Las corrientes manipulabilistas tradicionales consideran que una implementación de política efectiva debe estar fundamentada en un conocimiento invariante. Este modo de pensamiento está basado en el supuesto ontológico de que existen factores causales estables tanto en las ciencias naturales como en las sociales. También asumen que un sólo tipo de intervención ex-ante es pertinente para una implementación efectiva. En el presente artículo se realizará una crítica a estos enfoques. En particular, se mostrará que los procesos sociales responden a una lógica (...) de “árboles de posibilidades” o “resultados de final abierto”. Sobre la base de esta variante ontológica se argumentará que más que un conocimiento de factores invariantes, el sustento de una buena política debe buscarse en los condicionamientos explicitados dentro de un anteproyecto y en la factibilidad de que los mismos se satisfagan en el sistema objetivo. Asimismo, se mostrará cómo las típicas intervenciones ex-ante no son adecuadas en el reino de lo social. Contrario a ellos, las intervenciones deberán ser sistemáticas. (shrink)

What is natural selection? I address this question by exploring the relation between two debates: Is natural selection a mechanism? Is natural selection a causal or a statistical theory? I argue that the first can be assessed only relative to a model and that, following the second, there are two fundamentally different and independent kinds of models, Modern-Synthesis and Darwinian models. MS-models, I argue, are not mechanistic even if they are causal. D-models, in contrast, are mechanistic. A causal-mechanistic interpretation of (...) D-models is thus compatible with a statistical interpretation of MS-models. Natural selection, I conclude, lacks a single, unifying nature. (shrink)

The goal of this article is to show that formal analysis and reconstructions may be useful to discuss and shed light on substantive meta-theoretical issues. We proceed here by exemplification, analysing and reconstructing as a case study a paradigmatic biochemical theory, the Monod-Wyman-Changeux theory of allosterism, and applying the reconstruction to the discussion of some issues raised by prominent representatives of the new mechanist philosophy. We conclude that our study shows that at least in this case mechanicism and more traditional (...) accounts are not rivals but complementary approaches. (shrink)

One might have thought that if something has two or more distinct realizations, then that thing is multiply realized. Nevertheless, some philosophers have claimed that two or more distinct realizations do not amount to multiple realization, unless those distinct realizations amount to multiple “ways” of realizing the thing. Corey Maley, Gualtiero Piccinini, Thomas Polger, and Lawrence Shapiro are among these philosophers. Unfortunately, they do not explain why multiple realization requires multiple “ways” of realizing. More significantly, their efforts to articulate multiple (...) “ways” of realizing turn out to be problematic. (shrink)

Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock (...) and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. (shrink)

An underlying assumption in computational approaches in cognitive and brain sciences is that the nervous system is an input–output model of the world: Its input–output functions mirror certain relations in the target domains. I argue that the input–output modelling assumption plays distinct methodological and explanatory roles. Methodologically, input–output modelling serves to discover the computed function from environmental cues. Explanatorily, input–output modelling serves to account for the appropriateness of the computed function to the explanandum information-processing task. I compare very briefly the (...) modelling explanation to mechanistic and optimality explanations, noting that in both cases the explanations can be seen as complementary rather than contrastive or competing. (shrink)

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of mechanistic reasoning where it is (...) not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences. (shrink)

RESUMEN Se critican dos tesis de Nancy Cartwright. Por un lado, se examina el enfoque de las "capacidades" en el campo de lo económico para argumentar que estas responden a la lógica de los "árboles de posibilidades" o resultados de final abierto; por el otro, se ofrece una alternativa al problema de "sobre-restricción" de los modelos económicos para mostrar cómo el gran número de supuestos auxiliares acota las posibilidades de extrapolar las conclusiones obtenidas en el modelo a condiciones distintas de (...) las explicitadas en él. Se muestra la utilidad del análisis de robustez para descubrir las condiciones esenciales que cierran el árbol de posibilidades. ABSTRACT The article criticizes two of Nancy Cartwright's theses. On the one hand, it examines the capabilities approach in the field of economics in order to argue that those capabilities function according to the logic of probability trees or open-ended results. On the other hand, it proposes an alternative to the problem of "over-restriction" of economic models, in order to show that the great number of auxiliary assumptions limits the possibilities of extrapolating the conclusions drawn from the model to conditions other than those it takes into account. The article shows the utility of robustness analysis in order to discover the essential conditions that surround the tree of probabilities. (shrink)

Biochemists often adopt what may be called the “Strategy of Decomposition” for the causal discovery of biochemical pathway dynamic behaviours. This involves decomposing a pathway into a set of isolated parts, which are then analysed separately. It is assumed that knowledge gained of the isolated parts can then be used to explain the dynamic behaviours of the whole pathway. My thesis addresses the extent to which use of the Strategy of Decomposition is warranted. I evaluate two challenges contained in Bechtel (...) and Richardson’s Discovering Complexity. The first challenge is that pathways lack the ‘modular’ structure assumed in the Strategy of Decomposition. Bechtel and Richardson take biochemists to use a concept of modularity called ‘near decomposability’. The second challenge is that pathways have ‘Pathway Emergent’ behaviours. I reject both challenges. I show that near decomposability is the wrong type of modularity to apply to pathways, and that the occurrence of Pathway Emergence has not been established. I argue that an underlying problem with Bechtel and Richardson’s analyses is that they overstate the consequences of feedback and nonlinearity for the Strategy of Decomposition. Instead, the analysis of pathway modularity and emergence needs to be centered on the context-sensitivity of pathways’ ‘local causal laws’. I identify that the type of modularity assumed in the Strategy of Decomposition is ‘causal law modularity’, which requires the invariance of local causal laws. I also identify a necessary condition for Pathway Emergence: a pathway must manifest at least one local causal law that is not manifested by its isolated parts. I argue that the use of the Strategy of Decomposition may often be unwarranted. This is because the local causal laws of pathways are highly context-sensitive, and pathways might often not be causal law modular. This context-sensitivity also leaves open the possibility of Pathway Emergence. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

It is widely assumed that mechanistic explanations are causal explanations. Many prominent new mechanists endorse interventionism as the correct analysis of explanatory causal models in biology and other fields. This article argues that interventionism is not entirely satisfactory in this regard. A case study of Jacob and Monod’s operon model shows that at least some important mechanistic explanations in biology present significant contrasts with the interventionist account. This result motivates a more inclusive approach to mechanistic explanation, allowing for noncausal aspects.

This paper describes a pattern of explanation prevalent in the biological sciences that I call a ‘lineage explanation’. The aim of these explanations is to make plausible certain trajectories of change through phenotypic space. They do this by laying out a series of stages, where each stage shows how some mechanism worked, and the differences between each adjacent stage demonstrates how one mechanism, through minor modifications, could be changed into another. These explanations are important, for though it is widely accepted (...) that there is an ‘incremental constraint’ on evolutionary change, in an important class of cases it is difficult to see how to satisfy this constraint. I show that lineage explanations answer important questions about evolutionary change, but do so by demonstrating differences between individuals rather than invoking population processes, such as natural selection.1. Introduction2. Turning a ‘Scale’ into a ‘Plume’3. Lineage Explanations in Biology3.1. The evolution of eyes3.2. The evolution of feathers4. The Two Dimensions of a Lineage Explanation4.1. The production dimension4.2. The continuity dimension4.3. The dual role of the parts5. Constraining the Explanations6. Operational and Generative Lineages7. Explaining Change Without Populations8. Conclusion. (shrink)

We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...) behaviour. We discuss some ways that the search for mechanisms can bring about such top-down and bottom-up revision, and we consider some examples from the recent neuroeconomics literature of how varieties of progress of this sort might be achieved. (shrink)

Among philosophers of science, there is now a widespread agreement that the DN model of explanation is poorly equipped to account for explanations in biology. Rather than identifying laws, so the consensus goes, researchers explain biological capacities by constructing a model of the underlying mechanism.We think that the dichotomy between DN explanations and mechanistic explanations is misleading. In this article, we argue that there are cases in which biological capacities are explained without constructing a model of the underlying mechanism. Although (...) these explanations do not conform to Hempel’s DN model, they do invoke more or less stable generalisations. Because they invoke generalisations and have the form of an argument, we call them inferential explanations. We support this claim by considering two examples of explanations of biological capacities: pigeon navigation and photoperiodism. Next, we will argue that these non-mechanistic explanations are crucial to biology in three ways: sometimes, they are the only thing we have, they are heuristically useful, and they provide genuine understanding and so are interesting in their own right.In the last sections we discuss the relation between types of explanations and types of experiments and situate our views within some relevant debates on explanatory power and explanatory virtues. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

Despite the miraculous progress of science—it’s practitioners continue to run into mistakes, either discrediting research unduly or making leaps of causal inference where none are warranted. In this we isolate two of the reasons for such behavior involving the misplaced understanding of the role of mechanisms and mechanistic knowledge in the establishment of cause-effect relationships. We differentiate causal knowledge into causes, effects, mechanisms, cause-effect relationships, and causal stories. Failing to understand the role of mechanisms in this picture, including their absence (...) of knowledge or incorrect specification, leads to errors of wrongly excluding cause-effect relationships or wrongly inferring their existence. We highlight the primary of causality over mechanistic knowledge and causal stories in scientific reasoning. (shrink)

In this article, I develop an account of the use of intentional predicates in cognitive neuroscience explanations. As pointed out by Maxwell Bennett and Peter Hacker, intentional language abounds in neuroscience theories. According to Bennett and Hacker, the subpersonal use of intentional predicates results in conceptual confusion. I argue against this overly strong conclusion by evaluating the contested language use in light of its explanatory function. By employing conceptual resources from the contemporary philosophy of science, I show that although the (...) use of intentional predicates in mechanistic explanations sometimes leads to explanatorily inert claims, intentional predicates can also successfully feature in mechanistic explanations as tools for the functional analysis of the explanandum phenomenon. Despite the similarities between my account and Daniel Dennett's intentional-stance approach, I argue that intentional stance should not be understood as a theory of subpersonal causal explanation, and therefore cannot be used to assess the explanatory role of intentional predicates in neuroscience. Finally, I outline a general strategy for answering the question of what kind of language can be employed in mechanistic explanations. (shrink)

This article reconsiders the theoretical role of the genetic code. By drawing on published and unpublished sources from the 1950s, I analyse how the code metaphor was actually employed by the scientists who first promoted its use. The analysis shows that the term ‘code’ picked out mechanism sketches, consisting of more or less detailed descriptions of ordinary molecular components, processes, and structural properties of the mechanism of protein synthesis. The sketches provided how-possibly explanations for the ordering of amino acids by (...) nucleic acids. I argue that employing the code metaphor was justified in virtue of its descriptive-denotational and explanatory roles, and because it highlighted a similarity with conventional codes that was particularly salient at the time. 1 Introduction2 Coding Schemes in the 1950s2.1 The research problem: Determining amino acid sequences2.2 The solution: Mapping schemes or ‘codes’3 The Code Metaphor Played Descriptive and Explanatory Roles4 Theness of Codes and the Expendability of the Code Metaphor5 The Role of Arbitrariness6 Conclusions. (shrink)

Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance of the (...) mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. (shrink)

The terms “perspectivism” and “perspectivalism” have been the focus of an intense philosophical discussion with important repercussions for the debate about the role of mechanisms in scientific explanations. However, leading exponents of the new mechanistic philosophy have conceded more than was necessary to the radically subjectivistic perspectivalism, and fell into the opposite error, by retaining not negligible residues of objectivistic views about mechanisms. In order to remove this vacillation between the subjective-cultural and the objective-natural sides of mechanisms, we shall raise (...) the question about theory-ladenness over again and interpret it in its connection with the technical–experimental nature of scientific knowledge, as affirming the perspectival character of scientific knowledge: It is because of the character at once theory-laden and practice-laden, i.e. technique-laden, of our putting questions to nature that empirical reality must be investigated from particular perspectives: nature can be known scientifically only from a potentially infinite number of perspectives or theoretical points of view, concretely exemplified by mechanisms or experimental ‘machines’ that allow specific access to specific aspects of sensible reality. (shrink)

Philosophical accounts of scientific explanation are broadly divided into ontic and epistemic views. This paper explores the idea that the lexical ambiguity of the verb to explain and its nominalisation supports an ontic conception of explanation (Salmon 1989; Craver 2007). I analyse one argument which challenges this strategy by criticising the claim that explanatory talk is lexically ambiguous (Wright, European Journal of Philosophy of Science 2(3), 375–394, 2012). I propose that the linguistic mechanism of transfer of meaning (Nunberg, Journal of (...) Semantics 12(2), 109–132, 1995) provides a better account of the lexical alternations that figure in the systematic polysemy of explanatory talk, and evaluate the implications of this proposal for the debate between ontic and epistemic conceptions of scientific explanation. (shrink)

I argue that difference-making should be a crucial element for evaluating the quality of evidence for mechanisms, especially with respect to the robustness of mechanisms, and that it should take central stage when it comes to the general role played by mechanisms in establishing causal claims in medicine. The difference- making of mechanisms should provide additional compelling reasons to accept the gist of Russo-Williamson thesis and include mechanisms in the protocols for Evidence- Based Medicine, as the EBM+ research group has (...) been advocating. (shrink)

Computational explanations focus on information processing required in specific cognitive capacities, such as perception, reasoning or decision-making. These explanations specify the nature of the information processing task, what information needs to be represented, and why it should be operated on in a particular manner. In this article, the focus is on three questions concerning the nature of computational explanations: What type of explanations they are, in what sense computational explanations are explanatory and to what extent they involve a special, “independent” (...) or “autonomous” level of explanation. In this paper, we defend the view computational explanations are genuine explanations, which track non-causal/formal dependencies. Specifically, we argue that they do not provide mere sketches for explanation, in contrast to what for example Piccinini and Craver :283–311, 2011) suggest. This view of computational explanations implies some degree of “autonomy” for the computational level. However, as we will demonstrate that does not make this view “computationally chauvinistic” in a way that Piccinini or Kaplan :339–373, 2011) have charged it to be. (shrink)

I propose a cautionary assessment of the recent debate concerning the impact of the dynamical approach on philosophical accounts of scientific explanation in the cognitive sciences and, particularly, the cognitive neurosciences. I criticize the dominant mechanistic philosophy of explanation, pointing out a number of its negative consequences: In particular, that it doesn’t do justice to the field’s diversity and stage of development, and that it fosters misguided interpretations of dynamical models’ contribution. In order to support these arguments, I analyze a (...) case study in computational neuroethology and show why it should not be understood through a mechanistic lens; I specially focus on Zednik’s mechanistic interpretation of the case study. In addition, I argue for a greater appreciation of the relation between explanation and other epistemic goals in the field, as well as an increased sensitivity towards the associated contextual factors. (shrink)

Much contemporary debate on the nature of mechanisms centers on the issue of modulating negative causes. One type of negative causability, which I refer to as "causation by absence," appears difficult to incorporate into modern accounts of mechanistic explanation. This paper argues that a recent attempt to resolve this problem, proposed by Benjamin Barros, requires improvement as it overlooks the fact that not all absences qualify as sources of mechanism failure. I suggest that there are a number of additional types (...) of effects caused by absences that need to be incorporated to account for the diversity of causal connections in the biological sciences. Furthermore, it is argued that recognizing natural variability in mechanisms, such as attenuation, leads to some interesting line-drawing issues for contemporary philosophy of mechanisms. (shrink)

The hunt for a biologically respectable definition for the folk concept of innateness is still on. I defend Ariew’s Canalization account of innateness against the criticisms of Griffiths and Machery, but highlight the remaining flaws in this proposal. I develop a new analysis based on the notion of environmental induction. A trait is innate, I argue, iff it is not environmentally induced. I augment this definition with a novel analysis of environmental induction that draws on the contrastive nature of causal (...) explanation. Whether a trait is environmentally induced, I argue, depends on a context sensitive contrast class. I argue that a “Noninduction” analysis of innateness allows the concept an explanatory role in biology. I show how my proposal co-opts the successes of the Canalization account whilst avoiding its pitfalls, and I account for why biologists associate a range of disparate properties with innateness. (shrink)

Philosophers have proposed various kinds of relations between Mendelian genetics and molecular biology: reduction, replacement, explanatory extension. This paper argues that the two fields are best characterized as investigating different, serially integrated, hereditary mechanisms. The mechanisms operate at different times and contain different working entities. The working entities of the mechanisms of Mendelian heredity are chromosomes, whose movements serve to segregate alleles and independently assort genes in different linkage groups. The working entities of numerous mechanisms of molecular biology are larger (...) and smaller segments of DNA plus related molecules. Discovery of molecular DNA mechanisms filled black boxes that were noted, but unilluminated, by Mendelian genetics. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

This paper argues that the form of explanation at issue in the hard problem of consciousness is scientifically irrelevant, despite appearances to the contrary. In particular, it is argued that the 'sense of understanding' that plays a critical role in the form of explanation implicated in the hard problem provides neither a necessary nor a sufficient condition on satisfactory scientific explanation. Considerations of the actual tools and methods available to scientists are used to make the case against it being a (...) necessary condition, and work by J.D. Trout that exploits psychological research on the hindsight and overconfidence biases is used to show that it is not a sufficient condition. It is argued, however, that certain intellectual and moral concerns give us good reason to still try to meet the hard problem's explanatory challenge, despite its extrascientific nature. (shrink)

While much of the recent literature on mechanisms has emphasized the superiority of mechanisms and mechanistic explanation over laws and nomological explanation, paradigmatic mechanisms—e.g., clocks or synapses—actually exhibit a great deal of stability in their behavior. And while mechanisms of this kind are certainly of great importance, there are many events that do not occur as a consequence of the operation of stable mechanisms. Events of natural and human history are often the consequence of causal processes that are ephemeral and (...) capricious. In this paper I shall argue that, notwithstanding their ephemeral nature, these processes deserve to be called mechanisms. Ephemeral mechanisms share important characteristics with their more stable cousins, and these shared characteristics will help us to understand connections between scientific and historical explanation. (shrink)

Most philosophical debate over mental causation has been concerned with reconciling commonsense intuitions that there are causal interactions between the mental and the physical with philosophical theories of the nature of the mental that seem to suggest otherwise. My concern is with a different and more practical problem. We often confront some cognitive, affective, or bodily phenomenon, and wonder about its source – its etiology or its underlying causal basis. For instance, you might wonder whether your queasiness due to something (...) you ate, or whether it is just nervousness, or whether your aunt’s memory loss is a neurological problem or a psychological response to trauma. Such questions attempt to localize the causes of a phenomenon at some level in the complex multi-level systems that we human animals are. In this paper I will attempt to tease out the sense of level implicit in such questions, and to show how it is related to current mechanistic accounts of levels. I will argue that the explanation of our practices of level attribution is deeply pragmatic. Such attributions are often attempts to locate the causes of problems, and to identify interventions that could solve those problems. (shrink)

The main models of scientific explanation assume the need for some kind of stable knowledge for assembling a good explanatory argument. While these approaches are useful in the natural sciences, it is doubtful that they are similarly applicable in the socioeconomic realm. In this paper it is expected to show that the logic of socioeconomic processes of being "possibility trees" or "open-ended results" makes regularities the exception rather than the rule. Alternatively, a mode of explanation that focuses on contextual factors (...) and people actions is proposed. Los principales modelos de explicación científica asumen la necesidad de utilizar algún tipo de conocimiento estable para el armado de un buen argumento explicativo. Si bien estos enfoques son muy útiles en las ciencias naturales, es dudoso que sean similarmente aplicables en el reino de lo socioeconómico. En el presente trabajo se prevé mostrar que la lógica de los “árboles de posibilidades” o “resultados de final abierto” propias de los procesos socioeconómicos hace que las regularidades sean más la excepción que la regla. Como alternativa, se propone un modo de explicación que focalice en los factores contextuales y en las acciones de las personas en el momento en que aconteció el fenómeno a explicar. (shrink)

An important strategy in the discovery of biological mechanisms involves the piecing together of experimental results from interventions. However, if mechanisms are investigated by means of ideal interventions, as defined by James Woodward and others, then the kind of information revealed is insufficient to discriminate between modular and non-modular causal contributions. Ideal interventions suffice for constructing webs of causal dependencies that can be used to make some predictions about experimental outcomes, but tell us little about how causally relevant factors are (...) organized together and how they interact with each other in order to produce a phenomenon. I argue that lab research relies on more elaborated types of interventions targeting in a controlled fashion multiple variables at the same time in order to probe the temporal organization of causally-relevant factors along distinct causal pathways and to test for non-modular interaction effects, thus providing crucial spatial-temporal constraints guiding the formulation of more detailed mechanistic explanations. (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)

Wesley Salmon’s version of the ontic conception of explanation is a main historical root of contemporary work on mechanistic explanation. This paper examines and critiques the philosophical merits of Salmon’s version, and argues that his conception’s most fundamental construct is either fundamentally obscure, or else reduces to a non-ontic conception of explanation. Either way, the ontic conception is a misconception.

In this thesis I investigate causal inquiry in the social sciences, drawing on examples from various disciplines and in particular from conflict studies. In a backlash against the pervasiveness of statistical methods, in the last decade certain social scientists have focused on finding the causal mechanisms behind observed correlations. To provide evidence for such mechanisms, researchers increasingly rely on ‘process tracing’, a method which attempts to give evidence for causal relations by specifying the chain of events connecting a putative cause (...) and effect of interest. I will ask whether the causal claims process tracers make are defensible, and where they are not defensible I will ask how we can improve the method. Throughout these investigations, I show that the conclusions of process tracing are constrained both by the causal structure ofthe social world and by social scientists’ aims and values. My central argument is this: all instances of social phenomena have causally relevant differences, which implies that any research design that requires some comparison between cases is limited by how we systematize these phenomena. Moreover, such research cannot rely on stable regularities. Nevertheless, to forego causal conclusions altogether is not the right response to these limitations; by carefully outlining our epistemic assumptions we can make progress in causal inquiry. While I use philosophical theories of causation to comment on the feasibility of a social scientific method, I also do the reverse: by investigating a popular contemporary method in the social sciences, I show to what extent our philosophical theories of causation are workable in practice. Thus, this thesis is both a methodological and a philosophical work. Every chapter discusses both a fundamental philosophical position on the social sciences and a relevant case study from the social sciences. (shrink)

Despite the fact that the notion of internal representation has - at least according to some - a fundamental role to play in the sciences of the mind, not only has its explanatory utility been under attack for a while now, but it also remains unclear what criteria should an explanation of a given cognitive phenomenon meet to count as a representational explanation in the first place. The aim of this article is to propose a solution to this latter problem. (...) I will assume that representational explanations should be construed as a form of mechanistic explanations and proceed by proposing a general sketch of a functional architecture of a representational cognitive mechanism. According to the view on offer here, representational mechanisms are mechanisms that meet four conditions: the structural resemblance condition, the action-guidance condition, the decouplability condition, and the error-detection condition. (shrink)

Glennan appeals to interventions to solve the ontological and explanatory regresses that threaten his mechanistic account of causality . I argue that Glennan’s manoeuvre fails. The appeal to interventions is not able to address the ontological regress, and it blocks the explanatory regress only at the cost of making the account inapplicable to non-modular mechanisms. I offer a solution to the explanatory regress that makes use of dynamic Bayesian networks. My argument is illustrated by a case study from systems biology, (...) namely, the mechanism for the irreversibility of apoptosis. I conclude by pointing out the implications of my argument for Glennan’s mechanistic account of causality and, more generally, for accounts of mechanistic explanation based on interventions. 1 Introduction2 Glennan’s Account of Causality3 Objections to Glennan’s Account4 Glennan’s Replies5 Ontological Symmetry?6 Explanatory Symmetry?7 A Solution to the Explanatory Regress8 The Prospects of Glennan’s Account. (shrink)

The paper starts by distinguishing between two kinds of economic practice: theoretical economic practice (TEP) (model and theory building) and direct economic practice (DEP) (the practical operation upon real economies). Most of the epistemological and philosophical considerations have been directed to the first type of practice, one of whose main goals is the discovery of particular sorts of economic laws, mechanisms and other regularities which throw light on relevant economic patterns. We do not deny that in some restricted domains these (...) kinds of regularities may be found. Rather, we claim that the realm of economics is best understood as consisting of processes whose regular structure (if they have one at all) is not guaranteed beforehand but may be crucially influenced and successfully enforced by what we call DEP. We claim that (a) some economic processes are a particular type of social process that will be referred to as Expectations-Based Processes (EBP). Characteristically, an EBP shows a connection between the information that individuals receive from the relevant economic context, the expectations they form, and the actions they perform; (b) in those cases in which EBP exhibit a regular behaviour, they depend on agents' expectations and, crucially, we argue, on interventions upon them. Authorities as well as other economic actors may intervene to change agents' expectations (and therefore, their decisions), contributing to shape EBP and helping to produce the patterns that lead to some targeted economic phenomena. These features of EBP show that they are not shielded from external influences and they do not run autonomously once triggered. Therefore they cannot be conceived as mechanisms or as economic machines. Rather they are open-ended processes that require continuous prodding on the part of policy makers to keep them running in the intended way. (shrink)

This paper argues against the view that the standard explanation of phase transitions in statistical mechanics may be considered a causal explanation, a distortion that can nevertheless successfully represent causal relations.