actual practices of scientists. Second, although there are fundamental differences in methodology between experimental scien- tists and historical scientists, they are keyed to a pervasive feature of nature, a time asymmetry of causation. As a consequence, the claim that historical science is methodo- logically inferior to experimental science cannot be sustained. (shrink)

In seeking general accounts of evidence, confirmation, or inference, philosophers have looked to logical relationships between evidence and hypotheses. Such logics of evidential relationship, whether hypothetico-deductive, Bayesian, or instantiationist fail to capture or be relevant to scientific practice. They require information that scientists do not generally have (e.g., an exhaustive set of hypotheses), while lacking slots within which to include considerations to which scientists regularly appeal (e.g., error probabilities). Building on my co-symposiasts contributions, I suggest some directions in which a (...) new and more adequate philosophy of evidence can move. (shrink)

To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (shrink)

The classic logical positivist account of historical explanation, putting forward what is variously called the "regularity interpretation" (#Gardiner, The Nature of Historical Explanation), the "covering law model" (#Dray, Laws and Explanation in History), or the "deductive model" (Michael #Scriven, "Truisms as Grounds for Historical Explanations"). See also #Danto, Narration and Knowledge, for further criticisms of the model. Hempel formalizes historical explanation as involving (a) statements of determining (initial and boundary) conditions for the event to be explained, and (b) statements of (...) general laws that imply that whenever events of the kind described in (a) occur, an event of the kind to be explained will take place. He admits that in practice historians rarely explain historical events in this way, but instead give only fragmentary "explanation sketches." Such sketches can, however, be "scientifically acceptable," providing it points to where "more specific statements" are to be found (351). An interesting aspect of the article is its "late" positivist, proto‑Kuhnian assertion that "the separation of 'pure description' and 'hypothetical generalization and theory construction' in empirical science is unwarranted" (356). But Hempel does not work out the wider implications of this important conclusion. It is also worth noting that he himself was not much interested in the philosophy of history; other authors took up his model and discussed it within that context. Usefully discussed by #Ricoeur, Time and Narrative, 1:112‑17. (shrink)

This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body (...) of evidence supporting hypotheses about climate change. Expanding on Staley’s (2004) distinction between evidential strength and security, and Lloyd’s (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic. (shrink)

After showing how Deborah Mayo’s error-statistical philosophy of science might be applied to address important questions about the evidential status of computer simulation results, I argue that an error-statistical perspective offers an interesting new way of thinking about computer simulation models and has the potential to significantly improve the practice of simulation model evaluation. Though intended primarily as a contribution to the epistemology of simulation, the analysis also serves to fill in details of Mayo’s epistemology of experiment.

The historical sciences, such as geology, evolutionary biology, and archaeology, appear to have no means to test hypotheses. However, on closer examination, reasoning in the historical sciences relies upon regularities, regularities that can be tested. I outline the role of regularities in the historical sciences, and in the process, blur the distinction between the historical sciences and the experimental sciences: all sciences deploy theories about the world in their investigations.

Simulation-based weather and climate prediction now involves the use of methods that reflect a deep concern with uncertainty. These methods, known as ensemble prediction methods, produce multiple simulations for predictive periods of interest, using different initial conditions, parameter values and/or model structures. This paper provides a non-technical overview of current ensemble methods and considers how the results of studies employing these methods should be interpreted, paying special attention to probabilistic interpretations. A key conclusion is that, while complicated inductive arguments might (...) be given for the trustworthiness of probabilistic weather forecasts obtained from ensemble studies, analogous arguments are out of reach in the case of long-term climate prediction. In light of this, the paper considers how predictive uncertainty should be conveyed to decision makers. (shrink)

In earlier work, I predicted that we would probably not be able to determine the colors of the dinosaurs. I lost this epistemic bet against science in dramatic fashion when scientists discovered that it is possible to draw inferences about dinosaur coloration based on the microstructure of fossil feathers (Vinther et al., 2008). This paper is an exercise in philosophical error analysis. I examine this episode with two questions in mind. First, does this case lend any support to epistemic optimism (...) about historical science? Second, under what conditions is it rational to make predictions about what questions scientists will or will not be able answer? In reply to the first question, I argue that the recent work on the colors of the dinosaurs matters less to the debate about the epistemology of historical science than it might seem. In reply to the second question, I argue that it is difficult to specify a policy that would rule out the failed bet without also being too conservative. (shrink)

The fifty entries in this _Companion_ cover the main issues in the philosophies of historiography and history, including natural history and the practices of historians. Written by an international and multi-disciplinary group of experts A cutting-edge updated picture of current research in the field Part of the renowned _Blackwell Companions_ series.

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...) models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)

Climate change fingerprint studies investigate the causes of recent climate change. I argue that these studies have much in common with Steel’s (2008) streamlined comparative process tracing, illustrating a mechanisms-based approach to extrapolation in which the mechanisms of interest are simulated rather than physically instantiated. I then explain why robustness and variety-of-evidence considerations turn out to be important for understanding the evidential value of climate change fingerprint studies.

In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...) I develop is a version of common cause explanation. Common cause explanation has long been vindicated by appealing to the principle of the common cause. Many philosophers of science (e.g., Sober and Tucker) find this principle problematic, however, because they believe that it is either purely methodological or strictly metaphysical. I defend a third possibility: the principle of the common cause derives its justification from a physically pervasive time asymmetry of causation (a.k.a. the asymmetry of overdetermination). I argue that explicating the principle of the common cause in terms of the asymmetry of overdetermination illuminates some otherwise puzzling features of the practices of historical natural scientists. (shrink)

Allan Franklin has identified a number of strategies that scientists use to build confidence in experimental results. This paper shows that Franklin's strategies have direct analogues in the context of computer simulation and then suggests that one of his strategies—the so-called 'Sherlock Holmes' strategy—deserves a privileged place within the epistemologies of experiment and simulation. In particular, it is argued that while the successful application of even several of Franklin's other strategies (or their analogues in simulation) may not be sufficient for (...) justified belief in results, the successful application of a slightly elaborated version of the Sherlock Holmes strategy is sufficient. (shrink)

FEW HEROES LOWER their sights in the prime of their lives; triumph leads inexorably on, often to destruction. Alexander wept because he had no new worlds to conquer; Napoleon, overextended, sealed his doom in the depth of a Russian winter. But Charles Darwin did not follow the Origin of Species (1859) with a general defense of natural selection or with its evident extension to human evolution (he waited until 1871 to publish The Descent of Man). Instead, he wrote his most (...) obscure work, a book entitled: On the Various Contrivances by Which British and Foreign Orchids Are Fertilized by Insects (1862). (shrink)

Experimental research is commonly held up as the paradigm of "good" science. Although experiment plays many roles in science, its classical role is testing hypotheses in controlled laboratory settings. Historical science is sometimes held to be inferior on the grounds that its hypothesis cannot be tested by controlled laboratory experiments. Using contemporary examples from diverse scientific disciplines, this paper explores differences in practice between historical and experimental research vis-à-vis the testing of hypotheses. It rejects the claim that historical research is (...) epistemically inferior. For as I argue, scientists engage in two very different patterns of evidential reasoning and, although there is overlap, one pattern predominates in historical research and the other pattern predominates in classical experimental research. I show that these different patterns of reasoning are grounded in an objective and remarkably pervasive time asymmetry of nature. (shrink)

Scientists often make surprising claims about things that no one can observe. In physics, chemistry, and molecular biology, scientists can at least experiment on those unobservable entities, but what about researchers in fields such as paleobiology and geology who study prehistory, where no such experimentation is possible? Do scientists discover facts about the distant past or do they, in some sense, make prehistory? In this book Derek Turner argues that this problem has surprising and important consequences for the scientific realism (...) debate. His discussion covers some of the main positions in philosophy of science - realism, social constructivism, empiricism, and the natural ontological attitude - and shows how they relate to issues in paleobiology and geology. His original and thought-provoking book will be of wide interest to philosophers and scientists alike. (shrink)

Scientific realism is fundamentally a view about unobservable things, events, processes, and so on, but things can be unobservable either because they are tiny or because they are past. The familiar abductive arguments for scientific realism lend more justification to scientific realism about the tiny than to realism about the past. This paper examines both the “basic” abductive arguments for realism advanced by philosophers such as Ian Hacking and Michael Devitt, as well as Richard Boyd’s version of the inference to (...) the best explanation of the success of science, and shows that these arguments provide less support to historical than to experimental realism. This is because unobservably tiny things can function both as unifiers of the phenomena and as tools for the production of new phenomena, whereas things in the past can only serve as unifiers of the phenomena. The upshot is that realists must not suppose that by presenting arguments for experimental realism they have thereby defended realism in general.Author Keywords: Author Keywords: Realism; Abduction; Historical science; Hacking; Devitt; Boyd. (shrink)

We discuss the scientific task of historical reconstruction and the problem of epistemic access. We argue that strong epistemic support for historical claims consists in the consilience of multiple independent lines of evidence, and analyze the impact hypothesis for the End-Cretaceous mass extinction to illustrate the accrual of epistemic support. Although there are elements of the impact hypothesis that enjoy strong epistemic support, the general conditions for this are strict, and help to clarify the difficulties associated with reconstructing the deep (...) past. (shrink)

This intriguing volume provides a thorough examination of the historical roots of global climate change as a field of inquiry, from the Enlightenment to the late twentieth century. Based on primary and archival sources, the book is filled with interesting perspectives on what people have understood, experienced, and feared about the climate and its changes in the past. Chapters explore climate and culture in Enlightenment thought; climate debates in early America; the development of international networks of observation; the scientific transformation (...) of climate discourse; and early contributions to understanding terrestrial temperature changes, infrared radiation, and the carbon dioxide theory of climate. But perhaps most important, this book shows what a study of the past has to offer the interdisciplinary investigation of current environmental problems. (shrink)

This paper develops a critical response to John Beatty’s recent (2006) engagement with Stephen Jay Gould’s claim that evolutionary history is contingent. Beatty identifies two senses of contingency in Gould’s work: an unpredictability sense and a causal dependence sense. He denies that Gould associates contingency with stochastic phenomena, such as drift. In reply to Beatty, this paper develops two main claims. The first is an interpretive claim: Gould really thinks of contingency has having to do with stochastic effects at the (...) level of macroevolution, and in particular with unbiased species sorting. This notion of contingency as macro-level stochasticity incorporates both the causal dependence and the unpredictability senses of contingency. The second claim is more substantive: Recent attempts by other scientists to put Gould’s claim to the test fail to engage with the hypothesis that species sorting sometimes resembles a lottery. Gould’s claim that random sorting is a significant macroevolutionary phenomenon remains an intriguing and largely untested live hypothesis about evolution. (shrink)

The Hedgehog, the Fox, and the Magister's Pox is a controversial discourse, rich with facts and observations gathered by one of the most erudite minds of our ...