This is the most comprehensive book ever published on philosophical methodology. A team of thirty-eight of the world's leading philosophers present original essays on various aspects of how philosophy should be and is done. The first part is devoted to broad traditions and approaches to philosophical methodology. The entries in the second part address topics in philosophical methodology, such as intuitions, conceptual analysis, and transcendental arguments. The third part of the book is devoted to essays about the interconnections between philosophy (...) and neighbouring fields, including those of mathematics, psychology, literature and film, and neuroscience. (shrink)

The books’ goal is to answer the question: Do the weaknesses of value-free economics imply the need for a paradigm shift? The author synthesizes criticisms from different perspectives (descriptive and methodological). Special attention is paid to choices over time, because in this area value-free economics has the most problems. In that context, the enriched concept of multiple self is proposed and investigated. However, it is not enough to present the criticisms towards value-free economics. For scientists, a bad paradigm is better (...) than no paradigm. Therefore, the author considers whether value-based economics with normative approaches such as economics of happiness, capability approach, libertarian paternalism, and the concept of multiple self can be the alternative paradigm for value-free economics. This book is essential reading to everyone interested in the current state of economics as a discipline. (shrink)

This open access book provides an exploration of the consequences of the ontological differences between natural and social objects (sometimes described as objects of nature and objects of thought) in the workings of causal and agency relationships. One of its important and possibly original conclusions is that causal and agency relationships do not encompass all of the dependent relationships encountered in social life. The idea that social reality is contingent has been known (and largely undisputed) at least since Wittgenstein’s “On (...) Certainty”, but social science, and most notably economics has continued to operate on the basis of causal and agency theories borrowed or adapted from the natural sciences. This volume contains essays that retain and justify the partial or qualified use of this approach and essays that totally reject any use of causal and agency theory built on determined facts (closed systems).The rejection is based on the possibly original claim that, whereas causation in the objects of the natural sciences reside in their properties, human action is a matter of intentionality. It engages with critical realist theory and re-examines the role of free will in theories of human action in general and economic theory in particular. (shrink)

Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...) I argue that the objection does not stand up to scrutiny. This is because it is riddled with a number of conceptual inconsistencies. By attempting to resolve the tensions, I also draw several general lessons regarding the difficulties of applying abstraction and idealization in scientific practice. Finally, I argue that more care is needed only when speaking of abstraction and idealization in a context in which these concepts play an important role in an argument, such as that on mechanistic 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)

Archaeological data are shadowy in a number of senses. Not only are they notoriously fragmentary but the conceptual and technical scaffolding on which archaeologists rely to constitute these data as evidence can be as constraining as it is enabling. A recurrent theme in internal archaeological debate is that reliance on sedimented layers of interpretative scaffolding carries the risk that “preunderstandings” configure what archaeologists recognize and record as primary data, and how they interpret it as evidence. The selective and destructive nature (...) of data capture in archeology further suggests that there may be little scope for putting “legacy” data to work in new ways. And yet archaeologists have been strikingly successful in mining old datasets for new insights. I situate these concerns in the broader context of debate about the epistemic standing of the historical sciences, and then consider three strategies by which archaeologists address the challenges posed by legacy data. The first two – secondary retrieval and recontextualization – are a matter of reconfiguring the scaffolding that underpins evidential reasoning. The third turns on redeploying old data in the context of computational models that support the experimental simulation of the cultural systems and contexts under study. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...) of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

In the late 1990s, computational technology had advanced sufficiently that astrophysicists were able to construct reasonably high resolution computer simulations of the Local Group of galaxies. These simulations indicated there should be around 250 small satellite galaxies orbiting the Milky Way and Andromeda. In the real Local Group, however, only around 40 satellites had been observed, and only twenty or so more have been discovered since then. Despite this discrepancy in numbers, claims have been made in recent years that the (...) ‘missing satellites problem’ has been solved. Using the examples of the constructed luminosity curve, and hydrodynamic simulations, this paper explores how simulations are used in conjunction with observation to ‘solve’ the missing satellites problem. It is suggested that the simulated universes have sufficient complexity to be understood as worlds in their own right, ones that can be measured and observed. By demonstrating that these virtual worlds are sufficiently ‘realistic’ with respect to observations, astrophysicists are able to make a robust argument for the existence of ‘dark’, non-observable astrophysical objects. Observational and simulated data are combined to demonstrate the plausibility—a term that develops more ontologically meaningful connotations—of both the existence and the maintenance of dark satellites. It is thus through the conflation of the real and virtual worlds, the blending of simulation data with empirical data, that the missing satellites problem is ‘solved’. (shrink)

How should institutions be designed that “work” in bringing about desirable social outcomes? I study a case of successful institutional design—the redesign of the National Resident Matching Program...

Scientific models are used to predict and understand the target phenomena in the reality. The kind of epistemic relationship between the model and the reality is always regarded by most of the philosophers as a representational one. I argue that, complementary to this representational role, some of the scientific models have a constructive role to play in altering and reconstructing the reality in a physical way. I hold that the idealized model assumptions and elements bestow the constructive force of a (...) model on the reality. By recognizing the physical constructive force of some scientific models, the merit of these models could be judged by how successful they are in the reality construction, rather than by the traditional criterion of model-world representation. (shrink)

Scientific models consist of fictitious elements and assumptions. Various attempts have been made to answer the question of how a model, which is sometimes viewed as a fiction, can explain or predict the target phenomenon adequately. I examine two accounts of models-as-fictions which are aiming at disentangling the myth of representing the reality by fictional models. I argue that both views have their own weaknesses in spite of many virtues. I propose to re-evaluate the problems of representation from a novel (...) perspective in which some of the model representations can be regarded as fictional representations. I argue that this type of model representation is credible despite being a fictional representation of the reality. (shrink)

ion is one of the important processes in scientific modeling. It has always been implied that abstraction is an agent-centric activity that involves the cognitive processes of scientists in model building. I contend that there is an autonomous aspect of abstraction in many modeling activities. I argue that the autonomous process of abstraction is continuous with the agent-centric abstraction but capable of evolving independently from the modeler’s abstraction activity.

In a broad brush, biological models are often constructed in two general types: as a concrete model; as an abstract model. A concrete model is a material model such as model organisms, while an abstract model is a mathematical or computational model consists of equations or algorithms. Though there are types of biological models that cannot be strictly categorized as either concrete or abstract, they are falling somewhere in between this spectrum. In view of the fact that biological phenomena are (...) sui generis and distinct from physical phenomena in many respects, using the concepts in standard modeling fails to account for the differences between biological sciences and physical sciences. Drawing from the resources of a credible-world account of models in economic modeling, I propose to reinterpret abstract models and concrete models in the light of the credible world account of models. (shrink)

In November 2015, after weeks of bitter political rhetoric and much discussion about the consequences of the proposed changes, the UK Tory government reversed their decision to eliminate tax credits for the poorest. While much was made of this reversal, particularly who deserved responsibility for the change, a more subtle politics was going on behind the scenes. The primary justification for the reversal, given by the Chancellor George Osborne, was that tax revenues in forthcoming years were now expected to be (...) much higher than before. Yet, a deeper look into this justification revealed that 55% of those extra revenues came from “modelling changes”. Suddenly, the discursive sparring over tax revenues found its material embodiment in the computers of the Office for Budget Responsibility. Similarly, central bank policies have become essential to the global economy since the 2008 crisis, and their policies concerning interest rates and quantitative easing are the joint product of hybrid human–computer systems. Yet, while scholars have examined the influence of modelling technology on derivatives valuation models, the field of central bank macroeconomic modelling has been largely ignored. This paper will examine these government economic models, outlining a broad history of their changing political ramifications. What are these models? How can they change the possibilities of government action so much? In addition, what effect do they have on politicians? Do they function merely as post-hoc justification for policies, or do they give shape to the space of the politically possible? The aim of this project is to begin answering these questions and generate a framework for understanding how economic modelling is shaping and interacting with economic policy. (shrink)

The standard view in current philosophy of creativity says that being creative has two requirements: being novel and being valuable. The standard view on creativity has recently become an object of critical scrutiny. Hills and Bird have specifically proposed to remove the value requirement from the definition, as it is not clear that creative objects are necessarily valuable or creative people necessarily praiseworthy. In this paper, I argue against Hills and Bird, since eliminating the element of value from the explanation (...) of creativity hinders the understanding of the role that creative products play in actual epistemic practices, which are fundamentally normative. More specifically, I argue that the terms ‘creativity’ and ‘creative’ function as thick epistemic concepts when employed by competent epistemic agents in practice, that is, these concepts have both a descriptive and an evaluative content that cannot be disentangled from one another. Accordingly, I suggest that philosophers should prefer thick accounts over thin accounts of creativity. A thick account of creativity is one that endorses the standard view at its basis, but further develops it in two ways: by stressing the entanglement of the value and novelty requirements; by permitting to encompass a range of domain-specific characterizations of such entanglement for different epistemic situations. In order to take the first steps in the development of such a thick account of creativity, I look at the domain of scientific practices as a case in point, and try to spell out what the thickness of creative instances typically entails here. Namely, I identify the worthy novelty of creative models and methods with their potential to clarify a tradition, with fruitfulness, and with the fulfilment of exploratory aims. (shrink)

Philosophers of science have recently taken care to highlight different modeling practices where scientific models primarily contribute modal information, in the form of for example possibility claims, how-possibly explanations, or counterfactual conditionals. While examples abound, comparatively little attention is being paid to the question of under what conditions, and in virtue of what, models can perform this epistemic function. In this paper, we firstly delineate modal modeling from other modeling practices, and secondly reviewattempts to spell out and explain the epistemic (...) success conditions of modal modeling. The aim is to more clearly expose the respective justificatory strategies of these accounts, and secondly, to identify lacunae where further work is needed. (shrink)

It is undeniable that much scientific work is model-based. Despite this, the justification for this reliance on models is still controversial. A particular difficulty here is the fact that many scientific models are based on assumptions that do not describe the exact details of many or even any empirical situations very well. This raises the question of why it is that, despite their frequent lack of descriptive accuracy, employing models is scientifically useful.One..

Brian Epstein has recently argued that a thoroughly microfoundationalist approach towards economics is unconvincing for metaphysical reasons. Generally, Epstein argues that for an improvement in the methodology of social science we must adopt social ontology as the foundation of social sciences; that is, the standing microfoundationalist debate could be solved by fixing economics’ ontology. However, as I show in this paper, fixing the social ontology prior to the process of model construction is optional instead of necessary and that metaphysical-ontological commitments (...) are often the outcome of model construction, not its starting point. By focusing on the practice of modeling in economics the paper provides a useful inroad into the debate about the role of metaphysics in the natural and social sciences more generally. (shrink)

Stephen T. Casper and Steve Fuller’s commentaries on my paper “Completing Circle of the Social Sciences? William Beveridge and Social Biology at the London School of Economics during the 1930s” raises important questions about the historical entanglement of the political left, welfarism, biology, and social science. In this response, I clarify questions about my analysis of events at the London School of Economics in the early twentieth century and identify ways in which they are important in the present. I suggest (...) that there is much to be learned from the school’s failed experiment with social biology, not least when it comes to thinking about the historical contingency of relationships between progressive politics and biology. (shrink)

On the basis of a case study in bioengineering, this paper proposes a novel perspective on models in science and engineering. This is done with the help of two notions: representation and design. These two notions are interpreted as referring to modeling relations between vehicles and targets that differ in their respective directions of fit. The representation relation has a vehicle-to-target direction of fit and the design relation has a target-to-vehicle direction of fit. The case study of an organ on (...) chip model illustrates that the technical device can participate in both design and representation relations. The two relations share the same relatum of the organ on chip, but they have different directions of fit. In the design relation, the chip is adjusted to a design plan, in which case we are dealing with a target-to-vehicle direction of fit. In the representation relation, the chip is adjusted to a human organ, in which case we are dealing with a vehicle-to-target direction of fit. The example shows that a conception of modeling as involving only relations with a vehicle-to-target direction of fit is too narrow to account for models in science and engineering. (shrink)

Despite the conclusions from the contemporary philosophy of science, many economists cherish the ideal of positive science. Therefore, value-free economics is still the central paradigm in economics. The first aim of the paper is to investigate economics' axiomatic assumptions from an epistemological perspective. The critical analysis of the literature shows that the positive-normative dichotomy is exaggerated. Moreover, value-free economics is based on normative foundations that have a negative impact on individuals and society. The paper's second aim is to show that (...) economics' normativity is not a problem because the discussion concerning values is possible and unavoidable. In this context, Weber and other methodologists are investigated. The conclusion of the paper is that science can thrive without strict methodological rules thanks to institutional mechanisms. Therefore, economists could learn from artists who accept the world without absolute rules. This perspective opens the possibility for methodological pluralism and normative approaches. (shrink)

In this article I connect two debates in the philosophy of science: the questions of scientific representation and both model and theoretical equivalence. I argue that by paying attention to how a model is used to draw inferences about its target system, we can define a notion of theoretical equivalence that turns on whether models license the same claims about the same target systems. I briefly consider the implications of this for two questions that have recently been discussed in the (...) context of the formal philosophy of science. (shrink)

In this article, I clarify some of the key concepts and commitments of realist social ontology in economics. To do so, I make use of a recent critique of Lawson’s Reorienting Economics by Mohun and Veneziani. Their article provides a useful foil because responding to their critique allows us to emphasize that realism’s claims are more conditional and less controversial than one might otherwise anticipate. The basic claim is that ontology matters and that explicit recognition and consideration of ontological issues (...) can be beneficial. However, developing a focus on ontology can create problems of interpretation among economists regarding what is being claimed and offered. I discuss some of these with reference to an adaption of Maki’s concept of economics imperialism and also with reference to Mary Morgan’s recent typology of experiments. (shrink)

Philosophers of science studying scientific practice often consider it a methodological requirement that their conceptualization of "model" closely connects with the understanding and use of models by practicing scientists. Occasionally, this connection has been explicitly made (Hutten 1954, Suppes 1961, Morgan and Morrison 1999, Bailer-Jones 2002, Lehtinen and Kuorikoski 2007, Kuorikoski 2007, Morgan 2012a). These studies have been dominated by a focus on the—relatively similar forms of—mathematical models in physics and economics. Yet it has become increasingly evident that the way (...) models are conceptualized is very different in some other sciences, where philosophers' accounts of models' characteristics and .. (shrink)

Graeme Earl's paper on computer graphic modeling in archaeology raises many themes of interest for the philosopher of science, although, as is to be expected of complex social and technical disciplinary practices, these philosophical issues are not to be easily separated or neatly labeled. On the one hand, the modeling practices and concerns of the archaeologists dispute (or even disrupt) the philosophers' traditional notions, while the formers' reective commentaries offer sophisticated analyses that go beyond the latters' traditional reflections on models. (...) On the other hand, the paper raises new questions about how human and social scientists—as humans with social lives—engage with models in their different .. (shrink)

In my paper I focus on the growth of knowledge in finance from an heuristic viewpoint and I propose the analysis of two different knowledge-advancing strategies usually adopted at the frontier of knowledge, i.e. problem-solving and model-building. I show how these two strategies, even though both effective in the short-run, nonetheless provide descriptions of the target object and which are different in their descriptive and knowledge-advancing depth. In order to do so, I propose a case study borrowed from the modelling (...) activities in the Libor market. (shrink)

In my paper I focus on the growth of knowledge in finance from an heuristic viewpoint and I propose the analysis of two different knowledge-advancing strategies usually adopted at the frontier of knowledge, i.e. problem-solving and model-building. I show how these two strategies, even though both effective in the short-run, nonetheless provide descriptions of the target object and which are different in their descriptive and knowledge-advancing depth. In order to do so, I propose a case study borrowed from the modelling (...) activities in the Libor market. (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)

Over time, Mark Blaug became increasingly sceptical of the merits of the approach to the history of economics that we find in his magnum opus, Economic theory in retrospect, first published in 1962, and increasingly leaned to favour 'historical' over 'rational' reconstructions. In this essay, I discuss Blaug's shifting historiographical position, and the changing terms of historiographical debate. I do so against the background of Blaug's personal life history and the increasingly beleaguered position the history of economic thought found itself (...) in after the Second World War. I argue that Blaug never resolved the tensions between historical and rational reconstructions, partly because he never fleshed out a viable notion of historical reconstruction. I trace Blaug's difficulty in doing so to his firm conviction that the history of economics should speak to economists, a conviction clearly present in his 2001 essay: "No history of ideas, please, we're economists". (shrink)

Since their inception in the 1980s, complexity sciences have been described as a revolutionary new domain of research. By describing some of the practices and assumptions of its representatives, the present article shows that this field is an association of subdisciplines laying on existing disciplinary footholds. The general question guiding us here is: On what basis do complexity scientists consider their inquiry methods and results as valuable? To answer it, I describe five “epistemic argumentative regimes,” namely the ways in which (...) complexity scientists argue the credibility of their research, and five “ontological views,” that is the ways in which they interpret the material and formal causes of their study objects and models. Finally, the article proposes the term of “regime of evidence” to designate the specific combination of one ontological view with one or more epistemic argumentative regimes. (shrink)

This paper proposes an account of scientific data that makes sense of recent debates on data-driven and ‘big data’ research, while also building on the history of data production and use particularly within biology. In this view, ‘data’ is a relational category applied to research outputs that are taken, at specific moments of inquiry, to provide evidence for knowledge claims of interest to the researchers involved. They do not have truth-value in and of themselves, nor can they be seen as (...) straightforward representations of given phenomena. Rather, they are fungible objects defined by their portability and prospective usefulness as evidence. (shrink)

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (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)

Deidealization as a topic in its own right has attracted remarkably little philosophical interest despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, deidealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal (...) thesis would have us believe, and deidealization emerges as a creative part of modeling. (shrink)

This paper presents an artifactual approach to models that also addresses their fictional features. It discusses first the imaginary accounts of models and fiction that set model descriptions apart from imagined-objects, concentrating on the latter :251–268, 2010; Frigg and Nguyen in The Monist 99:225–242, 2016; Godfrey-Smith in Biol Philos 21:725–740, 2006; Philos Stud 143:101–116, 2009). While the imaginary approaches accommodate surrogative reasoning as an important characteristic of scientific modeling, they simultaneously raise difficult questions concerning how the imagined entities are related (...) to actual representational tools, and coordinated among different scientists, and with real-world phenomena. The artifactual account focuses, in contrast, on the culturally established external representational tools that enable, embody, and extend scientific imagination and reasoning. While there are commonalities between models and fictions, it is argued that the focus should be on the fictional uses of models rather than considering models as fictions. (shrink)

Agent-based models are increasingly important in social science research. They have two obvious apparent virtues: they can model complex macrosociological phenomena without strong assumptions about agents and without analytic solutions for models, and they seem to instantiate the methodological individualist program in a concrete way. We argue that the latter claim is false. After providing schematic accounts of ABM models and a first introduction to ways in which to characterize individualist explanations, we work through six conceptions of individualist explanations that (...) are decreasingly "less individualist" and argue that ABM-based explanations in the social sciences are not inevitably individualist in any of these senses. ABMs allow for explanatory relations among social entities and properties in the model environment and they are silent on what basic agents are, allowing social entities and properties to play basic explanatory roles. (shrink)

La filosofía estándar de la economía presupone que en el dominio de los fenómenos económicos subyacen regularidades estables, las cuales pueden explicarse mediante el funcionamiento de mecanismos o de máquinas socioeconómicas. Asimismo, se considera que una vez puestos en funcionamiento, su comportamiento no necesita de subsecuentes intervenciones. Esto implica asumir que los procesos socioeconómicos tienen una naturaleza semejante a los de las ciencias naturales. No obstante, dichas regularidades son por lo general examinadas a la luz de algún modelo económico, por (...) lo cual pierden muchas veces contacto con el mundo real. Este trabajo tiene como objetivo poner en el centro del análisis otro objeto de estudio: los procesos económicos basados en expectativas. Se trata de procesos en los cuales la acción humana funciona como nexo causal entre las variables económicas y en los que dicha acción es producto de una formación previa de expectativas, las cuales son sensibles a la información del contexto. Se mostrará que en esta clase de procesos la intervención sistemática sobre las condiciones de fondo y sobre las expectativas es fundamental si lo que se busca es alcanzar un objetivo deseado o lograr un proceso estable. Esta intervención requerirá no solo del conocimiento proporcionado por los modelos, sino también de un conocimiento extrateorético o interdisciplinario. Mainstream philosophy of economics assumes that steady regularities underlie the domain of economic phenomena which can be explained by the operation of mechanisms or socioeconomic machines. It is also considered that once operating those mechanisms don't need further interventions. This implies the assumption that the nature of socioeconomic processes is similar to the one of the natural sciences. Nevertheless, such regularities are usually examined in the light of some economic model, which often ends up losing contact with the real world. The present paper aims at putting in the center of the analysis another object of study: the economic processes based on expectations. In these processes the human action operates as a causal link between economic variables; such an action being the result of a previous building of expectations which are sensitive to the information of the context. It will be shown that the systematic intervention on the background conditions and expectations is fundamental in this kind of processes if what is sought is fulfilling a desired goal or managing a stable process. That intervention will not only require the knowledge provided by models but also an extra-theoretical or interdisciplinary knowledge. (shrink)

1. A multidisciplinary group of scholars within the International Commission on Stratigraphy – known as the Anthropocene Working Group – recently recommended the Anthropocene as a new geological ep...

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)

Since the early days of economics, the rationality principle has been a core element of economic theorizing. It is part of almost any theoretical framework that economists use to generate knowledge. Despite its central role, the principle’s epistemic status and function continue to be debated between empiricists and rationalists, and a clear winner is yet to emerge. One point of contention is that we cannot explain the principle’s special status in light of clear evidence against its empirical validity and the (...) continuous conceptual changes it undergoes. In this paper, I argue that we should think of the rationality principle as a functional a priori principle along the lines of a pragmatic theory of constitutive elements recently put forward by David Stump. Such an approach would explain the principle’s persistence and changing status. More generally, the pragmatic theory of constitutive elements in science offers a viable alternative to rationalism and empiricism that allows for approaching the debate about the status and function of the rationality principle in economics. It provides a new framework and starting point to think about the usefulness of a central first principle in economics in a constructive way. (shrink)

This paper supports the literature which argues that derivational robustness can have epistemic import in highly idealized economic models. The defense is based on a particular example from mathematical economic theory, the dynamic Walrasian general equilibrium model. It is argued that derivational robustness first increased and later decreased the credibility of the Walrasian model. The example demonstrates that derivational robustness correctly describes the practices of a particular group of influential economic theorists and provides support for the arguments of philosophers who (...) have offered a general epistemic justification of such practices. (shrink)

We argue that the robustness analysis of idealized models can have confirmational power. This responds to concerns recently raised in the literature, according to which the robustness analysis of models whose idealizations are not discharged is unable to confirm the causal mechanisms underlying these models, and the robustness analysis of models whose idealizations are discharged is unnecessary. In response, we make clear that, where idealizations sweep out, in a specific way, the space of possibilities— which is sometimes, though not always, (...) the case—they can be holistically discharged. In turn, this can be used to show that the robustness analysis of idealized models can have confirmational force after all. (shrink)

Many scientific models are representations. Building on Goodman and Elgin’s notion of representation-as we analyse what this claim involves by providing a general definition of what makes something a scientific model, and formulating a novel account of how they represent. We call the result the DEKI account of representation, which offers a complex kind of representation involving an interplay of, denotation, exemplification, keying up of properties, and imputation. Throughout we focus on material models, and we illustrate our claims with the (...) Phillips-Newlyn machine. In the conclusion we suggest that, mutatis mutandis, the DEKI account can be carried over to other kinds of models, notably fictional and mathematical models. (shrink)