This paper discusses the epistemic import of highly abstract and simplified theoretical models using Thomas Schelling’s checkerboard model as an example. We argue that the epistemic contribution of theoretical models can be better understood in the context of a cluster of models relevant to the explanatory task at hand. The central claim of the paper is that theoretical models make better sense in the context of a menu of possible explanations. In order to justify this claim, we introduce a distinction (...) between causal scenarios and causal mechanism schemes. These conceptual tools help us to articulate the basis for modelers’ intuitive confidence that their models make an important epistemic contribution. By focusing on the role of the menu of possible explanations in the evaluation of explanatory hypotheses, it is possible to understand how a causal mechanism scheme can improve our explanatory understanding even in cases where it does not describe the actual cause of a particular phenomenon. (shrink)
This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive (...) explanations. Finally, the paper shows how the contrastive counterfactual theory of explanation can provide tools for assessing the explanatory power of models. (shrink)
This work consists of two parts. Part I will be a contribution to a philo- sophical discussion of the nature of causal explanation. It will present my contrastive counterfactual theory of causal explanation and show how it can be used to deal with a number of problems facing theories of causal explanation. Part II is a contribution to a discussion of the na- ture of interest explanation in social studies of science. The aim is to help to resolve some controversies (...) concerning interest explanation by explicating the concept of interest and its explanatory uses by using the account of explanation developed in Part I. (shrink)
This article discusses agent-based simulation (ABS) as a tool of sociological understanding. I argue that agent-based simulations can play an important role in the expansion of explanatory understanding in the social sciences. The argument is based on an inferential account of understanding (Ylikoski 2009, Ylikoski & Kuorikoski 2010), according to which computer simulations increase our explanatory understanding by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. (...) The inferential account also suggests a number of ways in which the use of simulation methodology might give rise to illusory understanding. The structure of the article is as .. (shrink)
In this chapter I will employ a well-known scientific research heuristic that studies how something works by focusing on circumstances in which it does not work. Rather than trying to describe what scientific understanding would ideally look like, I will try to learn something about it by observing mundane cases where understanding is partly illusory. My main thesis is that scientists are prone to the illusion of depth of understanding (IDU), and as a consequence they sometimes overestimate (...) the detail, coherence, and depth of their understanding. I will analyze the notion of understanding and its relation to a sense of understanding. In order to make plausible the claim that these are often disconnected, I will describe an interesting series of psychological experiments by Frank Keil and his coauthors that suggests that ordinary people routinely overestimate the depth of their understanding. en I will argue that we should take seriously the possibility that scientific cognition is also aðected by IDU and spell out some possible causes of explanatory illusions in science. I will conclude this chapter by discussing how scientific explanatory practices could be improved and how the philosophy of science might be able to contribute to this process. (shrink)
Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual approach (...) to explanation and the view of understanding as an inferential ability. By combining these perspectives, we show how the explanatory power of an explanation in a given dimension can be assessed by showing the range of answers it provides to what-if-things-had-been-different questions and the theoretical and pragmatic importance of these questions. Our account also explains intuitions linking explanation to unification or to exhibition of a mechanism. (shrink)
This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution is a synchronous (...) and asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation. (shrink)
Generalization from a case study is a perennial issue in the methodology of the social sciences. The case study is one of the most important research designs in many social scientific fields, but no shared understanding exists of the epistemic import of case studies. This article suggests that the idea of mechanism-based theorizing provides a fruitful basis for understanding how case studies contribute to a general understanding of social phenomena. This approach is illustrated with a re- construction (...) of Espeland and Sauder's case study of the effects of rankings on US legal education. On the basis of the reconstruction, it is argued that, at least with respect to sociology, the idea of mechanism-based theorizing captures many of the generalizable elements of case studies. (shrink)
In this Chapter, we address the challenge of explaining institutional change, asking whether the much-criticized rational choice perspective can contribute to the understanding of institutional change in political science. We discuss the methodological reasons why rational choice institutionalism (RCI) often assumes that institutional change is exogenous and discontinuous. We then identify and explore the possible pathways along which RCI can be extended to be more useful in understanding institutional change in political science. Finally, we reflect on what RCI (...) theorizing would look like if it started to take endogenous change seriously: by giving up some of its simplifying assumptions, RCI can be a useful tool for analyzing institutional change, but choosing this path has consequences for the generality of the models in RCI as well as for the style of its theorizing. (shrink)
This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent (...) of the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)
Väitöskirjassani Understanding Interests and Causal Explanation (2001) hahmottelin teoriaa yksittäisten tapahtumien kausaalisesta selittämisestä. Tässä kirjoituksessa tarkastelen niitä haasteita tai vaatimuksia, joihin teoriani yritti vastata. Alustavien huomioiden jälkeen esittelen ensiksi erityisesti selittämisen teoriaan liittyviä haasteita ja sen jälkeen yleisempiä filosofisia vaatimuksia hyväksyttävälle selittämisen teorialle.
The psychiatric category of addiction has recently been broadened to include new behaviors. This has prompted critical discussion about the value of a concept that covers so many different substances and activities. Many of the debates surrounding the notion of addiction stem from different views concerning what kind of a thing addiction fundamentally is. In this essay, we put forward an account that conceptualizes different addictions as sharing a cluster of relevant properties (the syndrome) that is supported by a matrix (...) of causal mechanisms. According to this “addiction-as-a-kind” hypothesis, several different kinds of substance and behavioral addictions can be thought of as instantiations of the same thing – addiction. We show how a clearly articulated account of addiction can facilitate empirical research and the theoretical integration of different perspectives on addiction. The causal matrix approach provides a promising alternative to existing accounts of the nature of psychiatric disorders, the traditional disease model, and its competitors. It is a positive addition to discussions about diagnostic criteria, and sheds light on how psychiatric classification may be integrated with research done in other scientific fields. We argue that it also provides a plausible approach to understanding comorbidity. (shrink)
During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...) of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations. (shrink)
Work on representing women's voices in ethics has produced a vision of moral understanding profoundly subversive of the traditional philosophical conception of moral knowledge. 1 explicate this alternative moral “epistemology,” identify how it challenges the prevailing view, and indicate some of its resources for a liberatory feminist critique of philosophical ethics.
Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.
In recent years there has been a resurgence of interest among epistemologists in the nature of understanding, with some authors arguing that understanding should replace knowledge as the primary focus of epistemology. But what is understanding? According to what is often called the standard view, understanding is a species of knowledge. Although this view has recently been challenged in various ways, even the critics of the standard view have assumed that understanding requires justification and belief. (...) I argue that it requires neither. If sound, these arguments have important upshots not only for the nature of understanding, but also for its distinctive epistemic value and its role in contemporary epistemology. (shrink)
We compare Guala’s unified theory of institutions with that of Searle and Greif. We show that unification can be many things and it may be associated with diverse explanatory goals. We also highlight some of the important shortcomings of Guala’s account: it does not capture all social institutions, its ability to bridge social ontology and game theory is based on a problematic interpretation of the type-token distinction, and its ability to make social ontology useful for social sciences is hindered by (...) Guala’s interpretation of social institution types as social kinds akin to natural kinds. (shrink)
is chapter takes a fresh look at micro-macro relations in the social sciences from the point of view of the mechanistic account of explanation. Traditionally, micro- macro issues have been assimilated to the problem of methodological individualism. It is not my intention to resurrect this notoriously unfruitful controversy. On the contrary, the main thrust of this chapter is to show that the cul-de-sac of that debate can be avoided if we give up some of its presuppositions. The debate about methodological (...) individualism is based on assumptions about explanation, and once we change those assumptions, the whole argumenta- tive landscape changes. (shrink)
In this paper I will discuss the idea of the invisible hand in the connection of its recent use in the philosophy of science. It has been invoked by some philosophers of science with a naturalistic bent as a part of their account of science. Some have made explicit references to the idea (Hull, 1988a) and others have only presupposed it (Giere, 1988; Goldman, 1991; Kitcher, 1993). I will argue that there are some problematic features in the way the idea (...) of the invisible hand isused inthese accounts. I will first discuss some general properties of the invisible hand explanations and then present some motives for its use in the theory of science. Then I will show how one particular philosopher of science, David Hull, uses the idea. I will use Hull's account as a practising target and offer some comments and criticism in order to promote more disciplined use of this model of explanation in science studies. (shrink)
Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.
Among philosophers of science there seems to be a general consensus that understanding represents a species of knowledge, but virtually every major epistemologist who has thought seriously about understanding has come to deny this claim. Against this prevailing tide in epistemology, I argue that understanding is, in fact, a species of knowledge: just like knowledge, for example, understanding is not transparent and can be Gettiered. I then consider how the psychological act of "grasping" that seems to (...) be characteristic of understanding differs from the sort of psychological act that often characterizes knowledge. Zagzebski's account Kvanvig's account Two problems Comanche cases Unreliable sources of information The upper-right quadrant So is understanding a species of knowledge? A false choice. (shrink)
Constitutivemechanisticexplanationsexplainapropertyofawholewith the properties of its parts and their organization. Carl Craver’s mutual manipulability criterion for constitutive relevance only captures the explanatory relevance of causal properties of parts and leaves the organization side of mechanistic explanation unaccounted for. We use the contrastive counterfactual theory of explanation and an account of the dimensions of organization to build a typology of organizational dependence. We analyse organizational explanations in terms of such dependencies and emphasize the importance of modular organizational motifs. We apply this framework (...) to two cases from social science and systems biology, both fields in which organization plays a crucial explanatory role: agent-based simulations of residential segregation and the recent work on network motifs in transcription regulation networks. (shrink)
This paper investigates how unsupervised machine learning methods might make hermeneutic interpretive text analysis more objective in the social sciences. Through a close examination of the uses of topic modeling—a popular unsupervised approach in the social sciences—it argues that the primary way in which unsupervised learning supports interpretation is by allowing interpreters to discover unanticipated information in larger and more diverse corpora and by improving the transparency of the interpretive process. This view highlights that unsupervised modeling does not eliminate the (...) researchers’ judgments from the process of producing evidence for social scientific theories. The paper shows this by distinguishing between two prevalent attitudes toward topic modeling, i.e., topic realism and topic instrumentalism. Under neither can modeling provide social scientific evidence without the researchers’ interpretive engagement with the original text materials. Thus the unsupervised text analysis cannot improve the objectivity of interpretation by alleviating the problem of underdetermination in interpretive debate. The paper argues that the sense in which unsupervised methods can improve objectivity is by providing researchers with the resources to justify to others that their interpretations are correct. This kind of objectivity seeks to reduce suspicions in collective debate that interpretations are the products of arbitrary processes influenced by the researchers’ idiosyncratic decisions or starting points. The paper discusses this view in relation to alternative approaches to formalizing interpretation and identifies several limitations on what unsupervised learning can be expected to achieve in terms of supporting interpretive work. (shrink)
This comment discusses Kaidesoja and raises the issue whether his analysis justifies stronger conclusions than he presents in the book. My comments focus on four issues. First, I argue that his naturalistic reconstruction of critical realist transcendental arguments shows that transcendental arguments should be treated as a rare curiosity rather than a general argumentative strategy. Second, I suggest that Kaidesoja’s analysis does not really justify his optimism about the usefulness of causal powers ontology in the social sciences. Third, I raise (...) some doubts about the heuristic value of Mario Bunge’s social ontology that Kaidesoja presents as a replacement for critical realist ontology. Finally, I propose an alternative way to analyze failures of aggregativity that might better serve Kaidesoja’s purposes than the Wimsattian scheme he employs in the book. (shrink)
In his paper Karl-Dieter Opp heroically sets out to defend both the adequacy and socio- logical fruitfulness of the covering-law account of explanation (the HO scheme). The attempt is bold, as he is not only defending the HO scheme as a theory of explanation but also as a scheme for finding and establishing causal relationships. In this reply I argue that the defense is not successful; quite the contrary, it clearly demonstrates why mecha- nism-based reasoning is important in the social (...) sciences. I also argue that this change in metatheoretical perspective has implications for thinking about the role of rational choice theory in sociology, which should not be seen as a foundational theory but rather as a version of commonsense psychology that can be used for modeling purposes. (shrink)
This paper is a reply to the discussions of Ruth Groff, Dave Elder-Vass, Daniel Little, and Petri Ylikoski of Tuukka Kaidesoja : Naturalizing Critical Realist Social Ontology.
Realism in Action is a selection of essays written by leading representatives in the fields of action theory and philosophy of mind, philosophy of the social sciences and especially the nature of social action, and of epistemology and philosophy of science. Practical reason, reasons and causes in action theory, intending and trying, and folk-psychological explanation are some of the topics discussed by these leading participants. A particular emphasis is laid on trust, commitments and social institutions, on the possibility of grounding (...) social notions in individual social attitudes, on the nature of social groups, institutions and collective intentionality, and on common belief and common knowledge. Applications to the social sciences include, e.g., a look at the Erklären-Verstehen controversy in economics, and at constructivist and realist views on archeological reconstructions of the past. (shrink)
We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that (...) our account could be fruitfully used in appraising other models in philosophy and science. (shrink)
This book is vintage North."--Barry Weingast, Professor of Political Science, Stanford University "In this book Douglass North once again opens new frontiers in economic research.
Peter Vickers examines 'inconsistent theories' in the history of science--theories which, though contradictory, are held to be extremely useful. He argues that these 'theories' are actually significantly different entities, and warns that the traditional goal of philosophy to make substantial, general claims about how science works is misguided.
Scientific understanding, this paper argues, can be analyzed entirely in terms of a mental act of “grasping” and a notion of explanation. To understand why a phenomenon occurs is to grasp a correct explanation of the phenomenon. To understand a scientific theory is to be able to construct, or at least to grasp, a range of potential explanations in which that theory accounts for other phenomena. There is no route to scientific understanding, then, that does not go by (...) way of scientific explanation. (shrink)
The aim of this paper is to evaluate the critical success factors and investigate the benefits that might be gained once implementing Electronic Customer Relationship Management at HEI from employee perspective. The study conducted at Al Quds Open University in Palestine and data collected from (300) employee through a questionnaire which consist of four variables. A number of statistical tools were intended for hypotheses testing and data analysis, including Spearman correlation coefficient for Validity, reliability correlation using Cronbach’s alpha, and Frequency (...) and Descriptive analysis. The overall findings of the current study show that all the features were important for staff and it was critical success factors, at the same time, websites were providing all the features discussed by the theory whereas staff showed their willingness to use those features if provided. It is also discovered that implementing Electronic Customer Relationship Management can cause staff retention, were provided efficiently and needed to be improved. Research limitations: The survey findings were based on QOU employee in Palestine, UAE and KSA branches not included in the study. (shrink)
Understanding is a central aim of science and highly important in present-day society. But what precisely is scientific understanding and how can it be achieved? This book answers these questions, through philosophical analysis and historical case studies, and presents a philosophical theory of scientific understanding that highlights its contextual nature.
If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a (...) sufficient but not slavish sensitivity to the facts. (shrink)
A model of writing in cognitive development, Understanding the Representational Mind synthesizes the burgeoning literature on the child’s theory of mind to provide an integrated account of children’s understanding of representational and mental processes, which is crucial in their acquisition of our commonsense psychology. Perner describes experimental work on children’s acquisition of a theory of mind and representation, offers a theoretical account of this acquisition, and gives examples of how the increased sophistication in children’s theory of mind improves (...) their understanding of social interaction and how, in the case of autistic children, an impairment results in social ineptitude. He analyzes the concepts of representation and metarepresentation as they appear in current discussion in the philosophy of cognitive science and explains how the unfolding of mental representation enables infants to comprehend change over time, engage in pretence, and use representational systems like pictures and language. Perner goes on to show that around age four children become able to understand the representational nature of pictures and language and to distinguish appearance from reality. Introducing basic distinctions in philosophy of mind for characterizing the mental, Perner discusses differences in how commonsense and cognitive psychology view the mind. Tracing the onset of a commonsense psychology in the social and emotional awareness of early infancy, he reveals how the child begins to take a cognitive, representational view of the mind with repercussions for children’s episodic memory, self control, and their ability to engage in deception. Perner concludes by describing the observed developmental changes as a case of theory change And contrasts his thesis with competing proposals. Josef Perner is Lecturer in Experimental Psychology at Sussex University, Brighton, England. (shrink)
This paper provides a conceptual analysis of the notion of interests as it is used in the social studies of science. After describing the theoretical background behind the Strong Program's adoption of the concept of interest, the paper outlines a reconstruction of the everyday notion of interest and argues that this same notion is used also by the sociologists of scientific knowledge. However, there are a couple of important differences between the everyday use of this notion and the way in (...) which it used by the sociologists. The sociologists do not use the term in evaluative context and they do not regard interests as purely non-epistemic factors. Finally, it is argued that most of the usual critiques of interest explanations, by both philosophers and fellow sociologists, are misguided. (shrink)