Narrative possibility and narrative explanation

Narratives are about not only what actually happened, but also what might have. And narrative explanations make productive use of these unrealized possibilities. I discuss narrative explanation as a form of counterfactual, difference-making explanation, with a demanding qualification: the counterfactual conditions are historically or narratively (not merely logically or physically) possible. I consider these issues in connection with literary, historical and scientific narratives.     

Narrative constructs in modern clinical case reporting

Modern clinical case reporting takes the form of problem-solution narratives that redescribe symptoms in terms of disease categories. Authored almost always by those who have played a part in the medical assessment of the patient, reports historicise the salient details of an individual's illness as a complex effect of identifiable antecedent causes. Candidate hypotheses linking illness to pathological mechanisms are suggested by the patient’s experience, and by data that emerge from clinical examination and investigation. Observational and interpretive statements from these considerations are fitted into a temporally inflected account of the patient’s medical condition, configured from the vantage point of hindsight. Drawing on established forms of deferred telling, readers are invited to follow a story that drip-feeds a mixture of contingent and non-incidental information into the account, which engenders and frustrates curiosity, creates expectations, and challenges powers of reasoning and pattern recognition. Whereas case reporting once favoured memoir, the sentimental tale and eccentric biography as the means by which its historical narrative was cast, the preferred genres of contemporary case reporting include detective fiction, and puzzle and riddle narratives, formats that conceptualise the medical consultation in narrow problem-solution terms.     

Process tracing in political science: What's the story?

Methodologists in political science have advocated for causal process tracing as a way of providing evidence for causal mechanisms. Recent analyses of the method have sought to provide more rigorous accounts of how it provides such evidence. These accounts have focused on the role of process tracing for causal inference and specifically on the way it can be used with case studies for testing hypotheses. While the analyses do provide an account of such testing, they pay little attention to the narrative elements of case studies. I argue that the role of narrative in case studies is not merely incidental. Narrative does cognitive work by both facilitating the consideration of alternative hypotheses and clarifying the relationship between evidence and explanation. I consider the use of process tracing in a particular case (the Fashoda Incident) in order to illustrate the role of narrative. I argue that process tracing contributes to knowledge production in ways that the current focus on inference tends to obscure.     

Project knowledge and its resituation in the design of research projects: Seymour Benzer's behavioral genetics, 1965-1974

The article introduces a framework for analyzing the knowledge that researchers draw upon when designing a research project by distinguishing four types of “project knowledge”: goal knowledge, which concerns possible outcomes, and three forms of implementation knowledge that concern the realization of the project: 1) methodological knowledge that specifies possible experimental and non-experimental strategies to achieve the chosen goal; 2) representational knowledge that suggests ways to represent data, hypotheses, or outcomes; and 3) organizational knowledge that helps to build or navigate the material and social structures that enable a project. In the design of research projects such knowledge will be transferred from other successful projects and these processes will be analyzed in terms of modes of resituating knowledge. The account is developed by analyzing a case from the history of biology. In a reciprocal manner, it enables a better understanding of the historical episode in question: around 1970, several researchers who had made successful careers in the emerging field of molecular biology, working with bacterial model systems, attempted to create a molecular biology of the physiological processes in multicellular organisms. One of them was Seymour Benzer, who designed a research project addressing the physiological processes underlying behavior in Drosophila.     

Collaborative explanation and biological mechanisms

This paper motivates and outlines a new account of scientific explanation, which I term ‘collaborative explanation.’ My approach is pluralist: I do not claim that all scientific explanations are collaborative, but only that some important scientific explanations are—notably those of complex organic processes like development. Collaborative explanation is closely related to what philosophers of biology term ‘mechanistic explanation’ (e.g., Machamer et al., Craver, 2007). I begin with minimal conditions for mechanisms: complexity, causality, and multilevel structure. Different accounts of mechanistic explanation interpret and prioritize these conditions in different ways. This framework reveals two distinct varieties of mechanistic explanation: causal and constitutive. The two have heretofore been conflated, with philosophical discussion focusing on the former. This paper addresses the imbalance, using a case study of modeling practices in Systems Biology to reveals key features of constitutive mechanistic explanation. I then propose an analysis of this variety of mechanistic explanation, in terms of collaborative concepts, and sketch the outlines of a general theory of collaborative explanation. I conclude with some reflections on the connection between this variety of explanation and social aspects of scientific practice.     

Historicity and explanation

Some scientific explanations are distinctively historical. The aim of this paper is to say what gives such explanations their historical character. A secondary aim is to describe what makes an explanation a stronger or weaker historical explanation. We begin with a critical discussion of John Beatty's and Eric Desjardins' work on historicity and historical narrative. We then offer an alternative account of historical explanation that draws on the work of earlier philosophers (Gallie, Danto, Mink, and Hull). In that alternative account, we highlight four features of narrative explanation that Beatty and Desjardins underemphasize: central subjects; historical trajectories; the idea that historical narratives are known retrospectively; and criteria for determining what is a stronger or weaker historical narrative.     

Circularity,indispensability, and mathematical explanation in science

In this paper I consider the objection that the Enhanced Indispensability Argument (EIA) is circular and hence fails to support mathematical platonism. The objection is that the explanandum in any mathematical explanation of a physical phenomenon is itself identified using mathematical concepts. Hence the explanandum is only genuine if the truth of some mathematical theory is already presupposed. I argue that this objection deserves to be taken seriously, that it does sometimes undermine support for EIA, but that there is no reason to think that circularity is an unavoidable feature of mathematical explanation in science.     

Realizability and the varieties of explanation

What realization is has been convincingly presented in relation to the way we determine what counts as the realizers of realized properties. The way we explain a fact of realization includes a reference to what realization should be; therefore it informs in turn our understanding of the nature of realization. Conceptions of explanation are thereby included in the views of realization as a metaphysical property.Recently, several major views of realization such as Polger and Shapiro's or Gillett and Aizawa's, however competing, have relied on the neo-mechanicist theory of explanations (e.g,. Darden and Caver 2013), currently popular among philosophers of science. However, it has also been increasingly argued that some explanations are not mechanistic (e.g., Batterman 2009).Using an account given in Huneman (2017), I argue that within those explanations the fact that some mathematical properties are instantiated is explanatory, and that this defines a specific explanatory type called “structural explanation”, whose subtypes could be: optimality explanations (usually found in economics), topological explanations, etc. This paper thereby argues that all subtypes of structural explanation define several kinds of realizability, which are not equivalent to the usual notion of realization tied to mechanistic explanations, onto which many of the philosophical investigations are focused. Then it draws some consequences concerning the notion of multiple realizability.     

Perspectivism, inconsistent models, and contrastive explanation

It is widely recognized that scientific theories are often associated with strictly inconsistent models, but there is little agreement concerning the epistemic consequences. Some argue that model inconsistency supports a strong perspectivism, according to which claims serving as interpretations of models are inevitably and irreducibly perspectival. Others argue that in at least some cases, inconsistent models can be unified as approximations to a theory with which they are associated, thus undermining this kind of perspectivism. I examine the arguments for perspectivism, and contend that its strong form is defeasible in principle, not merely in special cases. The argument rests on the plausibility of scientific knowledge concerning non-perspectival, dispositional facts about modelled systems. This forms the basis of a novel suggestion regarding how to understand the knowledge these models afford, in terms of a contrastive theory of what-questions.     

Distinctively mathematical explanation and the problem of directionality: A quasi-erotetic solution

The increasing preponderance of opinion that some natural phenomena can be explained mathematically has inspired a search for a viable account of distinctively mathematical explanation. Among the desiderata for an adequate account is that it should solve the problem of directionality —the reversals of distinctively mathematical explanations should not count as members among the explanatory fold but any solution must also avoid the exclusion of genuine explanations. In what follows, I introduce and defend what I refer to as a quasi-erotetic solution which provides a remedy to the problem in the form of an additional necessary condition on explanation.     

Inference to the best explanation and Norton's material theory of induction

I argue that we should consider Norton's material theory of induction as consisting of two largely independent claims. First, there is the claim that material facts license inductions - a claim which I interpret as a type of contextualism about induction. Second, there is the claim that there are no universal rules of induction. While a good case can be made for the first claim, I believe that Norton's arguments for the second claim are lacking. In particular, I spell out Norton's argument against the claim that all induction may be reduced to inference to the best explanation, and argue that it is not persuasive. Rejecting this part of Norton's theory does not however require us to abandon the first claim that material facts license inductions. In this way, I distinguish the parts of the material theory of induction we should happily accept from the parts about which we should be more skeptical.     

BonJour on explanation and skepticism

Laurence BonJour, among others, has argued that inference to the best explanation allows us to reject skeptical hypotheses in favor of our common-sense view of the world. BonJour considers several skeptical hypotheses, specifically: (i) our experiences arise by mere chance, uncaused; (ii) the simple hypothesis which states merely that our experiences are caused unveridically; and (iii) an elaborated hypothesis which explains in detail how our unveridical experiences are brought about. A central issue is whether the coherence of one’s experience makes that experience more likely to be veridical. BonJour’s recent treatment of “analog” and “digital” skeptical hypotheses is also discussed. I argue that, although there are important lessons to be learned from BonJour’s writings, his use of inference to the best explanation against skepticism is unsuccessful.     

Mechanistic explanation,cognitive systems demarcation,and extended cognition

Approaches to the Internalism–Externalism controversy in the philosophy of mind often involve both (broadly) metaphysical and explanatory considerations. Whereas originally most emphasis seems to have been placed on metaphysical concerns, recently the explanation angle is getting more attention. Explanatory considerations promise to offer more neutral grounds for cognitive systems demarcation than (broadly) metaphysical ones. However, it has been argued that explanation-based approaches are incapable of determining the plausibility of internalist-based conceptions of cognition vis-à-vis externalist ones. On this perspective, improved metaphysics is the route along which to solve the Internalist–Externalist stalemate. In this paper we challenge this claim. Although we agree that explanation-orientated approaches have indeed so far failed to deliver solid means for cognitive system demarcation, we elaborate a more promising explanation-oriented framework to address this issue. We argue that the mutual manipulability account of constitutive relevance in mechanisms, extended with the criterion of ‘fat-handedness’, is capable of plausibly addressing the cognitive systems demarcation problem, and thus able to decide on the explanatory traction of Internalist vs. Externalist conceptions, on a case-by-case basis. Our analysis also highlights why some other recent mechanistic takes on the problem of cognitive systems demarcation have been unsuccessful. We illustrate our claims with a case on gestures and learning.     

Anachronism and retrospective explanation: in defence of a present-centred history of science

This paper defends the right of historians to make use of their knowledge of the remote consequences of past actions. In particular, it is argued that the disciplinary cohesion of the history of science relies crucially upon our ability to target, for further investigation, those past activities ancestral to modern science. The history of science is not limited to the study of those activities but it is structured around them. In this sense, the discipline is inherently ‘present-centred’: its boundaries are determined, in part, by judgements inaccessible to the historical actors. Present-centredness of this sort, it is urged, should not be regarded as a problem; its methodological consequences are minimal.     

Exemplification and the use-values of cases and case studies

This paper provides an account of the ‘use-value’ of case-based research by showing how social scientists exploit cases, and case studies, in a variety of practices of inference and extension. The critical basis for making such extensions relies on the power of a case, or the account given of a case (the case-study account), to exemplify certain features of the social world in ways which prove valuable for further analysis: either of the same case, or in many domains beyond the original case study. Framing use-values in terms of exemplification compares favourably with understanding reasoning beyond the case either as a form of analogical reasoning or in taking cases as experimentable objects.     

The tragedy of the canon; or,path dependence in the history and philosophy of science

We have previously argued that historical cases must be rendered canonical before they can plausibly serve as evidence for philosophical claims, where canonicity is established through a process of negotiation among historians and philosophers of science (Bolinska and Martin, 2020). Here, we extend this proposal by exploring how that negotiation might take place in practice. The working stock of historical examples that philosophers tend to employ has long been established informally, and, as a result, somewhat haphazardly. The composition of the historical canon of philosophy of science is therefore path dependent, and cases often become stock examples for reasons tangential to their appropriateness for the purposes at hand. We show how the lack of rigor around the canonization of case studies has muddied the waters in selected philosophical debates. This, in turn, lays the groundwork for proposing ways in which they can be improved.     

Big data and prediction: Four case studies

Has the rise of data-intensive science, or ‘big data’, revolutionized our ability to predict? Does it imply a new priority for prediction over causal understanding, and a diminished role for theory and human experts? I examine four important cases where prediction is desirable: political elections, the weather, GDP, and the results of interventions suggested by economic experiments. These cases suggest caution. Although big data methods are indeed very useful sometimes, in this paper's cases they improve predictions either limitedly or not at all, and their prospects of doing so in the future are limited too.     

Science, truth and history, part II. Metaphysical bolt-holes for the Sociology of Scientific Knowledge?

Historians of science have frequently sought to exclude modern scientific knowledge from their narratives. Part I of this paper, published in the previous issue, cautioned against seeing more than a literary preference at work here. In particular, it was argued—contra advocates of the Sociology of Scientific Knowledge (SSK)—that a commitment to epistemological relativism should not be seen as having straightforward historiographical consequences. Part II considers further SSK-inspired attempts to entangle the currently fashionable historiography with particular positions in the philosophy of science. None, I argue, is promising. David Bloor’s proposed alliance with scientific realism relies upon a mistaken view of contrastive explanation; Andrew Pickering’s appeal to instrumentalism is persuasive for particle physics but much less so for science as a whole; and Bruno Latour’s home-grown metaphysics is so bizarre that its compatibility with SSK is, if anything, a further blow to the latter’s plausibility.