How is scientific knowledge used, adapted and extended in deriving real-world systems and technological devices? This paper aims at developing a general model of "applying science" based on the Exemplar-Based Explanation (EBE) model. EBE embodies the view that a real-world system is derived not by solving theoretical laws for specific boundary conditions but by constructing the system out of previously derived systems that function as exemplars. I will discuss a number of artifacts from hydraulics and language technology, and develop an (...) instantiation of EBE which generalizes over different disciplines. I argue that engineering practice is highly cumulative: new systems are almost literally built upon and constructed out of previous systems resulting into increasingly complex wholes. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards modelbased approaches. The idea that there are simple and true laws of nature has met with objections from philosophers such as Nancy Cartwright (1983) and Paul Teller (2001), and this has made a strictly Hempelian D-N style explanation largely irrelevant to the explanatory practices of science (Hempel & Oppenheim, 1948). Much of science does not involve subsuming particular events under laws of nature. It is increasingly recognized (...) that science across the disciplines is to some degree a patchwork of scientific models, with different methods, strategies, and with varying degrees of successful prediction and explanation. And so accounts of scientific explanation have reflected this change of perspective and model-based approaches have flourished in the explanation literature (Batterman, 2002b; Bokulich, 2008; Craver, 2006; Woodward, 2003). (shrink)

This dissertation examines the significance of Johann Nikolas Tetens, a German empiricist philosopher working in the 1770's, to the theoretical philosophy of Immanuel Kant. I begin by examining Tetens' discussion of philosophical methodology in his 1775 essay \textit{Über die allgemeine speculativische Philosophie}. I make the case that Tetens' criticism of the methodology of the Scottish common sense philosophers and his subsequent attempt to incorporate what he takes to be their valuable insights into the approach of the broadly Wolffian philosophical tradition (...) provides important context for interpreting Kant's methodology in the \textit{Critique of Pure Reason}. I then examine two different cases of Tetens' applying this methodology in his 1777 text \textit{Philosophische Versuche über die menschliche Natur und ihre Entwickelung}. I argue that Tetens' discussion and critique of Humean causation in the fourth essay of the \textit{Philosophische Versuche} heavily influenced Kant's understanding of ``Hume's Problem'' and that many of the more obscure issues about the Kant-Hume relationship can be greatly clarified by giving sufficient attention to Tetens. I then examine Tetens' engagement with Thomas Reid's account of perception. I argue that Tetens' attempt to develop a representationalist account of perception which withstands Reid's objections leads him toward the view that representation requires object concepts and the problem of accounting for the origin of these concepts pushes Tetens to articulate an account of synthesis. In the final chapter, I examine Kant's proof that the real of appearances has intensive magnitude in the Anticipations of Perception. I raise several difficulties for the interpretation of the proof and then argue that Tetens' discussion of perception can provide us with the context for such a proof and the nature of the ``correspondence'' between sensation and objects. (shrink)

Causalists about explanation claim that to explain an event is to provide information about the causal history of that event. Some causalists also endorse a proportionality claim, namely that one explanation is better than another insofar as it provides a greater amount of causal information. In this chapter I consider various challenges to these causalist claims. There is a common and influential formulation of the causalist requirement – the ‘Causal Process Requirement’ – that does appear vulnerable to these anti-causalist challenges, (...) but I argue that they do not give us reason to reject causalism entirely. Instead, these challenges lead us to articulate the causalist requirement in an alternative way. This alternative articulation incorporates some of the important anti-causalist insights without abandoning the explanatory necessity of causal information. For example, proponents of the ‘equilibrium challenge’ argue that the best available explanations of the behaviour of certain dynamical systems do not appear to provide any causal information. I respond that, contrary to appearances, these equilibrium explanations are fundamentally causal, and I provide a formulation of the causalist thesis that is immune to the equilibrium challenge. I then show how this formulation is also immune to the ‘epistemic challenge’ – thus vindicating (a properly formulated version of) the causalist thesis. (shrink)

The aim of this dissertation is to clarify the debate over the explanation of quantum speedup and to submit, for the reader's consideration, a tentative resolution to it. In particular, I argue, in this dissertation, that the physical explanation for quantum speedup is precisely the fact that the phenomenon of quantum entanglement enables a quantum computer to fully exploit the representational capacity of Hilbert space. This is impossible for classical systems, joint states of which must always be representable as product (...) states. I begin the dissertation by considering, in Chapter 2, the most popular of the candidate physical explanations for quantum speedup: the many worlds explanation of quantum computation. I argue that, although it is inspired by the neo-Everettian interpretation of quantum mechanics, unlike the latter it does not have the conceptual resources required to overcome objections such as the so-called `preferred basis objection'. I further argue that the many worlds explanation, at best, can serve as a good description of the physical process which takes place in so-called network-based computation, but that it is incompatible with other models of computation such as cluster state quantum computing. I next consider, in Chapter 3, a common component of most other candidate explanations of quantum speedup: quantum entanglement. I investigate whether entanglement can be said to be a necessary component of any explanation for quantum speedup, and I consider two major purported counter-examples to this claim. I argue that neither of these, in fact, show that entanglement is unnecessary for speedup, and that, on the contrary, we should conclude that it is. In Chapters 4 and 5 I then ask whether entanglement can be said to be sufficient as well. In Chapter 4 I argue that despite a result that seems to indicate the contrary, entanglement, considered as a resource, can be seen as sufficient to enable quantum speedup. Finally, in Chapter 5 I argue that entanglement is sufficient to explain quantum speedup as well. (shrink)

One of the most unsettling problems in the history of philosophy examines how mathematics can be used to adequately represent the world. An influential thesis, stated by Eugene Wigner in his paper entitled "The Unreasonable Effectiveness of Mathematics in the Natural Sciences," claims that "the miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve." Contrary to this view, this thesis delineates and implements (...) a strategy to show that the applicability of mathematics is very reasonable indeed. I distinguish three forms of the problem of the applicability of mathematics, and focus on one I call the problem of uncanny accuracy: Given that the construction and manipulation of mathematical representations is pervaded by uncertainty, error, approximation, and idealization, how can their apparently uncanny accuracy be explained? I argue that this question has found no satisfactory answer because our rational reconstruction of scientific practice has not involved tools rich enough to capture the logic of mathematical modelling. Thus, I characterize a general schema of mathematical analysis of real systems, focusing on the selection of modelling assumptions, on the construction of model equations, and on the extraction of information, in order to address contextually determinate questions on some behaviour of interest. A concept of selective accuracy is developed to explain the way in which qualitative and quantitative solutions should be utilized to understand systems. The qualitative methods rely on asymptotic methods and on sensitivity analysis, whereas the quantitative methods are best understood using backward error analysis. The basic underpinning of this perspective is readily understandable across scientific fields, and it thereby provides a view of mathematical tractability readily interpretable in the broader context of mathematical modelling. In addition, this perspective is used to discuss the nature of theories, the role of scaling, and the epistemological and semantic aspects of experimentation. In conclusion, we argue for a method of local and global conceptual analysis that goes beyond the reach of the tools standardly used to capture the logic of science; on their basis, the applicability of mathematics finds itself demystified. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...) mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert the (...) impossibility of causal explanations from attention layers over text data. We then introduce NLP researchers to contemporary philosophy of science theories that allow robust yet non-causal reasoning in explanation, giving computer scientists a vocabulary for future research. (shrink)

In this dissertation, I construct scientifically and practically adequate moral analogs of cognitive heuristics and biases. Cognitive heuristics are reasoning “shortcuts” that are efficient but flawed. Such flaws yield systematic judgment errors—i.e., cognitive biases. For example, the availability heuristic infers an event’s probability by seeing how easy it is to recall similar events. Since dramatic events, such as airplane crashes, are disproportionately easy to recall, this heuristic explains systematic overestimations of their probability (availability bias). The research program on cognitive heuristics (...) and biases (e.g., Daniel Kahneman’s work) has been scientifically successful and has yielded useful error-prevention techniques—i.e., cognitive debiasing. I attempt to apply this framework to moral reasoning to yield moral heuristics and biases. For instance, a moral bias of unjustified differences in the treatment of particular animal species might be partially explained by a moral heuristic that dubiously infers animals’ moral status from their aesthetic features. While the basis for identifying judgments as cognitive errors is often unassailable (e.g., per violating laws of logic), identifying moral errors seemingly requires appealing to moral truth, which, I argue, is problematic within science. Such appeals can be avoided by repackaging moral theories as mere “standards-of-interest” (a la non-normative metrics of purportedly right-making features/properties). However, standards-of-interest do not provide authority, which is needed for effective debiasing. Nevertheless, since each person deems their own subjective morality authoritative, subjective morality (qua standard-of-interest and not moral subjectivism) satisfies both scientific and practical concerns. As such, (idealized) subjective morality grounds a moral analog of cognitive biases—namely, subjective moral biases (e.g., committed anti-racists unconsciously discriminating). I also argue that "cognitive heuristic" is defined by its contrast with rationality. Consequently, heuristics explain biases, which are also so defined. However, such contrasting with rationality is causally irrelevant to cognition. This frustrates the presumed usefulness of the kind, heuristic, in causal explanation. As such, in the moral case, I jettison the role of causal explanation and tailor categories solely for contrastive explanation. As such, “moral heuristic” is replaced with "subjective moral fallacy," which is defined by its contrast with subjective morality and explains subjective moral biases. The resultant subjective moral biases and fallacies framework can undergird future empirical research. (shrink)

Crime is a serious social problem, but its causes are not exclusively social. There is growing consensus that explaining and preventing it requires interdisciplinary research efforts. Indeed, the landscape of contemporary criminology includes a variety of theoretical models that incorporate psychological, biological and sociological factors. These multi-disciplinary approaches, however, have yet to radically advance scientific understandings of crime and shed light on how to manage it. In this paper, using conceptual tools on offer in the philosophy of science in combination (...) with theoretical work represented in this special volume of Psychology, Crime and Law, I provide some perspective on why explanatory progress in criminology has remained elusive and evaluate some positive proposals for attaining it. -/- . (shrink)

This research offers a new perspective by reframing the positivist-interpretive debate as a distinction between the functional outcomes of research: explanation and understanding. Based on an older and well-established literature in philosophy, this distinction can reinvigorate important differences in research outcomes that have been lost. Understanding or “subjective meaning” is connected to the intentionality, thoughts, and motivations of the human subjects under study. From this perspective, understanding is the type of knowledge gained from determining the meanings, categories, and symbols humans (...) attach to actions, knowledge, and systems. In contrast, explanation is achieved by subsuming individual instantiations of the phenomenon under broad general laws, or identifying causal mechanisms that support antecedent-consequent pairs. Researchers can proactively use the understanding-explanation distinction as a heuristic to create new lines of research questions based on what has not been explained or understood rather than on which ontology or methodology has not been used. (shrink)

Le modèle déductivo-nomologique domine depuis longtemps la réflexion philosophique concernant l’explication en science économique. Or, pour plusieurs, comme James Woodward et Tony Lawson, ce modèle ne considère pas suffisamment la causalité dans l’explication. L’objectif de cet article est double : 1- renforcer la critique que Tony Lawson adresse à l’économie contemporaine et 2- évaluer la théorie alternative qu’il propose, le « réalisme critique », qui tente de réintroduire la causalité dans l’explication en science économique. Nous conclurons que les considérations causales (...) sont très importantes pour l’explication en science économique mais aussi pour bien comprendre les limites de cette science. (shrink)

As questões das leis da natureza e da modalidade subjacente à regularidade natural muitas vezes têm sido tratadas como uma só. No entanto, a análise metafísica mostra que só as posições que assumem um compromisso ontológico com as leis da natureza podem ser consideradas dentro do Realismo Nomológico. Mumford propõe uma alternativa ao RN compatível com os compromissos modais comumente associados a posições realistas. Neste ponto de vista, o peso da modalidade não está posto nas leis, mas sim em propriedades (...) entendidas em termos de poderes e propensões. De acordo com sua própria nomenclatura, trata-se de um Realismo sem Leis. Neste trabalho pretende-se mostrar, em primeiro lugar, que os argumentos de Mumford contra o RN não justificam a sua rejeição e, em segundo lugar, defende-se que a metafísica disposicional do RSL leva, pelo menos, aos mesmos problemas que o RN. (shrink)

The classical holism-reductionism debate, which has been of major importance to the development of ecological theory and methodology, is an epistemological patchwork. At any moment, there is a risk of it slipping into an incoherent, chaotic Tower of Babel. Yet philosophy, like the sciences, requires that words and their correlative concepts be used rigorously and univocally. The prevalent use of everyday language in the holism-reductionism issue may give a false impression regarding its underlying clarity and coherence. In reality, the conceptual (...) categories underlying the debate have yet to be accurately defined and consistently used. There is a need to map out a clear conceptual, logical and epistemological framework. To this end, we propose a minimalist epistemological foundation. The issue is easier to grasp if we keep in mind that holism generally represents the ontological background of emergentism, but does not necessarily coincide with it. We therefore speak in very loose terms of the “holism-reductionism” debate, although it would really be better characterised by the terms emergentism and reductionism. The confrontation between these antagonistic paradigms unfolds at various semantic and operational levels. In definitional terms, there is not just emergentism and reductionism, but various kinds of emergentisms and reductionisms. (shrink)

Some recent literature [Hicks, M. T. and van Elswyk. P., (2015) pp. 433-443, 2015; Bhogal, H. (2017), pp. 447-460] has argued that the non-Humean conceptions of laws of nature have a same weakness as the Humean conceptions of laws of nature. That is, both conceptions face an explanatory circularity problem. The argument is as follows: the Humean and the non-Humean conceptions of laws of nature agree that the law statements are universal generalisations; thus, both conceptions are vulnerable to an explanatory (...) circularity problem between the laws of nature and their instances. In this paper, I argue that Armstrong’s necessitarian view of laws of nature is invulnerable to this explanatory circularity problem. (shrink)

Gender greatly impacts access to opportunities, potential, and success in corporate leadership roles. We begin with a general presentation of why such discussion is necessary for basic considerations of justice and fairness in gender equality and how the issues we raise must impact any ethical perspective on gender in the corporate workplace. We continue with a breakdown of the central categories affecting the success of women in corporate leadership roles. The first of these includes gender-influenced behavioral factors, such as the (...) requirements and expectations of gendered verbal and nonverbal communication styles as well as appearance. We move on to address the impact of family on corporate leadership opportunities and success, discussing the asymmetrical evaluation of an individual’s potential, authority, and competence based on gender stereotypes of familial obligations and expectations. Finally, we address how gender impacts access to networking and sponsorship opportunities and the long-term effects of systematic limitations on women’s inclusion in the upper echelons of corporate leadership. We conclude with a summary of the questions and issues raised by our discussion and direct individuals to consider how different ethical systems and moral requirements might influence their interpretations of gender and leadership in the corporate workplace. (shrink)

Cognitive science has been beset for thirty years by foundational disputes about the nature and extension of cognition—e.g. whether cognition is necessarily representational, whether cognitive processes extend outside the brain or body, and whether plants or microbes have them. Whereas previous philosophical work aimed to settle these disputes, I aim to understand what conception of cognition scientists could share given that they disagree so fundamentally. To this end, I develop a number of variations on traditional conceptual explication, and defend a (...) novel explication of cognition called the sensitive management hypothesis. -/- Since expert judgments about the extension of “cognition” vary so much, I argue that there is value in explication that accurately models the variance in judgments rather than taking sides or treating that variance as noise. I say of explications that accomplish this that they are ecumenically extensionally adequate. Thus, rather than adjudicating whether, say, plants can have cognitive processes like humans, an ecumenically adequate explication should classify these cases differently: human cognitive processes as paradigmatically cognitive, and plant processes as controversially cognitive. -/- I achieve ecumenical adequacy by articulating conceptual explications with parameters, or terms that can be assigned a number of distinct interpretations based on the background commitments of participants in a discourse. For example, an explication might require that cognition cause “behavior,” and imply that plant processes are cognitive or not depending on whether anything plants do can be considered “behavior.” Parameterization provides a unified treatment of embattled concepts by isolating topics of disagreement in a small number of parameters. -/- I incorporate these innovations into an account on which cognition is the “sensitive management of organismal behavior.” The sensitive management hypothesis is ecumenically extensionally adequate, accurately classifying a broad variety of cases as paradigmatically or controversially cognitive phenomena. I also describe an extremely permissive version of the sensitive management hypothesis, arguing that it has the potential to explain several features of cognitive scientific discourse, including various facts about the way cognitive scientists ascribe representations to cognitive systems. (shrink)

This thesis consists of two essays and an introduction. The main theme is technological knowledge that is not based on the natural sciences.The first essay is about rules of thumb, which are simple instructions, used to guide actions toward a specific result, without need of advanced knowledge. Knowing adequate rules of thumb is a common form of technological knowledge. It differs both from science-based and intuitive technological knowledge, although it may have its origin in experience, scientific knowledge, trial and error, (...) or a combination thereof. One of the major advantages of rules of thumb is the ease with which they can be learned. One of their major disadvantages is that they cannot easily be adjusted to new situations or conditions. Engineers commonly use rules, theories and models that lack scientific justification. How to include these in introductory technology education is the theme of the second essay. Examples include rules of thumb based on experience, but also models based on obsolete science or folk theories. Centrifugal forces, heat and cold as substances, and sucking vacuum all belong to the latter group. These models contradict scientific knowledge, but are useful for prediction in limited contexts where they are used when found convenient. The role of this kind of models in technology education is the theme of the second essay. Engineers’ work is a common prototype for pupils’ work with product development and systematic problem solving during technology lessons. Therefore pupils should be allowed to use the engineers’ non-scientific models when doing design work in school technology. The acceptance of these could be experienced as contradictory by the pupils: a model that is allowed, or even encouraged in technology class is considered wrong when doing science. To account for this, different epistemological frameworks must be used in science and technology education. Technology is first and foremost about usefulness, not about the truth or even generally applicable laws. This could cause pedagogical problems, but also provide useful examples to explain the limitations of models, the relation between model and reality, and the differences between science and technology. (shrink)

Technological knowledge is of many different kinds, from experience-based know-how in the crafts to science-based knowledge in modern engineering. It is inherently oriented towards being useful in technological activities, such as manufacturing and engineering design. The purpose of this thesis is to highlight special characteristics of technological knowledge and how these affect how technology should be taught in school. It consists of an introduction, a summary in Swedish, and five papers: Paper I is about rules of thumb, which are simple (...) instructions, used to guide actions toward a specific result, without need of advanced knowledge. One off the major advantages of rules of thumb is the ease with which they can be learnt. One of their major disadvantages is that they cannot easily be adjusted to new situations or conditions. Paper II describes how Gilbert Ryle's distinction between knowing how and knowing that is applicable in the technological domain. Knowing how and knowing that are commonly used together, but there are important differences between them which motivate why they should be regarded as different types: they are learnt in different ways, justified in different ways, and knowing that is susceptible to Gettier type problems which technological knowing how is not. Paper III is based on a survey about how Swedish technology teachers understand the concept of technological knowledge. Their opinions show an extensive variation, and they have no common terminology for describing the knowledge. Paper IV deals with non-scientific models that are commonly used by engineers, based on for example folk theories or obsolete science. These should be included in technology education if it is to resemble real technology. Different, and partly contradictory, epistemological frameworks must be used in different school subjects. This leads to major pedagogical challenges, but also to opportunities to clarify the differences between technology and the natural sciences and between models and reality. Paper V is about explanation, prediction, and the use of models in technology education. Explanations and models in technology differ from those in the natural sciences in that they have to include users' actions and intentions. (shrink)

The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of formal (...) conceptions of computation for describing simulation is refuted; the roles of programming languages according to intentional accounts of computation are identified; and the roles of iconographic programming languages and aesthetic machines in simulation are characterized. The roles that simulation and intentional decision making may be able to play in a participative information society are also discussed. (shrink)

This dissertation aims to determine the optimal level of granularity for the variables used in probabilistic causal models. These causal models are useful for generating explanations in a number of scientific contexts. In Chapter 1, I argue that there is rarely a unique level of granularity at which a given phenomenon can be causally explained, thereby rejecting various causal exclusion arguments. In Chapter 2, I consider several recent proposals for measuring the explanatory power of causal explanations, and show that these (...) measures fail to track the comparative depth of explanations given at different levels of granularity. In Chapter 3, I offer a pragmatic account of how to partition the measure space of a causal variable so as to optimally explain its effect. My account uses the decision-theoretic notion of value of information, and indexes the relative depth of an explanation to a particular agent faced with a particular decision problem. Chapter 4 applies this same decisiontheoretic framework to answer the epistemic question of how to discover constitutive relationships in nature. In Chapter 5, I describe the formal details of the relationship between random variables that are meant to be coarse-grained and fine-grained representations of the same type of phenomenon. I use this formal framework to rebut a popular argument for the view that special science probabilities can be objective chances. Chapter 6 discusses challenges related to the causal interpretation of Bayes nets that use imprecise rather than precise probabilities. (shrink)

There is an ongoing and robust tradition of science and technology studies scholars conducting ethnographic laboratory studies. These laboratory studies—like all ethnographies—are each conducted at a particular time, are situated in a particular place, and are about a particular culture. Presumably, this contextual specificity means that such ethnographies have limited applicability beyond the narrow slice of time, place, and culture that they each subject to examination. But we do not always or even often treat them that way. It is beyond (...) common for us to speak about what one or another laboratory study reveals about the laboratory, or “science” much more broadly. Given the contextual specificity of our ethnographic laboratory studies, what justifies this presumed generalizability? Initially, this manuscript surveys typical responses to this question, but then it pursues an unusual one: the potential replicability of ethnographic results. This potential is hereby explored, via an ethnographic replication attempt—one designed and conducted in order to test the generalizability of a particular laboratory study, that of Latour and Woolgar’s classic Laboratory Life. The results of the ethnographic replication attempt are reported, and a remarkable degree of replicability is established. (shrink)

Philosophical work on explanation has focused on the following two topics: theories of explanation, intended to enumerate necessary and sufficient conditions for explanation, and inference to the best explanation as the strongest form of justification for ontological or metaphysical claims. I critically examine the most important philosophical work in both of these areas and defend my own conclusions about the connections between explanation and ontology. I argue that all of our inferences about the nature of the world, in ontology or (...) metaphysics, presuppose criteria for acceptable explanation. I first examine the metaphysics of Plato, Aristotle, and Leibniz, arguing that their metaphysical reasoning was guided by assumptions about the nature of explanation. I also survey some recent work in ontology and find inference to the best explanation offered as the strongest available method of defending existence claims. To conclude this discussion, I offer an original argument for the thesis that all reasoning about existence claims, being nondeductive, presupposes some criteria for acceptable explanations, or a theory of explanation. Carl Hempel and Wesley Salmon have been two of the most influential philosophers offering theories of explanation, and I examine their work with the intention of discovering ontological or metaphysical assumptions shaping their theories of explanation. I argue that Hempel's theory rests on deterministic assumptions, and I argue the Salmon's theory of causality, which he admits supports his theory of explanation, is subject to empiricist criticisms. Theories of explanation typically rest on assumptions about the nature of the world, I argue, and I explain why this is so with an original theory of explanation connecting it to the psychological phenomenon of understanding. We rely on understanding in the identification of explanations, and understanding requires establishing a metaphysical context for an explanandum-event. I end by indicating the possibility of generating vicious justificatory circles through the reciprocal relationship of support between explanation and ontology, and I argue that vicious circles can be avoided only by grounding all ontological reasoning in a fundamental explanatory task of giving order to experience through a system of categories. (shrink)

In this BA dissertation, I deploy examples of non-causal explanations of physical phenomena as evidence against the view that causal models of explanation can fully account for explanatory practices in science. I begin by discussing the problems faced by Hempel’s models and the causal models built to replace them. I then offer three everyday examples of non-causal explanation, citing sticks, pilots and apples. I suggest a general form for such explanations, under which they can be phrased as inductive-statistical arguments incorporating (...) plausible assumptions. I then show the applicability of this form to explanatory practices in thermal physics. I explore the possibility that population genetics provides a similar form of explanation, and offer a novel defence of the statistical interpretation of population genetics proposed by Matthen and Ariew (2002). I close with remarks concerning how, when faced with competing causal and non-causal explanations of the same phenomenon, we can perform an Inference to the Best Explanation. (shrink)

Ongoing empirical discoveries in molecular biology have generated novel conceptual challenges and perspectives. Philosophers of biology have reacted to these trends when investigating the practice of molecular biology and contributed to scientific debates on methodological and conceptual matters. This article reviews some major philosophical issues in molecular biology. First, philosophical accounts of mechanistic explanation yield a notion of explanation in the context of molecular biology that does not have to rely on laws of nature and comports well with molecular discovery. (...) Second, reductionism continues to be debated and increasingly be rejected by scientists. Philosophers have likewise moved away from reduction toward integration across fields or integrative explanations covering several levels of organization. Third, although the gene concept has undergone substantial transformation and even fragmentation, it still enjoys widespread use by molecular biologists, which has prompted philosophers to understand the empirical reasons for this. At the same time, it has been argued the notion of ‘genetic information’ is largely an empty metaphor, which generates the illusion of explanatory understanding without offering an adequate explanation of molecular and developmental mechanisms. (shrink)

Opinionated state of the art paper on scientific explanation. Analysis and discussion of the most relevant models and theories in the contemporary literature, namely, the deductive-nomological model, the models of inductive-statistical and statistical relevance, the pragmatic theory of why questions, the unifying theory of standard arguments, and the causal/non-causal counterfactual theory.

This chapter utilises scholarship in philosophy of biology and philosophy of chemistry to produce meaningful implications for biology and chemistry education. The primary purpose for studying philosophical literature is to identify different perspectives on the nature of laws and explanations within these disciplines. The goal is not to resolve ongoing debates about the nature of laws and explanations but to consider their multiple forms and purposes in ways that promote deep and practical understanding of biological and chemical knowledge in educational (...) contexts. Most studies on the nature of science in science education tend to focus on general features of scientific knowledge and underemphasise disciplinary nuances. The authors aim to contribute to science education research by focusing on the characterisations of laws and explanations in biology and chemistry in the philosophical literature and illustrating how the typical coverage of biology and chemistry textbooks does not problematise meta-perspectives on the nature of laws and explanations. The chapter concludes with suggestions for making science teaching, learning and curriculum more inclusive of the epistemological dimensions of biology and chemistry. (shrink)

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...) can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone. (shrink)

The article presents the essence as well as various models of academic explanation and the explanatory value of understanding, indicating their usability and limitations as regards understanding why and how tourism functions. Particular attention has been paid to the epistemological dimension of tourism research, as well as its new directions. The author has referred to two models concerning the epistemological aspects of tourism research where the focal point is the category of ‘truth about tourism’. These have been presented in two (...) articles by John Tribe. (shrink)

"Partial realism" is a common position in the contemporary philosophy of science literature. It states that the "essential" elements of empirically successful scientific theories accurately represent corresponding features the world. This thesis makes several novel contributions related to this position. Firstly, it offers a new definition of the concept of “empirical success”, representing a principled merger between the use-novelty and unification accounts. Secondly, it provides a comparative critical analysis of various accounts of which elements are "essential" to the success of (...) a theory, including structural realism and the divide et impera strategy. A novel account of essentialness, entitled the “empirically successful sub-theory "account", is defended. Thirdly, it is argued that the realism/anti-realism debate should put to the side metaphysical questions and focus instead on partial realism's commitment to the continuity of science. Because this commitment lacks metaphysical implications, it is referred to as "deflationary realism". Anti-realists cannot reject deflationary realism as a matter of a priori principle; its overall viability can therefore only be assessed by a careful examination of the history of science. Finally, another consequence of partial realism, named "partial rationalism", is defended. Partial rationalism states that, in cases where several competing theories have been suggested, scientists are rational just in case they accept the essential elements of each of the scientific theories on offer. This novel position subverts the existing literature on scientific "revolutions", as it sometimes demands that scientists devise a synthesis between competing scientific theories, instead of "choosing" only one. The philosophical points defended in this thesis are illustrated and supported by case studies from the history of science, including Fresnel’s wave theory of light, the Copernican revolution, the "neo-Darwinian synthesis" in evolutionary biology, the "prion revolution" in molecular biology, the miasma theory of disease, and the chemical revolution. (shrink)

Laboratory experimentation was once considered impossible or irrelevant in economics. Recently, however, economic science has gone through a real ‘laboratory revolution’, and experimental economics is now a most lively subfield of the discipline. The methodological advantages and disadvantages of controlled experimentation constitute the main subject of this thesis. After a survey of the literature on experiments in philosophy and economics, the problem of testing normative theories of rationality is tackled. This philosophical issue was at the centre of a famous controversy (...) in decision theory, during which a methodology of normative falsification was first articulated and used to assess experimental results. In the third chapter, the methodological advantages of controlled experimentation are illustrated and discussed with examples taken from the experiments on the so-called ‘preference reversal’ phenomenon. Laboratory testing allows to establish with a high degree of certainty that certain phenomena lie behind the experimental data, by means of independent testing, elimination of alternative hypotheses, and the use of different instruments of observation. The fourth chapter is devoted to a conceptual analysis of the problem of ‘parallelism’. This is the problem of inferring from the occurrence of a phenomenon in the laboratory, to its instantiation also in non-laboratory environments. Experimental economists have discussed parallelism at length, and their views are presented and criticised. Eventually, it is argued that parallelism is a factual matter and as such can only be established on empirical grounds. The fifth chapter provides an example of how one can argue for parallelism, focusing on the case of experimentation on the ‘winner’s curse’ phenomenon. The role of experiments as ‘mediators’ between theoretical models and their target domain of application is illustrated, and the structure of parallelism arguments analysed in detail. Finally, in the last chapter, economic experiments are compared to simulations, in order to highlight their specific characteristics. (shrink)

Three metascientific concepts that have been object of philosophical analysis are the concepts oflaw, model and theory. The aim ofthis article is to present the explication of these concepts, and of their relationships, made within the framework of Sneedean or Metatheoretical Structuralism (Balzer et al. 1987), and of their application to a case from the realm of biology: Population Dynamics. The analysis carried out will make it possible to support, contrary to what some philosophers of science in general and of (...) biology in particular hold, the following claims: a) there are "laws" in biological sciences, b) many of the heterogeneous and different "models" of biology can be accommodated under some "theory", and c) this is exactly what confers great unifying power to biological theories. (shrink)

There were various initial reactions to the terrorist attacks of 11 September 2001, and among those reactions were some contradictions. There were those who demanded an explanation for the attacks, and others who condemned attempts to explain as immoral or unpatriotic. Though President George W. Bush did make some rhetorical remarks that, I believe, masqueraded as explanatory, it appears that he agrees with the latter set.

At the interface of developmental biology and evolutionary biology, the very criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena. This dissertation compares two recent research projects in which researchers jointly use the two kinds (...) of models. I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis. I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena. (shrink)

Book review: Łukasz Hardt, Economics Without Laws. Towards a New Philosophy of Economics, Palgrave Macmillan, Cham, 2017, pp. 220.

In this book, I defend the present-centered approach in historiography of science (i.e. study of the history of science), build an account for causal explanations in historiography of science, and show the fruitfulness of the approach and account in when we attempt to understand science. -/- The present-centered approach defines historiography of science as a field that studies the developments that led to the present science. I argue that the choice of the targets of studies in historiography of science should (...) be directly connected to our values and preferences in an intersubjective process. The main advantage of this approach is that it gives a clear motivation for historiography of science and avoids or solves stubborn conceptual and practical problems within the field. -/- The account of causal explanations is built on the notions of counterfactual scenarios and contrastive question-answer pairs. I argue that if and only if we track down patterns of counterfactual dependencies, can we understand history. Moreover, I define the notions of historical explanation, explanatory competition, explanatory depth, and explanatory resources. -/- Finally, I analyze the existing historiography of science with the framework built in the previous chapter, and I show that this framework clarifies many first-order (i.e. concerning the history of science) and meta-level issues (i.e. concerning the nature of science in general) that historians and philosophers tackle. As an illustration of the philosophical power of the framework, I explicate the notion of local explanation and analyze the question of whether the developments of science were necessary or contingent. (shrink)

1. A Historical Look at Unity 2. Field Guide to Modern Concepts of Reduction and Unity 3. Kitcher's Revisionist Account of Unification 4. Critics of Unity 5. Integration Instead of Unity 6. Reduction via Mechanisms 7. Case Studies in Reduction and Unification across the Disciplines.

Both in biology and psychology there has been a tendency on the part of many investigators to focus solely on the mature organism and ignore development. There are many reasons for this, but an important one is that the explanatory framework often invoked in the life sciences for understanding a given phenomenon, according to which explanation consists in identifying the mechanism that produces that phenomenon, both makes it possible to side-step the development issue and to provide inadequate resources for actually (...) explaining development. When biologists and psychologists do take up the question of development, they find themselves confronted with two polarizing positions of nativism and empiricism. However, the mechanistic framework, insofar as it emphasizes organization and recognizes the potential for self-organization, does in fact provide the resources for an account of development which avoids the nativism-empiricism dichotomy. (shrink)

Recently, several philosophers have argued that nonreductive physicalism is a false, unstable, and incoherent position. I argue that the position these critics are attacking is a straw one. To help explain why let us distinguish three issues about which nonreductive physicalists might plausibly be thought to have an opinion: ontological considerations about the types of things that exist at a world, issues involving the existence and nature of any dependency relationships between the types of things that exist at a world, (...) and epistemological questions regarding the best way to describe, explain, or characterize the types of things that exist at a world. I argue that reductive and nonreductive physicalists essentially agree with respect to the first two issues, but disagree with respect to the last issue. Nonreductive physicalists advocate a position that is ontologically or metaphysically reductive, but epistemologically or representationally nonreductive. Although this position could prove false on empirical grounds, it is neither unstable nor incoherent. (shrink)

Philosophers of science have by and large neglected technology. In this book, I have tried to do something about this lacuna by analyzing a few aspects of technical artifacts from a philosophical angle. The project was part of the research program "The Dual Nature of Technical Artifacts" based at Delft University of Technology in the Netherlands. Technical artifacts are both plain physical objects and objects that have been purposefully made for a purpose; which is to say they have a physical (...) structure and a technical function. As a result, they belong equally in a purely physical conceptualisation of the world "in which human intentions and goals seem to have no place" and in an intentional conceptualisation, which is used to describe and understand people and their mental lives. My main goal was to find out how these two philosophically very different aspects of artifacts are related to one another. To achieve this goal, I looked at two contexts in which these aspects are regularly brought together in a systematic fashion. First, the context of design; design can be characterized as a transition from a desired function or goal to a physical structure. In particular, I have studied and analyzed the role of functional decomposition in design processes. The second context is the explanation of how artifacts are able to fulfill their technical function in virtue of their specific physical structure. The result of this part of the project is a general account of such explanations. (shrink)

Recently, Michael Friedman has claimed that virtually all the seeds of Hempel’s philosophical development trace back to his early encounter with the Vienna Circle (Friedman 2003, 94). As opposed, however, to Friedman’s view of the principal early influences on Hempel, we shall see that those formative influences originated rather with the Berlin Group. Hempel, it is true, spent the fall term of 1929 as a student at the University of Vienna, and, thanks to a letter of recommendation from Hans Reichenbach, (...) he even attended some sessions of the Vienna Circle. But he spent much less time in Vienna than in Berlin, where he studied under Reichenbach from 1926 till 1933 and wrote a dissertation on probability, Reichenbach’s specialty. Hempel also attended seminars conducted by Walter Dubislav, another member of the Berlin Group. (shrink)

The aim of the present paper is to contribute to the discussion on the constitutive a priori in science by linking it with the discussion on scientific laws and theories, in such a way to show how the different senses of the notion of constitutive a priori are not incompatible to each other and that they can be precised in a unified, though differentiated, manner.

One of the most important questions in epistemology and the philosophy of science is: what is a good theory and when is a theory better than another theory, given some observational data? The coherentist‟s answer would be the following twofold conjecture: A theory is a good theory given some observational data iff that theory coheres with the observational data and a theory is better than another theory given some observational data iff the first theory coheres more with the observational data (...) than the second theory. In this paper we show that this answer is a good answer. More precisely, we argue that the coherence measures of Olsson and Shogenji are good measures for the purpose of comparing and evaluating theories, i.e. assessing theories. We do so by clarifying the sufficient and necessary conditions every assessment function must satisfy for being a good measure of the goodness of theories. Afterwards we will show that the coherence measures of Olsson and Shogenji are indeed good assessment functions for assessing theories. (shrink)