In medicine and the social sciences, researchers must frequently integrate the findings of many observational studies, which measure overlapping collections of variables. For instance, learning how to prevent obesity requires combining studies that investigate obesity and diet with others that investigate obesity and exercise. Recently developed causal discovery algorithms provide techniques for integrating many studies, but little is known about what can be learned from such algorithms. This article argues that there are causal facts that one could learn by conducting (...) a large study but which could not be learned by combining many smaller studies. Moreover, I characterize the frequency with which combining many studies increases underdetermination and exactly how much information is lost. 1 Introduction2 Causal Inference from Observational Data3 Piecemeal Causal Inference4 The Extent and Frequency of the Problem of Piecemeal Induction5 Conclusion. (shrink)

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

This paper describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that it (...) would continue to hold under a relevant class of changes. Unlike lawfulness, invariance comes in degrees and has other features that are well suited to capture the characteristics of explanatory generalizations in the special sciences. For example, a generalization can be invariant even if it has exceptions or holds only over a limited spatio-temporal interval. The notion of invariance can be used to resolve a number of dilemmas that arise in standard treatments of explanatory generalizations in the special sciences. (shrink)

Scientists and laypeople alike use the sense of understanding that an explanation conveys as a cue to good or correct explanation. Although the occurrence of this sense or feeling of understanding is neither necessary nor sufficient for good explanation, it does drive judgments of the plausibility and, ultimately, the acceptability, of an explanation. This paper presents evidence that the sense of understanding is in part the routine consequence of two well-documented biases in cognitive psychology: overconfidence and hindsight. In light of (...) the prevalence of counterfeit understanding in the history of science, I argue that many forms of cognitive achievement do not involve a sense of understanding, and that only the truth or accuracy of an explanation make the sense of understanding a valid cue to genuine understanding. (shrink)

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

Truth is standardly considered a requirement on epistemic acceptability. But science and philosophy deploy models, idealizations and thought experiments that prescind from truth to achieve other cognitive ends. I argue that such felicitous falsehoods function as cognitively useful fictions. They are cognitively useful because they exemplify and afford epistemic access to features they share with the relevant facts. They are falsehoods in that they diverge from the facts. Nonetheless, they are true enough to serve their epistemic purposes. Theories that contain (...) them have testable consequences, hence are factually defeasible. (shrink)

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)

: The underdetermination argument establishes that scientists may use political values to guide inquiry, without providing criteria for distinguishing legitimate from illegitimate guidance. This paper supplies such criteria. Analysis of the confused arguments against value-laden science reveals the fundamental criterion of illegitimate guidance: when value judgments operate to drive inquiry to a predetermined conclusion. A case study of feminist research on divorce reveals numerous legitimate ways that values can guide science without violating this standard.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

This article examines the concept of wishful thinking in philosophical literature on science and values. It suggests that this term tends to be used in an overly broad manner that fails to distinguish between separate types of bias, mechanisms that generate biases, and general theories that might explain those mechanisms. I explain how confirmation bias is distinct from wishful thinking and why it is more useful for examining the relationship between cognitive bias and beliefs about the existence of injustices.

The `fact' of pluralism in science is nosurprise. Yet, if science is representing andexplaining the structure of the oneworld, why is there such a diversity ofrepresentations and explanations in somedomains? In this paper I consider severalphilosophical accounts of scientific pluralismthat explain the persistence of bothcompetitive and compatible alternatives. PaulSherman's `Levels of Analysis' account suggeststhat in biology competition betweenexplanations can be partitioned by the type ofquestion being investigated. I argue that thisaccount does not locate competition andcompatibility correctly. I then defend anintegrative (...) model for understanding pluralism. This view is based on taking seriously both thecomplexity and contingency of biologicalorganization and the idealized character ofbiological models. On this view, explanationbecomes, among other things, the location forthe integration of diverse models. I explicatemy argument by an analysis of explanations ofdivision of labor in social insects. (shrink)

This article critically examines a recent philosophical debate on the role of values in climate change forecasts, such as those found in assessment reports of the Intergovernmental Panel on Climate Change. On one side, several philosophers insist that the argument from inductive risk, as developed by Rudner and Douglas among others, applies to this case. AIR aims to show that ethical value judgments should influence decisions about what is sufficient evidence for accepting scientific hypotheses that have implications for policy issues. (...) Advocates of extending AIR to climate science claim that values are deeply... (shrink)

Francesco Guala once wrote that ‘The problem of extrapolation is a minor scandal in the philosophy of science’. This paper agrees with the statement, but for reasons different from Guala’s. The scandal is not, or not any longer, that the problem has been ignored in the philosophy of science. The scandal is that framing the problem as one of external validity encourages poor evidential reasoning. The aim of this paper is to propose an alternative—an alternative which constitutes much better evidential (...) reasoning about target systems of interest, and which makes do without consideration of external validity. (shrink)

Obesity is the focus of multiple lines of inquiry that have -- together and separately -- produced many deep insights into the physiology of weight gain and maintenance. We examine three such streams of research and show how they are oriented to obesity intervention through multilevel integrated approaches. The first research programme is concerned with the genetics and biochemistry of fat production, and it links metabolism, physiology, endocrinology and neurochemistry. The second account of obesity is developmental and draws together epigenetic (...) and environmental explanations that can be embedded in an evolutionary framework. The third line of research focuses on the role of gut microbes in the production of obesity, and how microbial activities interact with host genetics, development and metabolism. These interwoven explanatory strategies are driven by an orientation to intervention, both for experimental and therapeutic outcomes. We connect the integrative and intervention-oriented aspects of obesity research through a discussion of translation, broadening the concept to capture the dynamic, iterative processes of scientific practice and therapy development. This system-oriented analysis of obesity research expands the philosophical scrutiny of contemporary developments in the biosciences and biomedicine, and has the potential to enrich philosophy of science and medicine. (shrink)

Obesity is the focus of multiple lines of inquiry that have -- together and separately -- produced many deep insights into the physiology of weight gain and maintenance. We examine three such streams of research and show how they are oriented to obesity intervention through multilevel integrated approaches. The first research programme is concerned with the genetics and biochemistry of fat production, and it links metabolism, physiology, endocrinology and neurochemistry. The second account of obesity is developmental and draws together epigenetic (...) and environmental explanations that can be embedded in an evolutionary framework. The third line of research focuses on the role of gut microbes in the production of obesity, and how microbial activities interact with host genetics, development and metabolism. These interwoven explanatory strategies are driven by an orientation to intervention, both for experimental and therapeutic outcomes. We connect the integrative and intervention-oriented aspects of obesity research through a discussion of translation, broadening the concept to capture the dynamic, iterative processes of scientific practice and therapy development. This system-oriented analysis of obesity research expands the philosophical scrutiny of contemporary developments in the biosciences and biomedicine, and has the potential to enrich philosophy of science and medicine. (shrink)

Russo and Williamson claim that establishing causal claims requires mechanistic and difference-making evidence. In this article, I will argue that Russo and Williamson's formulation of their thesis is multiply ambiguous. I will make three distinctions: mechanistic evidence as type vs object of evidence; what mechanism or mechanisms we want evidence of; and how much evidence of a mechanism we require. I will feed these more precise meanings back into the Russo–Williamson thesis and argue that it is both true and false: (...) two weaker versions of the thesis are worth supporting, while the stronger versions are not. Further, my distinctions are of wider concern because they allow us to make more precise claims about what kinds of evidence are required in particular cases. (shrink)

Proponents of evidence-based medicine and some philosophers of science seem to agree that knowledge of mechanisms can help solve the problem of applying results of controlled studies to target populations (‘the problem of extrapolation’). We describe the problem of extrapolation, characterize mechanisms, and outline how mechanistic knowledge might be used to solve the problem. Our main thesis is that there are four often overlooked problems with using mechanistic knowledge to solve the problem of extrapolation. First, our understanding of mechanisms is (...) often (and arguably, likely to remain) incomplete. Secondly, knowledge of mechanisms is not always applicable outside the tightly controlled laboratory conditions in which it is gained. Thirdly, mechanisms can behave paradoxically. Fourthly, as Daniel Steel points out, using mechanistic knowledge faces the problem of the ‘extrapolator’s circle’. At the same time, when the problems with mechanistic knowledge have been addressed, such knowledge can and should be used to mitigate (nothing can entirely solve) the problem of extrapolation. (shrink)

This paper considers the applicability of standard accounts of causation to living systems. In particular it examines critically the increasing tendency to equate causal explanation with the identification of a mechanism. A range of differences between living systems and paradigm mechanisms are identified and discussed. While in principle it might be possible to accommodate an account of mechanism to these features, the attempt to do so risks reducing the idea of a mechanism to vacuity. It is proposed that the solution (...) to this problem requires the development of a philosophical account of process adequate to apply to living systems. (shrink)

A survey of models in immunology is conducted and distinct kinds of models are characterized based on whether models are material or conceptual, the distinctiveness of their epistemic purpose, and the criteria for evaluating the goodness of a model relative to its intended purpose. I argue that the diversity of models in interdisciplinary fields such as immunology reflects the fact that information about the phenomena of interest is gathered from different sources using multiple methods of investigation. To each model is (...) attached a description specifying how information about a phenomenon of interest has been acquired, highlighting points of commonality and difference between the methodological and epistemic histories of the information encapsulated in different models. These points of commonality and difference allow investigators to integrate findings from different models into more comprehensive explanatory accounts, as well as to troubleshoot anomalies and faulty accounts by going back to the original building blocks. (shrink)

The underdetermination argument establishes that scientists may use political values to guide inquiry, without providing criteria for distinguishing legitimate from illegitimate guidance. This paper supplies such criteria. Analysis of the confused arguments against value-laden science reveals the fundamental criterion of illegitimate guidance: when value judgments operate to drive inquiry to a predetermined conclusion. A case study of feminist research on divorce reveals numerous legitimate ways that values can guide science without violating this standard.