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)

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)

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)

Mechanism is undoubtedly a causal concept, in the sense that ordinary definitions and philosophical analyses explicate the concept in terms of other causal concepts such as production and interaction. Given this fact, many philosophers have supposed that analyses of the concept of mechanism, while they might appeal to philosophical theories about the nature of causation, could do little to inform such theories. On the other hand, methods of causal inference and explanation appeal to mechanisms. Discovering a mechanism is the gold (...) standard for establishing and explaining causal connections. This fact suggests that it might be possible to provide an analysis of causation that appeals to mechanisms. (shrink)

Mechanisms are often characterized as causal structures and the interventionist account of causation is then used to characterize what it is to be a causal structure. The associated modularity constraint on causal structures has evoked criticism against using the theory as an account of mechanisms, since many mechanisms seem to violate modularity. This paper answers to this criticism by making a distinction between a causal system and a causal structure. It makes sense to ask what the modularity properties of a (...) given causal structure are, but not whether a causal system is modular tout court. The counter-examples to the interventionist account are systems in which a particular structure is modular in variables, but not in parameters. A failure of parameter-modularity does not by itself threaten the interventionist interpretation of the structure and the possibility of causally explaining with that structure, but it does mean that knowledge of the structure is not sufficient to constitutively explain system-level properties of the embedding system. (shrink)

Gebharter has proposed using one of the best known Bayesian network causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this article is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in (...) the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions. (shrink)

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)

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)

The aim of this paper is to examine the notion of social mechanisms by comparison with the notions of evolutionary and physical mechanisms. It is argued that social mechanisms are based on trends, and not lawlike regularities, so that social mechanisms are different from mechanisms in the natural sciences. Taking as an example of social causation the abolition of the slave trade, the paper argues that social mechanisms should be incorporated in Weber’s wider notion of adequate causation in order to (...) achieve their explanatory purpose. (shrink)

Fodor argue that Darwinism cannot be true on the grounds that there are no laws of selection to support counterfactuals about why traits are selected-for. Darwinian explanations, according to this objection, amount to mere ‘plausible historical narratives’. I argue that the objection is predicated on two problematic assumptions: A nomic-subsumption account of causation and causal explanation, and a fine-grained view of the individuation of selected-for effects. Against the former, I argue that Darwinian explanations are a historical species of mechanistic explanation (...) and that mechanisms are causally productive and counterfactual supporting in the absence of appropriate laws. Once this mechanistic framework is in place, the demand for laws of selection vanishes and the historical cum causal coherence of Darwinism is restored. As for the second assumption, I argue that it is an artefact of the teleosemantic program with no basis in evolutionary biology and that properly understood, Darwinian evolutionary biology shows just why teleosemantics cannot succeed. (shrink)

Cybernetics promoted machine-supported investigations of adaptive sensorimotor behaviours observed in biological systems. This methodological approach receives renewed attention in contemporary robotics, cognitive ethology, and the cognitive neurosciences. Its distinctive features concern machine experiments, and their role in testing behavioural models and explanations flowing from them. Cybernetic explanations of behavioural events, regularities, and capacities rely on multiply realizable mechanism schemata, and strike a sensible balance between causal and unifying constraints. The multiple realizability of cybernetic mechanism schemata paves the way to principled (...) comparisons between biological systems and machines. Various methodological issues involved in the transition from mechanism schemata to their machine instantiations are addressed here, by reference to a simple sensorimotor coordination task. These concern the proper treatment of ceteris paribus clauses in experimental settings, the significance of running experiments with correct but incomplete machine instantiations of mechanism schemata, and the advantage of operating with real machines ??? as opposed to simulated ones ??? immersed in real environments. (shrink)

This paper discusses the explanatory power of discourse analysis, an approach to typically considered one of the main qualitative methods for data analysis. Although discourse analysis is typically not used to develop explanatory models, some have claimed that discourse models can causally explain social phenomena, such as institutional change. I analyze a case of institutional change to discuss and provide arguments for two claims. First, discourse analysis cannot generate causal explanations of social phenomena. Secondly, discourse analysis can generate non-causal explanations, (...) specifically constitutive explanations of social phenomena. I conclude the paper by discussing possible implications for social research. (shrink)

In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the (...) actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Craver's continuum of ?how-possibly,? to ?how-plausibly,? to ?how-actually? models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanism's activities, not its entities. This point is illustrated with two examples of functional models. (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)

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)