The practice of social studies continues to be a complicated scientific endeavor. From an epistemological point of view, the social sciences, unlike the natural sciences, do not conform to the predominant definition of science. The existing differences among expositions of “science,” “inquiry,” and “studies” lie with the contested role of the intellectual who is embarked on understanding the social realm. The “maturity” of the social sciences is usually discussed in the context of objectivity and rationality. But continuing epistemological debates would (...) be insufficient without reference to the scholar as a human studying humans. The philosophy of science has focused mainly on the procedures of knowledge accumulation, neglecting social context and its implications for inquiry. To address this neglect, this essay sets out first to retrace doubts about the role of the scholar that emerged with the institutionalization of the social sciences at the outset of the twentieth century and then to rethink these issues in terms of recent scientific developments. What surfaces is a new, participatory role for scholars that demands responsible contextualization and a broader conception of causal stories. (shrink)

There are, broadly speaking, two ways to think about rationality, as defined in the following passage: ‘Reason’ for a long time meant the activity of understanding and assimilating the eternal ideas which were to function as goals for men. Today, on the contrary, it is not only the business but the essential work of reason to find means for the goals one adopts at any given time. To use what Horkheimer called objective reason, and what others have called expressive or (...) non–instrumental reason, is to reflect on one's goals, to attempt to determine what preferences one ought to hold. On the other hand, to use what Horkheimer called subjective reason is to ‘be concerned with means and ends, with the adequacy of procedures for purposes more or less taken for granted’, that is, to be instrumentally rational. This contrast between non-instrumental and instrumental reason is at the heart of many contemporary social and philosophical disputes. 1. (shrink)

In this paper, I review the literature on rational choice theory to scrutinize a number of criticisms that philosophers have voiced against its usefulness in economics. The paper has three goals: first, I argue that the debates about RCT have been characterized by disunity and confusion about the object under scrutiny, which calls into question the effectiveness of those criticisms. Second, I argue that RCT is not a single and unified choice theory—let alone an empirical theory of human behavior—as some (...) critics seem to suppose. Rather, there are several variants of RCT used in economics. Third, I propose that we think of RCT as a set of distinct research strategies to appreciate its diversity. This account implies that the effectiveness of any criticism depends on the variant of RCT we are considering. (shrink)

Prominent research programs dealing with the nature and mechanisms of interpersonal social coordination have emerged in cognitive science, developmental psychology and evolutionary anthropology. I argue that the mechanistic approach to explanation in contemporary philosophy of science can facilitate interdisciplinary integration and division of labor between these different disciplinary research programs. By distinguishing phenomenal models from mechanistic models and structural decomposition from functional decomposition in the process of mechanism discovery, I argue that behavioral and cognitive scientists can make interlocking contributions to (...) families of mechanism models representing a) what central forms of interpersonal social coordination consist in, b) what types of agents engage in such forms of coordination, c) what types of cognitive mechanisms give rise to such forms of coordination, d) how the operation of such mechanisms is modulated by the natural and social environments that the agents populate. Thus mechanistic philosophy of science can play a heuristic role in guiding the research strategies of scientists in different scientific disciplines in a manner that is complementary to the research strategies of scientists in other disciplines and thereby efficient from the point of view of the division of epistemic labor. (shrink)

A collective volume in memoriam Mihail Radu Solcan.

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)

While the existence of human cognitive and behavioral diversity is now widely recognized, it is not yet well established how to explain this diversity. In particular, it is still unclear how to determine whether any given instance of human cognitive and behavioral diversity is due to a common psychology that is merely “triggered” differently in different bio-cultural environments, or whether it is due to deeply and fundamentally different psychologies. This paper suggests that, to answer this question, we need to employ (...) subtle theoretical considerations of theory choice—especially the consideration of the complexity-weighted differential predictive successes of the two accounts. To make this clearer, the paper develops a novel analysis of the observed differences in human sharing dispositions. (shrink)

Humans are standouts in their propensity to trade. More specially, the kind of trading found in humans—featuring the exchange of many different goods and services with many different others, for the mutual benefit of all the involved parties—far exceeds anything that is found in any other creature. However, a number of important questions about this propensity remain open. First, it is not clear exactly what makes this propensity so different in the human case from that of other animals. Second, it (...) is not clear why other animals did not acquire this propensity to the extent that humans did. Third, it is not clear what explains the fact that the extent to which humans engage in trade is culturally highly variable. The paper argues that at the heart of the human-animal divergence in this propensity is the particular socio-cultural environment in which humans evolved. This has led them to sometimes, but not always, acquire the cognitive technology (writing, algebra, tallying devices, money, etc.) to support a sophisticated disposition and capacity for reciprocal cooperation, and deep and wide concepts of property and exchange value. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...) models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

According to Margaret Gilbert’s collective epistemology, we should take attributions of beliefs to groups seriously, rather than metaphorically or as reducible to individual belief. I argue that, similarly, attributions of belief to markets ought to be taken seriously and not merely as reports of the average beliefs of market participants. While many of Gilbert’s purported examples of group belief are better thought of as instances of acceptance, some collectives, such as courts and markets, genuinely believe. Such collectives enact truth-aimed processes (...) that are beyond the control of any single individual. These processes produce beliefs that are distinct from any individual belief and do not merely report the “average” or “majority” view of the group. In the case of markets, beliefs are indicated by prices, though it is often difficult to infer beliefs from prices and those inferences are almost always uncertain. Reliabilism is the best available standard of justification for market beliefs. In some cases market beliefs are reliable and prove to be true. Thus, in some cases markets can know. (shrink)

This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

Why are causal generalizations in the higher-level sciences “inexact”? That is, why do they have apparent exceptions? This paper offers one explanation: many causal generalizations cite as their antecedent—the \(F\) in \(Fs\,\, {\textit{are}}\,\, G\) —a property that is not causally relevant to the consequent, but which is rather “entangled” with a causally relevant property. Entanglement is a relation that may exist for many reasons, and that allows of exceptions. Causal generalizations that specify entangled but causally irrelevant antecedents therefore tolerate exceptions.

The ubiquity of the term CSR threatens its carrying any distinctive meaning. Despite its long history no consensus has been developed among the industry participants, academics or other interested parties. After a careful review of the complications and complexities of the CSR debate and distinct disciplinary definitions, the article turns to approach the problem of definition using the philosophy of science. It applies a scientific definitional approach of genus, differentia and species to arrive at a definition of CSR as international (...) private business self-regulation. The article provides an overview of the implications of this definition on CSR as a field of study, a management practice and an approach to improving the dialogue concerning the social contribution of business. (shrink)

In 1981, A. C. Crombie identified six “styles of scientific thinking in the European tradition” that constitute our ways of reasoning in the natural sciences. In this paper, I try to show that these styles constitute reasoning in the social sciences as well, and that, as a result, the differences between reasoning about the physical world and about human beings are not so different as some interpretevists have supposed.

In this paper, I adopt the view that if general forces or processes can be detected in ecology, then the principles or models that represent them should provide predictions that are approximately correct and, when not, should lead to the sorts of intervening factors that usually make trouble. I argue that Lotka–Volterra principles do not meet this standard; in both their simple “strategic” and their complex “tactical” forms they are not approximately correct of the findings of the laboratory experiments and (...) historical studies most likely to confirm them; nor do they instruct ecologists where to look for likely intervening factors. Evidence drawn from long-term case studies and other available data sets suggests that the populations of predators and their prey are not regulated by an interaction between them but are controlled by transient, contingent, and accidental events that affect each animal and each population individualistically. This paper argues that the presence of general forces or processes in ecology should be determined by comparing competing models of these forces not just to each other or to a null model but also to case studies that may challenge theoretical approaches with convincing individualistic causal accounts of the phenomena. (shrink)

In a number of very influential publications, Epstein and Hoover (among other authors) have recently argued that a thoroughly micro-foundationalist approach towards economics is unconvincing for metaphysical reasons. However, as we show in this article, this metaphysical/social ontological approach to the debate fails to resolve the status of micro-foundations in the practice of economic modelling. To overcome this, we argue that endogenizing a model—that is, providing micro-foundations for it—correlates with making that model more complex. Specifically, we show that models with (...) more micro-foundations tend to have more parameters or variables. This matters, as there are well-established methodological reasons for preferring models with fewer parameters or variables—ceteris paribus. We therefore conclude that, from a practice-based point of view, micro-foundations are only defensible to the extent that they significantly improve the ability of the relevant model to fit the data of interest. In this way, we arrive at a practice-based, methodological reconceptualization of the debate surrounding the need for micro-foundations in economics. (shrink)

Imagine asking a typical, well informed, contemporary philosopher whether or not she considered biology to be a science. Our informant, being a philosopher, would not necessarily respond with the straightforward “of course” that would be expected from anyone else. She might first reason through a complicated and heavily qualified definition of science, or she might distinguish certain parts of biology that she held to be more clearly scientific than others. If she were partial to a certain sort of critical stance, (...) she might question the political basis for wishing to dignify certain parts of our inquisitive practice with the honorific ‘scientific’ in the first place. But there is at least one thing that she would almost certainly not do. She would not simultaneously embrace a version of the conventional philosophical view of science and deny that biology is a science. This is despite the fact that, as she will acknowledge, biology exploits a range of methodologies and explanatory strategies that have not yet admitted of systematic, consensual philosophical explication. (shrink)

In this paper, I shall defend two main claims. First, Friedman’s famous paper “On the methodology of positive economics” (“F53”) cannot be properly understood without taking into account the influence of three authors who are neither cited nor mentioned in the paper: Max Weber, Frank Knight, and Karl Popper. I shall trace both their substantive influence on F53 and the historical route by which this influence took place. Once one has understood these ingredients, especially Weber’s ideal types, many of F53’s (...) astonishing sentences like “the more significant the theory, the more unrealistic the assumptions”, make good sense. Second, I shall claim that the much-discussed question whether Friedman’s essay espouses an instrumentalist or a realist position, is the wrong question to be asked. I shall illustrate that by a comparison with examples from physics in which also unrealistic assumptions are made. Also there, the question whether these assumptions are indicators of instrumentalism or realism is not appropriate. Cleared from these misunderstandings, F53 presents itself as an interesting and reasonable but much less controversial contribution to the methodology of economics. (shrink)

This paper investigates the interaction between semantic theories for cp-laws (roughly, laws that hold “all things equal”) and metaphysical theories of kinds in the special sciences. Its central conclusion is that cp-laws concerning kinds behave differently from cp-laws concerning non-kinds: “ravens are black” which concerns the kind corvus corax, behaves differently from from “albino ravens are white” which concerns the non-kind grouping of albino ravens. I argue that this difference is in the first instance logical: the two sorts of cp-laws (...) give rise to different inferential patterns. I draw two further conclusions. The difference in logical behavior poses a severe problem for extant semantic theories of cp-laws, and: we cannot elucidate the distinction between kinds and non-kinds by suggesting that only kinds can appear in laws. (shrink)

This essay presents a model-theoretic account of dispositional properties, according to which dispositions are not ordinary properties of real entities; dispositions capture the behavior of abstract, idealized models. This account has several payoffs. First, it saves the simple conditional analysis of dispositions. Second, it preserves the general connection between dispositions and regularities, despite the fact that some dispositions are not grounded in actual regularities. Finally, it brings together the analysis and the explanation of dispositions under a unified framework.

This paper defends the thesis of learning from non-causal models: viz. that the study of some model can prompt justified changes in one’s confidence in empirical hypotheses about a real-world target in the absence of any known or predicted similarity between model and target with regards to their causal features. Recognizing that we can learn from non-causal models matters not only to our understanding of past scientific achievements, but also to contemporary debates in the philosophy of science. At one end (...) of the philosophical spectrum, my thesis undermines the views of those who, like Cartwright (Erkenntnis 70:45–58, 2009), follow Hesse (Models and Analogies in Science, Notre Dame, University of Notre Dame Press, 1963) in restricting the possibility of learning from models to only those situations where a model identifies some causal factors present in the target. At the other end of the spectrum, my thesis also helps undermine some extremely permissive positions, e.g., Grüne-Yanoff’s (Erkenntnis 70(1):81–99, 2009, Philos Sci 80(5): 850–861, 2013) claim that learning from a model is possible even in the absence of any similarity at all between model and target. The thesis that we can learn from non-causal models offers a cautious middle ground between these two extremes. (shrink)

Consider how your consumption would change if you were stranded on a deserted island. Isolation would eliminate all social influences on your consumption decisions, even for the same choice set. You might decide not to consume cosmetics, curtains, or neckties, and pay less attention to the style or color of your clothes, car, or furniture. These choices might not matter as much to you anymore, for you would not have to consider the reactions of other individuals to your consumption. Similarly, (...) isolation would also eliminate social influences on your speech. Absent an audience, your choice of words would not be subject to the judgments of others. (shrink)

Over the last few decades, theoretical discussions about metaphors have appeared with increasing frequency in the literature and, during the last fifteen years or so, such discussions have become more and more common in the methodology of economics. But what exactly is a metaphor? According to a tradition which dates back to Aristotle, a metaphor is the attribution to one object, A, of the name of another object, B, while this name or these qualities do not properly or normally belong (...) to A. Thus, a metaphor is present when a term used to describe A is a term which is already commonly used to name B. Defined in such a way, one must admit that metaphors are frequently found in economics as well as in other sciences. Let us consider, for example, a term like ‘elasticity’ which is extensively used by economists. According to the ordinary dictionary definition, this word designates a property of bodies by which they recover their initial form after having been submitted to a pressure; in a less technical sense, it refers to the flexibility of some bodies or to their responsiveness to pressures. (shrink)

Network theory is applied across the sciences to study phenomena as diverse as the spread of SARS, the topology of the cell, the structure of the Internet and job search behaviour. Underlying the study of networks is graph theory. Whether the graph represents a network of neurons, cells, friends or firms, it displays features that exclusively depend on the mathematical properties of the graph itself. However, the way in which graph theory is implemented to the modelling of networks differs significantly (...) across scientific fields. This article compares the economics variant of network theory with those of other fields. It shows how the methodology employed by economists to model networks is shaped by two explanatory desiderata: that the explanandum phenomenon is based on micro-economic foundations and that the explanation is general. (shrink)

The paper, as Part I of a two-part series, argues for a hybrid formulation of the semantic view of scientific theories. For stage-setting, it first reviews the elements of the model theory in mathematical logic (on whose foundation the semantic view rests), the syntactic and the semantic view, and the different notions of models used in the practice of science. The paper then argues for an integration of the notions into the semantic view, and thereby offers a hybrid semantic view, (...) which at once secures the view's logical foundations and enhances its applicability. The dilemma of either losing touch with the practice of science or yielding up the benefits of the model theory is thus avoided. (shrink)

This article disputes the common view that social science explanations depend on discovery of lawlike generalizations from which descriptions of social outcomes can be derived. It distinguishes between governing and phenomenal regularities, and argues that social regularities are phenomenal rather than governing. In place of nomological deductive arguments, the article maintains that social explanations depend on the discovery of causal mechanisms underlying various social processes. The metaphysical correlate of this argument is that there are no social kinds: types of social (...) entities that share a common casual constitution giving rise to strong regularities of behavior. The article turns next to a consideration of the character of social causation and argues for a microfoundational interpretation of social causation: social causal powers are embodied in the constraints and opportunities that institutions present to individual agents. Finally, it is noted that these arguments have consequences for the credibility of social predictions: it is argued that predictions in social science are generally unreliable. (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)

According to manipulationist accounts of causal explanation, to explain an event is to show how it could be changed by intervening on its cause. The relevant change must be a ‘serious possibility’ claims Woodward 2003, distinct from mere logical or physical possibility—approximating something I call ‘scientific possibility’. This idea creates significant difficulties: background knowledge is necessary for judgments of possibility. Yet the primary vehicles of explanation in manipulationism are ‘invariant’ generalisations, and these are not well adapted to encoding such knowledge, (...) especially in the social sciences, as some of it is non-causal. Ceteris paribus (CP) laws or generalisations labour under no such difficulty. A survey of research methods such as case and comparative studies, randomised control trials, ethnography, and structural equation modeling, suggests that it would be more difficult and in some instances impossible to try to represent the output of each method in invariant generalisations; and that this is because in each method causal and non-causal background knowledge mesh in a way that cannot easily be accounted for in manipulationist terms. Ceteris paribus-generalisations being superior in this regard, a theory of explanation based on the latter is a better fit for social science. (shrink)

One striking feature of the contemporary modelling practice is its interdisciplinary nature. The same equation forms, and mathematical and computational methods, are used across different disciplines, as well as within the same discipline. Are there, then, differences between intra- and interdisciplinary transfer, and can the comparison between the two provide more insight on the challenges of interdisciplinary theoretical work? We will study the development and various uses of the Ising model within physics, contrasting them to its applications to socio-economic systems. (...) While the renormalization group methods justify the transfer of the Ising model within physics – by ascribing them to the same universality class – its application to socio-economic phenomena has no such theoretical grounding. As a result, the insights gained by modelling socio-economic phenomena by the Ising model may remain limited. (shrink)

This paper examines two recent approaches to the nature and functioning of economic models: models as isolating representations and models as credible constructions. The isolationist view conceives of economic models as surrogate systems that isolate some of the causal mechanisms or tendencies of their respective target systems, while the constructionist approach treats them rather like pure constructions or fictional entities that nevertheless license different kinds of inferences. I will argue that whereas the isolationist view is still tied to the representationalist (...) understanding of models that takes the model-target dyad as the basic unit of analysis, the constructionist perspective can better accommodate the way we actually acquire knowledge through them. Using the example of Tobin’s ultra-Keynesian model I will show how many of the epistemic characteristics of modelling tend to go unrecognised if too much focus is placed on the model-target dyad. (shrink)

In this paper I argue, first, that ecologists have routinely treated humans—or more specifically, anthropogenic causal factors—as disturbing conditions. I define disturbing conditions as exogenous variables, variables “outside” a model, that when present in a target system, inhibit the applicability or accuracy of the model. This treatment is surprising given that humans play a dominant role in many ecosystems and definitions of ecology contain no fundamental distinction between human and natural. Second, I argue that the treatment of humans as disturbing (...) conditions is an idealization: since it is, and has long been, known that humans are pervasive, this treatment amounts to an intentionally introduced theoretical distortion. Finally, characterizing this treatment as idealization forces us to confront the question of its justification, and so, drawing on three different kinds of idealization, I evaluate how this treatment may be justified. (shrink)

New technologies not only contribute greatly to society and the economy; they also involve fundamental societal shifts, challenging our values and ideas about ourselves and the world. With a view to aligning technological change and innovation with ethical values, the concept of responsible innovation advocates the inclusion of a variety of stakeholders, in particular from society. In shifting moral responsibility towards the producers of innovations, responsible innovation rejects the standard normative economic view that the ethical evaluation of innovations is a (...) matter of individual consumers’ market-based choices. However, in this article we argue that responsible innovation should not abandon all normative consideration of the individual outright, to which end we present an alternative normative economic approach based on preference learning. We show how this approach can provide an enhanced understanding of responsible innovation by clarifying the redistribution of moral responsibility and casting individuals in the normative role of co-innovators, rather than mere consumers. We argue that responsible innovation should enable individuals to form preferences and evaluate innovations, so as to align innovation with ethical demands. Finally, we show how our proposed approach can be put into practice in so-called laboratories in real-world contexts, using methods from the field of design. In short, drawing on normative economics, this article aims to establish a new understanding of responsible innovation that is conceptually sound and can form the basis for novel innovation practices. (shrink)

In the eyes of its practitioners, economics is both a deductive science and an empirical science. The starting point of its deductions might be thought of as first principles. But what is the status of such principles? The tension between foundationalism, the idea that there are necessary and secure first principles for economic inquiry, and fallibilism, the idea that no belief can be certified as true beyond the possibility of doubt, is explored. Empirical disciplines require some sort of falsifiability. Yet, (...) empirical inquiries also require a starting place—if not a necessarily true one, at least an indubitable one, that is, one that is not actually doubted. Indubitability appears to have necessary consequences, undercutting fallibilism, while fallibilism threatens confidence in the de facto first principles that begin inquiry. This tension is examined in three well-known attempts to define economics and its method: John Stuart Mill’s economics as the science of wealth, Lionel Robbins’s economics as constrained optimization; and George Stigler and Becker’s attempt to reformulate neoclassical economics to square empiricism with Robbins’ deductivism. (shrink)

This essay attempts to distinguish the pressing issues for economists and economic methodologists concerning realism in economics from those issues that are of comparatively slight importance. In particular I shall argue that issues concerning the goals of science are of considerable interest in economics, unlike issues concerning the evidence for claims about unobservables, which have comparatively little relevance. In making this argument, this essay raises doubts about the two programs in contemporary economic methodology that raise the banner of realism. In (...) particular I argue that the banner makes it more difficult to relate the concerns of those who wave it to those of other methodologists. Although this essay argues that many of the debates in this century between scientific realists and their opponents are not relevant to economics, it does not attack scientific realism, and it does not urge economists or economic methodologists to reject it. (shrink)

The Inexact and Separate Science of Economics offers an overview of standard microeconomics and general equilibrium theory. These are not the whole of orthodox economics, and orthodox economics is not the whole of economics. But orthodox economics dominates the profession, and the theoretical core of microeconomics and general equilibrium theory – what I called ‘equilibrium theory’ – is central to most orthodox economics. Unlike many methodological works, which focus almost exclusively on the empirical problems of equilibrium theory and its applications, (...) ISSE is also concerned with the structure, strategy and heuristics of equilibrium theorizing, and it attempts to link questions about theory appraisal to questions about structure and strategy. It is addressed both to philosophers interested in epistemological questions posed by the social sciences and to economists interested in reflecting on and improving their discipline. Its inspiration lies in the work of John Stuart Mill. (shrink)

This paper examines methodological issues raised by revealed preference theory in economics: particularly contemporary revealed preference theory. The paper has three goals. First, to make the case that revealed preference theory is a broad research program in choice theory—not a single theory—and understanding this diversity is essential to any methodological analysis of the program. Second, to explore some of the existing criticisms of revealed preference theory in a way that emphasizes how the effectiveness of the critique depends on the particular (...) version of revealed preference under consideration. Finally, three additional criticisms are presented that are aimed specifically at contemporary revealed preference theory. (shrink)

ABSTRACTIn Against Democracy, Jason Brennan argues that public ignorance undermines the legitimacy of democracy because, to the extent that ignorant voters make bad policy choices, they harm their own and one another’s interests. The solution, he thinks, is epistocracy, which would leave policy decisions largely in the hands of social-scientific experts or voters who pass tests of political knowledge. However, Brennan fails to explain why we should think that these putative experts are sufficiently knowledgeable to avoid making errors as damaging (...) as those made by voters. Given the strong link between political knowledge and ideological dogmatism, as well as the tendency of social scientists to disagree with one another, the case for epistocracy is deeply implausible, at best. Moreover, given that there are important non-instrumental justifications of democracy—justifications of which Brennan appears to be radically ignorant—the epistocratic alternative would be unnecessary even if it were viable. (shrink)

Many scientific models lack an established representation relation to actual targets and instead refer to merely possible processes, background conditions, and results. This article shows how such models can be appraised. On the basis of the discussion of how-possibly explanations, five types of learning opportunities are distinguished. For each of these types, an example—from economics, biology, psychology, and sociology—is discussed. Contexts and purposes are identified in which the use of a model offers a genuine opportunity to learn. These learning opportunities (...) offer novel justifications for modeling practices that fall between the cracks of standard representationalist appraisals of models. (shrink)

Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to (...) explicate in virtue of what properties or features minimal models supposedly prompt learning and for substantially overstating the epistemic import of minimal models. I then examine and refute several arguments one may put forward to demonstrate that consideration of minimal models can prompt learning about real-world targets. In doing so, I illustrate the implications of my critique for the wider debate on the epistemology of scientific modelling. (shrink)

In recent years, several authors have reconstructed the relationship between 20th-century economic theory and neuro-psychological research in terms of a three-stage narrative of initial unity, increasing separation, and ongoing reunification. In this article, I draw on major developments in economic theory and neuro-psychological research to provide a descriptive and normative critique of this reconstruction. Moreover, I put forward a reconstruction of the relationship between economics and neuro-psychology that, I claim, better fits both the available empirical evidence and the methodological foundations (...) of these disciplines. In doing so, I argue that recent calls to develop a unified interdisciplinary framework for modeling choice are premised on disputable presuppositions concerning both the domain of economic theory and the relationship between this theory’s axiomatic foundations and empirical findings about the neuro-psychological substrates of choice. (shrink)

Over the last decade, neuroeconomic research has attracted increasing attention by economic modellers and methodologists. In this paper, I examine five issues about neuroeconomic modelling and methodology that have recently been subject to considerable controversy. For each issue, I explicate and appraise prominent neuroeconomists' findings, focusing on those that are claimed to directly inform economic theorizing. Moreover, I assess often-made assertions concerning how neuroeconomic research putatively advances the economic modelling of choice. In doing so, I combine review and critical arguments (...) to provide a methodological evaluation of neuroeconomists' contributions. (shrink)

This paper consists of four parts. Part 1 is an introduction. Part 2 evaluates arguments for the claim that there are no strict empirical laws in biology. I argue that there are two types of arguments for this claim and they are as follows: (1) Biological properties are multiply realized and they require complex processes. For this reason, it is almost impossible to formulate strict empirical laws in biology. (2) Generalizations in biology hold contingently but laws go beyond describing contingencies, (...) so there cannot be strict laws in biology. I argue that both types of arguments fail. Part 3 considers some examples of biological laws in recent biological research and argues that they exemplify strict laws in biology. Part 4 considers the objection that the examples in part 3 may be strict laws but they are not distinctively biological laws. I argue that given a plausible account of what distinctively biological means, such laws are distinctively biological. (shrink)