one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

This is an important book precisely because there is none other quite like it.

In a new introduction, the authors describe how science and its social context were understood when this book was first published, and how the study of the history of science has changed since then.

It is common to assume that the problem of induction arises only because of small sample sizes or unreliable data. In this paper, I argue that the piecemeal collection of data can also lead to underdetermination of theories by evidence, even if arbitrarily large amounts of completely reliable experimental and observational data are collected. Specifically, I focus on the construction of causal theories from the results of many studies (perhaps hundreds), including randomized controlled trials and observational studies, where the studies (...) focus on overlapping, but not identical, sets of variables. Two theorems reveal that, for any collection of variables V, there exist fundamentally different causal theories over V that cannot be distinguished unless all variables are simultaneously measured. Underdetermination can result from piecemeal measurement, regardless of the quantity and quality of the data. Moreover, I generalize these results to show that, a priori, it is impossible to choose a series of small (in terms of number of variables) observational studies that will be most informative with respect to the causal theory describing the variables under investigation. This final result suggests that scientific institutions may need to play a larger role in coordinating differing research programs during inquiry. (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)

Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter’s regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable in ideal evidential circumstances (i.e., (...) when evidence is concordant), often when a variety of evidence is available from multiple techniques, the evidence is discordant. †To contact the author, please write to: Jacob Stegenga, Department of Philosophy, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093; e‐mail: [email protected]. (shrink)

With this manifesto, John Dupré systematically attacks the ideal of scientific unity by showing how its underlying assumptions are at odds with the central conclusions of science itself.

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (shrink)

This 1983 book is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about (...) realism. Hacking illustrates how experimentation often has a life independent of theory. He argues that although the philosophical problems of scientific realism can not be resolved when put in terms of theory alone, a sound philosophy of experiment provides compelling grounds for a realistic attitude. A great many scientific examples are described in both parts of the book, which also includes lucid expositions of recent high energy physics and a remarkable chapter on the microscope in cell biology. (shrink)

A small consortium of philosophers has begun work on the implications of epistemic networks (Zollman 2008 and forthcoming; Grim 2006, 2007; Weisberg and Muldoon forthcoming), building on theoretical work in economics, computer science, and engineering (Bala and Goyal 1998, Kleinberg 2001; Amaral et. al., 2004) and on some experimental work in social psychology (Mason, Jones, and Goldstone, 2008). This paper outlines core philosophical results and extends those results to the specific question of thresholds. Epistemic maximization of certain types does show (...) clear threshold effects. Intriguingly, however, those effects appear to be importantly independent from more familiar threshold effects in networks. (shrink)

Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence —when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a (...) sufficient independence condition for warranting robustness arguments. We show that OI evidence can collectively confirm a hypothesis to a lower degree than individual lines of evidence, contrary to the standard assumption undergirding usual robustness arguments. We employ Bayesian networks to represent the ideal empirical scenario for a robustness argument and a variety of ways in which empirical scenarios can fall short of this ideal. (shrink)

Science is the study of our world, as it is in its messy reality. Nonetheless, science requires idealization to function—if we are to attempt to understand the world, we have to find ways to reduce its complexity. Idealization and the Aims of Science shows just how crucial idealization is to science and why it matters. Beginning with the acknowledgment of our status as limited human agents trying to make sense of an exceedingly complex world, Angela Potochnik moves on to explain (...) how science aims to depict and make use of causal patterns—a project that makes essential use of idealization. She offers case studies from a number of branches of science to demonstrate the ubiquity of idealization, shows how causal patterns are used to develop scientific explanations, and describes how the necessarily imperfect connection between science and truth leads to researchers’ values influencing their findings. The resulting book is a tour de force, a synthesis of the study of idealization that also offers countless new insights and avenues for future exploration. (shrink)

Material traces of the past are notoriously inscrutable; they rarely speak with one voice, and what they say is never unmediated. They stand as evidence only given a rich scaffolding of interpretation which is, itself, always open to challenge and revision. And yet archaeological evidence has dramatically expanded what we know of the cultural past, sometimes demonstrating a striking capacity to disrupt settled assumptions. The questions we address in Evidential Reasoning are: How are these successes realized? What gives us confidence (...) in the credibility and robustness, the trustworthiness, of the evidential claims based on archaeological data? And, what constitute best practices in building evidential claims, critically scrutinizing them and putting them to work in archaeological contexts? Rather than retreat to abstractions about how how science operates in the ideal, we approach this question by interrogating a number of close-to-the-ground case studies with the aim of teasing out the wisdom embodied in archaeological practice. The cases we consider – of fieldwork, strategies for working with old evidence, and the role of external resources – illuminate the role of various types of inferential scaffolding and bring into focus practice-grounded epistemic norms that we believe serve archaeologists better than the all-or-nothing ideals of truth and objectivity that dominate programmatic debate. (shrink)

The ecologist today finds scarce ground safe from controversy. Decisions must be made about what combination of data, goals, methods, and theories offers them the foundations and tools they need to construct and defend their research. When push comes to shove, ecologists often turn to philosophy to justify why it is their approach that is scientific. Karl Popper’s image of science as bold conjectures and heroic refutations is routinely enlisted to justify testing hypotheses over merely confirming them. One of the (...) most controversial theories in contemporary science is the Neutral Theory of Ecology. Its chief developer and proponent, Stephen Hubbell, presents the neutral theory as a bold conjecture that has so far escaped refutation. Critics of the neutral theory claim that it already stands refuted, despite what the dogmatic neutralists say. We see the controversy through a Popperian lens. But Popper’s is an impoverished philosophy of science that distorts contemporary ecology. -/- The controversy surrounding the neutral theory actually rests on a methodological fault. There is a strong but messy historical link between the concepts of being neutral and being null in biology, and Hubbell perpetuates this when he claims that the neutral theory is supplies the appropriate null for testing alternative theories. What method is being followed here? There are three contenders: -/- Null hypothesis testing tests for whether a there is a pattern to be explained. Null modeling tests for whether a process is causally relevant to a pattern. Baseline modeling apportions relative responsibility to multiple processes each relevant to a pattern. -/- Whether the neutral theory supplies an appropriate “null” depends upon whether null hypothesis, null modeling, or baseline model is intended. These methods prescribe distinct inference patterns. If they are null hypothesis testing or null modeling, the neutralists’s reasoning is invalid. If they are baseline modeling, the justification of a crucial assumption remains opaque. Either way, the neutral-null connection is being exploited rhetorically to privilege the neutral theory over its rivals. Clarifying the reasoning immunizes us against the rhetoric and foregrounds the underlying virtues of the neutralist approach to ecology. -/- The Popperian lens distorts theoretical development as dogmatism. Lakatos’s view of science as the development of research programmes clarifies the epistemology of the neutral theory. Focusing philosophical attention on the neutralist research programme illuminates (1) the synchronic uses of the neutral theory to make predictions and give descriptions and explanations; (2) its diachronic development in response to theoretical innovation and confrontation with data; (3) its complex relationships to alternative theories. For example, baseline modeling is now seen to be its primary explanatory heuristic. The justification for baseline modeling with the neutral theory, previously hidden from view, is seen in the logic of in the neutralist research programme. (shrink)

This article examines the effect of material evidence upon historiographic hypotheses. Through a series of successive Bayesian conditionalizations, I analyze the extended competition among several hypotheses that offered different accounts of the transition between the Bronze Age and the Iron Age in Palestine and in particular to the “emergence of Israel”. The model reconstructs, with low sensitivity to initial assumptions, the actual outcomes including a complete alteration of the scientific consensus. Several known issues of Bayesian confirmation, including the problem of (...) old evidence, the introduction and confirmation of novel theories and the sensitivity of convergence to uncertain and disputed evidence are discussed in relation to the model’s result and the actual historical process. The most important result is that convergence of probabilities and of scientific opinion is indeed possible when advocates of rival hypotheses hold similar judgment about the factual content of evidence, even if they differ sharply in their historiographic interpretation. This speaks against the contention that understanding of present remains is so irrevocably biased by theoretical and cultural presumptions as to make an objective assessment impossible. (shrink)

Our epistemic access to the past is infamously patchy: historical information degrades and disappears and bygone eras are often beyond the reach of repeatable experiments. However, historical scientists have been remarkably successful at uncovering and explaining the past. I argue that part of this success is explained by the exploitation of dependencies between historical events, entities, and processes. For instance, if sauropod dinosaurs were hot blooded, they must have been gluttons; the high-energy demands of endothermy restrict sauropod grazing strategies. Understanding (...) such dependencies extends our reach into the past in spite of incomplete data. In addition, this serves as a counterexample to two accounts of method in the historical sciences. By one, historical science proceeds by identifying ‘smoking guns’: traces that discriminate between live hypotheses. By the other, historical hypotheses are supported by consilience: the convergence of independent lines of evidence. However, testing for ‘coherency’ between past hypotheses also plays a critical role in historical confirmation. Just as historical scientists exploit dependencies between past entities and present entities to infer what the past was like, they also exploit dependencies between past entities themselves. I do not suggest that archetypical historical science proceeds in this manner. Rather, the lesson I draw is that historical methodology cannot be characterized as archetypically relying on one method or another. Historical science is at base opportunistic, and is resistant to unitary analyses. 1 Introduction2 Snowballs and Explosions: The Basic Idea3 Were Sauropods Endothermic?4 Dependent Entities and Interdependent Explanations5 Smoking Guns and Consilience. (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)

Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied “methodological triangulation”. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than (...) it could have been by any single method. Against this, methodological purists believe that one should choose a single appropriate method and stick with it. Using tools from voting theory, we show Du Boisian methodological triangulation to be more likely to yield the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This holds even when in fact only one of the methods is appropriate for the given research question. (shrink)

In this paper I argue that we can best make sense of the practice of experimental evolutionary biology if we see it as investigating contingent, rather than lawlike, regularities. This understanding is contrasted with the experimental practice of certain areas of physics. However, this presents a problem for those who accept the Logical Positivist conception of law and its essential role in scientific explanation. I address this problem by arguing that the contingent regularities of evolutionary biology have a limited range (...) of nomic necessity and a limited range of explanatory power even though they lack the unlimited projectibility that has been seen by some as a hallmark of scientific laws. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

. Philosophers and scientists often cite ontic factors when explaining the methods and success of scientific inquiry. That is, the adoption of a method or approach is explained in reference to the kind of system in which the scientist is interested: these are explanations of why scientists do what they do, that appeal to properties of their target systems. We present a framework for understanding such “Opticks to his Principia. Newton’s optical work is largely experiment-driven, while the Principia is primarily (...) mathematical, so usually, each work is taken to exemplify a different kind of science. However, Newton himself often presented them in terms of a largely consistent method. We use our framework to articulate an original and plausible position: that the differences between the Opticks and the Principia are due to the kinds of systems targeted. That is, we provide an ontic-driven explanation of methodological differences. We suspect that ontic factors should have a more prominent role in historical explanations of scientific method and development. (shrink)

When should a scientific community be cognitively diverse? This article presents a model for studying how the heterogeneity of learning heuristics used by scientist agents affects the epistemic efficiency of a scientific community. By extending the epistemic landscapes modeling approach introduced by Weisberg and Muldoon, the article casts light on the micro-mechanisms mediating cognitive diversity, coordination, and problem-solving efficiency. The results suggest that social learning and cognitive diversity produce epistemic benefits only when the epistemic community is faced with problems of (...) sufficient difficulty. (shrink)

It is often supposed that the spectacular successes of our modern mathematical sciences support a lofty vision of a world completely ordered by one single elegant theory. In this book Nancy Cartwright argues to the contrary. When we draw our image of the world from the way modern science works - as empiricism teaches us we should - we end up with a world where some features are precisely ordered, others are given to rough regularity and still others behave in (...) their own diverse ways. This patchwork makes sense when we realise that laws are very special productions of nature, requiring very special arrangements for their generation. Combining classic and newly written essays on physics and economics, The Dappled World carries important philosophical consequences and offers serious lessons for both the natural and the social sciences. (shrink)

An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...) of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

Some scientists are happy to follow in the footsteps of others; some like to explore novel approaches. It is tempting to think that herein lies an epistemic division of labor conducive to overall scientific progress: the latter point the way to fruitful areas of research, and the former more fully explore those areas. Weisberg and Muldoon’s model, however, suggests that it would be best if all scientists explored novel approaches. I argue that this is due to implausible modeling choices, and (...) I present an alternative ‘epistemic landscape’ model that demonstrates the alleged benefits from division of labor, with one restriction. (shrink)

Historical scientists frequently face incomplete data, and lack direct experimental access to their targets. This has led some philosophers and scientists to be pessimistic about the epistemic potential of the historical sciences. And yet, historical science often produces plausible, sophisticated hypotheses. I explain this capacity to generate knowledge in the face of apparent evidential scarcity by examining recent work on Thylacoleo carnifex, the ‘marsupial lion’. Here, we see two important methodological features. First, historical scientists are methodological omnivores, that is, they (...) construct purpose-built epistemic tools tailored to generate evidence about highly specific targets. This allows them to produce multiple streams of independent evidence and thus maximize their epistemic reach. Second, investigative scaffolding: research proceeds in a piece-meal fashion, information only gaining evidential relevance once certain hypotheses are well supported. I illustrate scaffolding in a discussion of the nature of functional ascription in paleobiology. Frequently, different senses of ‘function’ are not discriminated during paleobiological investigation—something which can mar adaptationist investigations of extant organisms. However, I argue that, due to scaffolding, conflating senses of ‘function’ can be the right thing to do. Coarse-grained functional hypotheses are required before it is clear what evidence could discriminate between more fine-grained ones. I draw on omnivory and scaffolding to argue that pessimists make a bad empirical bet. It is a bad idea to bet against the epistemic fortunes of such opportunistic and resourceful scientists, especially when we have reason to think we will systematically underestimate the amount of evidence ultimately available to them. (shrink)

Contrary to formal theories of induction, I argue that there are no universal inductive inference schemas. The inductive inferences of science are grounded in matters of fact that hold only in particular domains, so that all inductive inference is local. Some are so localized as to defy familiar characterization. Since inductive inference schemas are underwritten by facts, we can assess and control the inductive risk taken in an induction by investigating the warrant for its underwriting facts. In learning more facts, (...) we extend our inductive reach by supplying more localized inductive inference schemes. Since a material theory no longer separates the factual and schematic parts of an induction, it proves not to be vulnerable to Hume's problem of the justification of induction. (shrink)

The Dappled World: A Study of the Boundaries of Science. nancy cartwright. Plato's Reception of Parmenides. john a. palmer.

How is medical knowledge made? There have been radical changes in recent decades, through new methods such as consensus conferences, evidence-based medicine, translational medicine, and narrative medicine. Miriam Solomon explores their origins, aims, and epistemic strengths and weaknesses; and she offers a pluralistic approach for the future.

Because of its complexity, contemporary scientific research is almost always tackled by groups of scientists, each of which works in a different part of a given research domain. We believe that understanding scientific progress thus requires understanding this division of cognitive labor. To this end, we present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to climb uphill in this landscape, where elevation represents the significance of the (...) results discovered by employing a research approach. We consider three different search strategies scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community as a whole influence their actions. This is compared with two social research strategies, which we call the follower and maverick strategies. Followers are biased towards what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform both of the other strategies. Finally, we show that in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains. (shrink)

Proponents of the value ladenness of science rely primarily on arguments from underdetermination or inductive risk, which share the premise that we should only consider values where the evidence runs out or leaves uncertainty; they adopt a criterion of lexical priority of evidence over values. The motivation behind lexical priority is to avoid reaching conclusions on the basis of wishful thinking rather than good evidence. This is a real concern, however, that giving lexical priority to evidential considerations over values is (...) a mistake and unnecessary for avoiding the wishful thinking. Values have a deeper role to play in science. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The vagaries of evidential reasoning in archaeology are notorious: the material traces that comprise the archaeological record are fragmentary and profoundly enigmatic, and the inferential gap that archaeologists must cross to constitute them as evidence of the cultural past is a peren­nial source of epistemic anxiety. And yet we know a great deal about the cultural past, including vast reaches of the past for which this material record is our only source of evidence. The contents of this record stand as (...) evidence only under interpretation, but however much a construct it is, archaeological evidence has a striking capacity to disrupt settled assump­tions, redirecting inquiry and expanding interpretive horizons in direc­tions no one could have anticipated. It is this capacity for constraining inference and interpretation that I am concerned to understand. I outline a model of evidential reasoning based on archaeological practice that integrates insights drawn from philosophical theories of confirmation, model building and hypothesis testing. Given growing interest in the uses of material evidence in fields that had been resolutely text-based, the archaeological principles of evidential reasoning may have much wider reach than this particular social/historical discipline. (shrink)

In his 1966 paper “The Strategy of model-building in Population Biology”, Richard Levins argues that no single model in population biology can be maximally realistic, precise and general at the same time. This is because these desirable model properties trade-off against one another. Recently, philosophers have developed Levins’ claims, arguing that trade-offs between these desiderata are generated by practical limitations on scientists, or due to formal aspects of models and how they represent the world. However this project is not complete. (...) The trade-offs discussed by Levins had a noticeable effect on modelling in population biology, but not on other sciences. This raises questions regarding why such a difference holds. I claim that in order to explain this finding, we must pay due attention to the properties of the systems, or targets modelled by the different branches of science.Keywords: Trade-offs; Population biology; Scientific models; Generality; Precision. (shrink)

The epistemology of studies addressing questions about historical and prehistorical phenomena is a subject of increasing discussion among philosophers of science. A related field of inquiry that has yet to be connected to this topic is the epistemology of climate science. Branching these areas of research, I show how variety-of-evidence reasoning accounts for scientific inferences about the past by detailing a case study in paleoclimate reconstruction. This analysis aims to clarify the logic of historical inquiry in general and, by focusing (...) on a case study about climate change, it offers an epistemic account of a particular discipline that is of environmental and social importance. (shrink)

The epistemology of the historical sciences has been debated recently. Cleland argued that the effects of the past overdetermine it. Turner argued that the past is underdetermined by its effects because of the decay of information from the past. I argue that the extent of over- and underdetermination cannot be approximated by philosophical inquiry. It is an empirical question that each historical science attempts to answer. Philosophers should examine how paradigmatic cases of historical science handled underdetermination or utilized overdetermination. I (...) analyze such a paradigmatic case, Darwin’s phylogenetic inferences. Darwin proceeded in three consecutive stages. The initial inference that there was some common cause of homologies was usually overdetermined. The final inference of the character traits of ancestor species was usually underdetermined. The second stage inference of the causal net that connected the species that share some common cause was inbetween. A comparison with Comparative Historical Linguistics demonstrates similar three stages of inference that move from the over- to the underdetermined. (shrink)

A Bayesian account of independent evidential support is outlined. This account is partly inspired by the work of C. S. Peirce. I show that a large class of quantitative Bayesian measures of confirmation satisfy some basic desiderata suggested by Peirce for adequate accounts of independent evidence. I argue that, by considering further natural constraints on a probabilistic account of independent evidence, all but a very small class of Bayesian measures of confirmation can be ruled out. In closing, another application of (...) my account to the problem of evidential diversity is also discussed. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)