Biologists in many different fields of research give how-possibly explanations of the phenomena they study. Although such explanations lack empirical support, and might be regarded by some as unscientific, they play an important heuristic role in biology by helping biologists develop theories and concepts and suggesting new areas of research. How-possibly explanations serve as a useful framework for conducting research in the absence of adequate empiri cal data, and they can even become how-actually explanations if they gain enough (...) empirical support. (shrink)

A common view of how-possibly explanations in biology treats them as explanatorily incomplete. In addition to this interpretation of how-possibly explanation, I argue that there is another interpretation, one which features what I term “explanatory strategies.” This strategy-centered interpretation of how-possibly explanation centers on there being a different explanatory context within which how-possibly explanations are offered. I contend that, in conditions where this strategy context is recognized, how-possibly explanations can be understood as complete (...) explanations. I defend this alternative interpretation by analyzing the explanatory value of simple physical models the nineteenth century developmental biologist Wilhelm His constructed for animal development. (shrink)

A primary goal of quantum computer science is to find an explanation for the fact that quantum computers are more powerful than classical computers. In this paper I argue that to answer this question is to compare algorithmic processes of various kinds and to describe the possibility spaces associated with these processes. By doing this, we explain how it is possible for one process to outperform its rival. Further, in this and similar examples little is gained in subsequently asking (...) a how-actually question. Once one has explained how-possibly, there is little left to do. (shrink)

The notion of how-possibly explanations emerged with William Dray in response to Carl Hempel’s influential deductive-nomological model of scientific explanation. Dray’s aim was to distinguish explanations of states of affairs that might occur, in contrast to the aim of D-N explanations working to establish that states of affairs must actually occur. More recently, interest in how-possibly explanations has been particularly keen among philosophers of biology. One of the concerns philosophers of biology have focused on is whether how- (...) class='Hi'>possibly explanations are “complete” explanations. Dray considered how-possibly explanations to be complete explanations, but the view that they are incomplete explanations became prominent with Robert Brandon’s articulation of successful adaptation explanation in evolutionary biology. According to Brandon, how-possibly adaptation explanations are incomplete, since they lack the requisite empirical evidence. Moreover, Brandon’s characterization of how-possibly explanation can be seen as having set the stage for thinking broadly about how-possibly explanations in biology. Echoing Brandon’s account for adaptation explanations, for example, David Resnik contends that how-possibly explanations are inherently incomplete, and yet they serve an important heuristic role throughout biology by setting out an agenda for future research. (shrink)

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly (...) and how-actually explanations. Whereas how-possibly explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims. (shrink)

‘Possibilist Explanation’ is a promising account of scientific explanation which avoids the familiar problems of “how-possibly explanations”. It explains an event by showing how-actually it was epistemically possible, instead of why it was epistemically necessary. Its explanandum is the epistemic possibility of an actual event previously considered epistemically impossible. To define PE, two new concepts are introduced: ‘permissive condition’ and ‘possibilist law’. A permissive condition for an event is something that does not entail the event itself, but (...) a necessary condition for it. A ‘Possibilist Law’ is a kind of scientific law that predicts that in the absence of a necessary condition N, the event E is not possible. Both PE and PL are legitimate and neglected parts of scientific knowledge and are especially suitable for human sciences. (shrink)

Abstract‘Possibilist Explanation’ is a promising account of scientific explanation which avoids the familiar problems of “how-possibly explanations”. It explains an event by showing how-actually it was epistemically possible, instead of why it was epistemically necessary. Its explanandum is the epistemic possibility of an actual event previously considered epistemically impossible. To define PE, two new concepts are introduced: ‘permissive condition’ and ‘possibilist law’. A permissive condition for an event is something that does not entail the event itself, but (...) a necessary condition for it. A ‘Possibilist Law’ is a kind of scientific law that predicts that in the absence of a necessary condition N, the event E is not possible. Both PE and PL are legitimate and neglected parts of scientific knowledge and are especially suitable for human sciences. (shrink)

Simulations using idealized numerical models can often generate behaviors or patterns that are visually very similar to the natural phenomenon being investigated and to be explained. The question arises, when should these model simulations be taken to provide an explanation for why the natural phenomena exhibit the patterns that they do? An important distinction for answering this question is that between ‘how-possibly’ explanations and ‘how-actually’ explanations. Despite the importance of this distinction there has been surprisingly little agreement over (...) how exactly this distinction should bedrawn. I shall argue that inadequate attention has been paid to the different contexts in which an explanation can be given and the different levels of abstraction at which the explanandum phenomenon can be framed. By tracing how scientists are using model simulations to explain a striking periodic banding of vegetation known as tiger bush, I will show how our understanding of the distinction between how-possibly and how-actually model explanations needs to be revised. (shrink)

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the (...) view that formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the (...) view that formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Explaining how something is possible is a familiar and epistemically important achievement in both science and ordinary life. But a satisfactory general account of how-possibly explanation has not yet been given. A crucial desideratum for a successful account is that it must differentiate a demonstration that something is possible from an explanation of how it is possible. In this paper, I offer an account of how-possibly explanation that fully captures this distinction. I motivate my account (...) using two cases, one from ordinary life and one from ornithology. On my account, a how-possibly explanation is a greater achievement than a mere description of how a state of affairs might possibly obtain. In addition to being a potential explanation of why some state of affairs actually obtains, a how-possibly explanation must involve the relief of an imaginative frustration on the part of its recipient. When a recipient’s imaginative frustration is relieved, she does not just know that the state of affairs in question is possible, but is also able to imagine how it could possibly obtain. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in (...) contradiction. The second variety offers a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

Some years ago, in the course of a general critique of what has sometimes been referred to as the covering law theory of explanation, I made the claim that perfectly satisfactory explanations can often be provided by indicating only one or a few necessary conditions, where we remain ignorant of the sufficient conditions, of what we nevertheless claim to understand. What seemed to me one identifiable type of such explanations I called “explaining how-possibly,” because it was a type (...) more naturally given in response to the question how it could be that a certain thing happened than to the more familiar question why it did so. In the present paper I propose to review certain objections to this thesis which have come to my attention in the interval, and to make such concessions as these seem to require. In fact, the concessions will be minor, since the general thesis still seems to me quite defensible. (shrink)

That biology provides explanations is not open to doubt. But how it does so must be a vexed question for those who deny that biology embodies laws or other generalizations with the sort of explanatory force that the philosophy of science recognizes. The most common response to this problem has involved redefining law so that those grammatically general statements which biologists invoke in explanations can be counted as laws. But this terminological innovation cannot identify the source of biology's explanatory power. (...) I argue that because biological science is historical, the problem of biological explanation can be assimilated to the parallel problem in the philosophy of history, and that the problem was solved by Carl Hempel. All we need to do is recognize that the only laws that biology—in all its compartments from the molecular onward—has or needs are the laws of natural selection. (shrink)

In this paper, we explore different possible explanations for research misconduct (especially falsification and fabrication), and investigate whether they are compatible. We suggest that to explain research misconduct, we should pay attention to three factors: (1) the beliefs and desires of the misconductor, (2) contextual affordances, (3) and unconscious biases or influences. We draw on the three different narratives (individual, institutional, system of science) of research misconduct as proposed by Sovacool to review six different explanations. Four theories start from the (...) individual: Rational Choice theory, Bad Apple theory, General Strain Theory and Prospect Theory. Organizational Justice Theory focuses on institutional factors, while New Public Management targets the system of science. For each theory, we illustrate the kinds of facts that must be known in order for explanations based on them to have minimal plausibility. We suggest that none can constitute a full explanation. Finally, we explore how the different possible explanations interrelate. We find that they are compatible, with the exception of explanations based on Rational Choice Theory and Prospect Theory respectively, which are incompatible with one another. For illustrative purposes we examine the case of Diederik Stapel. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). (...) Either there is nothing that unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible. Others suggest that there is a set of necessary features that can unify all explanations under a single account Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock’s dilemma. (shrink)

Nancy Cartwright argues that so-called capacities, not universal laws of nature, best explain the often complex way events actually unfold. On this view, science would represent a world that is fundamentally "dappled", or disunified, and not, as orthodoxy would perhaps have it, a world unified by universal laws of nature. I argue, first, that the problem Cartwright raises for laws of nature seems to arise for capacities too, so why reject laws of nature? Second, that in so far as there (...) is a problem, it concerns the role of counterfactuals in explanation; I then briefly propose a simple model of counterfactual explanation. Finally, I investigate how a sophisticated version of the regularity theory of laws of nature (that of Ramsey-Lewis) can be neutral between the empirical hypotheses that the world is unified, and that the world is disunified. (shrink)

In scientific explanations, the explanans theory is sometimes incommensurable with the explanandum empirical data. How is this possible, especially when the explanation is deductive in nature? This paper attempts to solve the puzzle without relying on any particular theory of reference. For us, it is rather obvious that the geometric idea of projection plays a key role in Keplers explanation of Tycho Brahes empirical data. We discover that a similar mechanism operates in theoretic explanations in general. In short, (...) all theoretic explanations are projective explanations. If so, there should be no logical reason why explanans theories cannot be incommensurable with explanandum data. For illustration, we analyse Einsteins explanation of the results of the Michelson–Morley experiment in some detail. (shrink)

Theories of explanation in the social sciences vacillate between holism and individualism. This book contends that this has been a consequence of theories of rationality which assume that rationality requires coherent theories to be shown to be true. It claims that traditional explanations place unrealistic demands on individuals and institutions.

One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding. While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it (...) on the basis of theoretical models that provide how-possibly explanations. These models, while they do not explain in the strict sense, afford understanding. In response, I propose an alternative epistemology of understanding, broad KAU, that takes cases of theoretical modelling into account. (shrink)

Graphical AbstractThe hiccup may have evolved to remove swallowed air from the stomach, which may help suckling mammals to consume more milk.

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The (...) experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: the performance of the minority of participants who did not find boundedly optimal adaptations, and the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training. (shrink)

This paper evaluates the potentials of Mullā Şadrā’s philosophy to explain the possibility of the Islamization of philosophy. This contributes to a more general, yet controversial, project in post-revolutionary Iran, namely the Islamization of knowledge, especially in the humanities. If there would be a mechanism through which Islamization of philosophy – as a historical example and as a field of knowledge that provides theoretical grounds of other humanities – can be plausibly explained, then one might think of Islamizing the humanities, (...) as well. One famous explanation in Iran is based on the distinction between contexts of discovery and justification. It explains how a philosopher is permitted to use the Islamic content in the context of discovery – not justification – and how this helps to Islamize philosophy. In this article, we claim a new explanation which is based on Mullā Şadrā’s transcendent philosophy. Such a philosophical explanation not only acknowledges using the Qur’an and authentic narrations in the context of discovery but also necessitates involving revelation as a philosophical criterion in the context of justification and a highly valid epistemic source in producing the new philosophical content. This provides a strong account of the Islamization of philosophy. (shrink)

Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for (...) a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden‘s (this issue) “self-organized criticality”.? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. (shrink)

Mental health legislation that requires patients to accept ‘care’ has come under increasing scrutiny, prompted primarily by a human rights ethic. Epistemic issues in mental health have received some attention, however, less attention has been paid to the possible epistemic problems of mental health legislation existing. In this manuscript, we examine the epistemic problems that arise from the presence of such legislation, both for patients without a prior experience of being detained under such legislation and for those with this experience. (...) We also examine how the doctor is legally obligated to compound the epistemic problems by the knowledge they prioritise and the failure to generate new knowledge. Specifically, we describe the problems of testimonial epistemic injustice, epistemic silencing, and epistemic smothering, and address the possible justification provided by epistemic paternalism. We suggest that there is no reasonable epistemic justification for mental health legislation that creates an environment that fundamentally unbalances the doctor–patient relationship. Significant positive reasons to counterbalance this are needed to justify the continuation of such legislation. (shrink)

The concept of developmental constraint was at the heart of developmental approaches to evolution of the 1980s. While this idea was widely used to criticize neo-Darwinian evolutionary theory, critique does not yield an alternative framework that offers evolutionary explanations. In current Evo-devo the concept of constraint is of minor importance, whereas notions as evolvability are at the center of attention. The latter clearly defines an explanatory agenda for evolutionary research, so that one could view the historical shift from ‘developmental constraint’ (...) towards ‘evolvability’ as the move from a concept that is a mere tool of criticism to a concept that establishes a positive explanatory project. However, by taking a look at how the concept of constraint was employed in the 1980s, I argue that developmental constraint was not just seen as restricting possibilities (‘constraining’), but also as facilitating morphological change in several ways. Accounting for macroevolutionary transformation and the origin of novel form was an aim of these developmental approaches to evolution. Thus, the concept of developmental constraint was part of a positive explanatory agenda long before the advent of Evo-devo as a genuine scientific discipline. In the 1980s, despite the lack of a clear disciplinary identity, this concept coordinated research among paleontologists, morphologists, and developmentally inclined evolutionary biologists. I discuss the different functions that scientific concepts can have, highlighting that instead of classifying or explaining natural phenomena, concepts such as ‘developmental constraint’ and ‘evolvability’ are more important in setting explanatory agendas so as to provide intellectual coherence to scientific approaches. The essay concludes with a puzzle about how to conceptually distinguish evolvability and selection. (shrink)

This study considers the verisimilitude of the harvest saying in Matthew 9.37–38 and Luke (Q) 10.2, specifically the opening statement that the harvest is plentiful but the workers few. By ‘verisimilitude’ is meant the tradition’s tendency to be viewed as realistic in its original socio-historical context. In other words, would the first listeners have nodded their heads in agreement at the claim that the harvest is plentiful but the workers few? The focus here is not on the logion’s possible metaphorical (...) application, but on the literal saying, which involves ancient agriculture. To address the verisimilitude question, the study will consider some individual features of the logion itself, as well as the socio-historical context of farming and harvesting in 1st-century Palestine and the Roman Empire. Contribution: This study attempts to determine the verisimilitude of the literal claim that the harvest is plentiful but the workers few. The author is not aware of any other study that attempts to answer this verisimilitude question about Matthew 9.37–38 and Luke (Q) 10.2. Answering this question is sure to contribute to the understanding and interpretation of the chosen logion in the future. (shrink)

Freezing of gait can cause reduced independence and quality of life for many with Parkinson’s disease. Episodes frequently occur at points of transition such as navigating a doorway. Therapeutic interventions, i.e., drugs and exercise, do not always successfully mitigate episodes. There are several different, but not exclusive causes for freezing of gait. People with freezing of gait are able to navigate dynamic situations like stairways by utilizing a different attentional strategy to over-ground walking, but may freeze when passing through a (...) doorway. The question is, is it possible to employ a special attentional strategy to prevent freezing at this point? Motor imagery allows for learning motor skills in absolute safety and has been widely employed in a variety of populations, including other neuro-compromised groups. Motor imagery is not studied in a homologous manner in people with Parkinson’s Disease, leading to conflicting results, but may have the potential to establish a different attentional strategy which allows a subject to mitigate freezing of gait episodes. This paper will identify and discuss the questions that still need to be answered in order to consider this approach i.e., can this population access motor imagery, can motor imagery alter the attentional strategy employed when moving through doorways, what is the best motor imagery approach for people with Parkinson’s Disease and freezing of gait, and what dosage is most effective, while briefly outlining future research considerations. (shrink)

Scientists regularly make possibility claims. While philosophers of science are well aware of the distinction between epistemic and objective notions of possibility, we believe that they often fail to apply this distinction in their analyses of scientific practices that employ modal concepts. We argue that heeding this distinction will help further progress in current debates in the philosophy of science, as it shows that the debaters talk about different things, rather than disagree on the same issue. We first discuss how (...) the two notions differ with respect to their epistemology and show that these differences are sometimes ignored in the philosophy of science. We then revisit four current philosophy of science debates about modelling, that are framed in modal terms, to showcase how the distinction significantly clarifies these debates and thereby and helps advance them. (shrink)

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from "geometry of motion" with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.

If a person is competent to consent to a treatment, is that person necessarily competent to refuse the very same treatment? Risk relativists answer no to this question. If the refusal of a treatment is risky, we may demand a higher level of decision-making capacity to choose this option. The position is known as asymmetry. Risk relativity rests on the possibility of setting variable levels of competence by reference to variable levels of risk. In an excellent 2016 article inJournal of (...) Medical Ethics(JME), Rob Lawlor defends asymmetry of this kind by defending risk relativity, using and developing arguments and approaches found in earlier work such as that of Wilks. He offers what we call the two-scale approach: a scale of risk is to be used to set a standard of competence on a scale of decision-making difficulty. However, can this be done in any rational way? We argue it cannot, and in this sense, and to this extent, risk relativity is a nonsense. (shrink)

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from ‘geometry of motion’ with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.

The regulation of chemicals is undergoing drastic changes with the use of computational models to predict environmental toxicity. This particular issue has not attracted much attention, despite its major impacts on the regulation of chemicals. This raises the problem of causality at the crossroads between data and regulatory sciences, particularly in the case models known as quantitative structure–activity relationship models. This paper shows that models establish correlations and not scientific facts, and it engages anew the way regulators deal with uncertainties. (...) It does so by exploring the tension and problems raised by the possibility of causal explanation afforded by quantitative structure–activity relationship models. It argues that the specificity of predictive modelling promotes rethinking of the regulation of chemicals. (shrink)

An epistemological how-possible question asks how knowledge, or knowledge of some specific kind, is possible. Familiar epistemological how-possible questions include ‘How is knowledge of the external world possible?’, ‘How is knowledge of other minds possible?’ and ‘How is a priori knowledge possible?’ These are the three questions that I tackle in my book. In each case, I explain how and why the question arises and propose a way of answering it. The main negative claim of the book is that transcendental (...) arguments are of little use in answering how-possible questions. A transcendental demonstration of the necessity of a certain kind of knowledge does not amount to an explanation of its possibility. The main positive claim is that such questions call for what I describe as a multi-levels response. I give an account of the multi-levels approach and put it to use in explaining how various kinds of knowledge are possible.Epistemological how-possible questions are not directly concerned with whether knowledge is possible, but if we cannot explain how a certain kind of knowledge is possible then the reality of that kind of knowledge is called into question. How-possible questions are obstacle-dependent. We ask how knowledge …. (shrink)

We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of (...) rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing “levels” approaches to explanation, and to other optimality‐based modeling approaches. (shrink)

Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...) Can the fictions and falsehoods inherent in the modeling practice do real explanatory work? Do some highly abstract and mathematical models exhibit a noncausal form of scientific explanation? How can one distinguish an exploratory "how-possibly" model explanation from a genuine "how-actually" model explanation? Do modelers face tradeoffs such that a model that is optimized for yielding explanatory insight, for example, might fail to be the most predictively accurate, and vice versa? This chapter explores the various answers that have been given to these questions. (shrink)

This book develops a philosophical structure for historical explanation that resolves disputes about the scientific status of history that have persisted since the nineteenth century. It does this by showing why historical explanations must take the form of a narrative and by making their logic explicit. The books formulates a unique positive account of the logic of narrative explanations. This logic reveals how the rational evaluation of narrative explanation becomes possible. The book also develops a nonrealist (irrealist) metaphysics (...) and epistemology of history--that is, it argues that there exists no one fixed past but many pasts. It includes a novel reading of Kuhn's The Structure of Scientific Revolutions, displaying how Kuhn offers a narrative explanation of theory change in science. The book situates narrative explanations within a naturalistic framework. Naturalism regards all canons of rational inquiry as evolving and contingent. The book also argues for the general philosophical significance of historical explanation. The first four chapters defuse methodological and the metaphysical objections to narrative explanations. The final three chapters explore how narrative explanations relate to other sciences. It will be of interest to researchers in historiography, theory of history, philosophy of history, philosophy of science, philosophy of social science, and epistemology"--Provided by publisher. (shrink)

Millions of pounds are spent on educational research each year in the UK alone. By far the greatest proportion of this expenditure is on research which is thought to have practical relevance to educational problems and the vast majority of this is spent on empirical educational research, that is educational research which examines and seeks explanations for actual or proposed educational practices or the kinds of activities, institutions or policies that prepare young people for life (Pring, 2015, p. 27). Invariably, (...) the aim of such research is not merely to gain understanding of these practices, but to improve or replace them with better ones. This practical aspect of educational research exercises most commentators, although it should not be forgotten that educational research can be carried out in a relatively disinterested manner, out of intellectual curiosity (Hammersley, 2006). There are two related issues to be considered here: 1] is it possible to gain knowledge of how educational practices work?; 2] is it possible to use such knowledge to improve existing practices, replace existing ones with better ones or introduce practices which will improve the overall practice of education? In this book, both these questions will be addressed. If the answer to 1] is negative, then it is futile to address 2]. By implication then the answer to 1] will be positive. The answer to 2] will not be negative, but there are degrees of positivity attached to a positive answer and what those degrees are will be crucial to the ultimate claims of the book. It is no exaggeration to say that in recent decades educational research has undergone a crisis of confidence, particularly but not exclusively within the world of educational policymaking. Dissatisfaction has been expressed both with the quality and the usefulness of such research. Conceptual research on education tends to be regarded with some suspicion as something that is either of little practical value or which undermines existing practices. But empirical research fares little better, with scepticism expressed both about its quality (Tooley and Darby, 1998) and about its applicability (Hillage et al., 1998). More recently there have been moves to tie funding to preferred approaches to empirical research such as intervention studies and randomised control trials (RCTs) and to disseminate in accessible form what the findings of such studies are and how they are relevant to the improvement of educational practice. In the UK alone we see organisations such as the Educational Policy Institute (EPI), the Educational Endowment Foundation (EEF), and the Sutton Trust, not to mention meta-researchers Robert Slavin and John Hattie gaining a significant amount of influence in the propagation of studies of 'what works' in educational practice. One should also mention the rising interest in the deliverances of educational research from within the teaching profession, such as ResearchEd in the UK, which betoken a wish by teachers to become more active. (shrink)

Why-questions and how-possibly-questions are two common forms of explanation request. Answers to the former ones require factual assertions, but the latter ones can be answered by displaying a representation of the targeted phenomenon. However, in an extreme case, a representation could come accompanied by the assertion that it displays the only possible way a phenomenon could develop. Using several historical controversies concerning statistical modeling, it is argued that such cases must inevitably involve tacit or explicit empirical assumptions.

Robustness analysis is widespread in science, but philosophers have struggled to justify its confirmatory power. We provide a positive account of robustness by analysing some explicit and implicit uses of within and across-model robustness in evolutionary theory. We argue that appeals to robustness are usually difficult to justify because they aim to increase the likeliness that a phenomenon obtains. However, we show that robust results are necessary for explanations of phenomena with specific properties. Across-model robustness is necessary for how-possibly (...) explanations of multiply instantiated phenomena, while within-model robustness is necessary for explanations of phenomena with multiple evolutionary starting points. In such cases, the appeal of robustness is explanatory rather than confirmatory. (shrink)

Explanation in mathematics has recently attracted increased attention from philosophers. The central issue is taken to be how to distinguish between two types of mathematical proofs: those that explain why what they prove is true and those that merely prove theorems without explaining why they are true. This way of framing the issue neglects the possibility of mathematical explanations that are not proofs at all. This paper addresses what it would take for a non-proof to explain. The paper focuses (...) on a particular example of an explanatory non-proof: an argument that mathematicians regard as explaining why a given theorem holds regarding the derivative of an infinite sum of differentiable functions. The paper contrasts this explanatory non-proof with various non-explanatory proofs of the same theorem. The paper offers an account of what makes the given non-proof explanatory. This account is motivated by investigating the difficulties that arise when we try to extend Mark Steiner’s influential account of explanatory proofs to cover this explanatory non-proof. (shrink)

This paper presents a new approach to resolving an apparent tension in Descartes’ discussion of scientific theories and explanations in the Principles of Philosophy. On the one hand, Descartes repeatedly claims that any theories presented in science must be certain and indubitable. On the other hand, Descartes himself presents an astonishing number of speculative explanations of various scientific phenomena. In response to this tension, commentators have suggested that Descartes changed his mind about scientific theories having to be certain and indubitable, (...) that he lacked the conceptual resources to describe the appropriate epistemic attitude towards speculative theories, or that the presence of geometrical principles in these explanations guarantee their certainty. I argue that none of these responses is satisfactory and suggest a different resolution to the tension by examining Descartes’ notion of explanation. On Descartes’ view, providing an adequate explanation does not require being certain of the theories that constitute the explanans. Relatedly, the purpose of Cartesian explanations is not to discover the truth about the various underlying mechanisms that such explanations appeal to, but to support his general philosophical thesis that all natural phenomena can be explained by appealing to the extension of matter. (shrink)

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from “geometry of motion” with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.