This paper studies the epistemic failures to reach understanding in relation to scientific explanations. We make a distinction between genuine understanding and its negative phenomena—lack of understanding and misunderstanding. We define explanatory understanding as inclusive as possible, as the epistemic success that depends on abilities, skills, and correct explanations. This success, we add, is often supplemented by specific positive phenomenology which plays a part in forming epistemic inclinations—tendencies to receive an insight from familiar types of explanations. We define lack of (...) understanding as the epistemic failure that results from a lack of an explanation or from an incorrect one. This can occur due to insufficient abilities and skills, or to fallacious explanatory information. Finally, we characterize misunderstanding by cases where one’s epistemic inclinations do not align with an otherwise correct explanation. We suggest that it leads to potential debates about the explanatory power of different explanatory strategies. We further illustrate this idea with a short meta-philosophical study on the current debates about distinctively mathematical explanations. (shrink)

There are several important criticisms against the unificationist model of scientific explanation: Unification is a broad and heterogeneous notion and it is hard to see how a model of explanation based exclusively on unification can make a distinction between genuine explanatory unification from cases of ordering or classification. Unification alone cannot solve the asymmetry and irrelevance problems. Unification and explanation pull in different directions and should be decoupled, because for good scientific explanation extra ad explanandum information is often required. I (...) am presenting a possible solution to those problems, by focusing on an often overlooked but important element of how theoretic unification is achieved—the conceptual frameworks of theories. The core conceptual assumptions behind theories are decisive for discriminating between explanatory and non-explanatory unification. The conceptual framework is also flexible enough to balance the tension between informativeness and maximum systematization in constructing explanatory inferences. A short case study of orthogenetic and Darwinian explanations in paleontology is presented as an illustration of how my addition to the unificationist model is applicable to a historical debate between rival explanations. (shrink)

Dans cet article, je présente une approche sémantique de l’analyse de la fonction de la métaphore du paysage dans la biologie de l’évolution. Le concept de paysage adaptatif a suscité une attention considérable dans la philosophie de la biologie récente. La plupart des auteurs ont considéré ce concept de l’une des deux manières suivantes: en tant qu’outil heuristique, comme partie intrinsèque de modèles mathématiques robustes, ou comme un ensemble définissable d’analogies sur lesquelles les modèles sont basés et testés. Chacune de (...) ces visions conduit à la conclusion que la valeur de la métaphore du paysage dépend seulement du succès des modèles que sous-tend la métaphore, en vue de représenter adéquatement la dynamique de l’évolution. J’essaie de montrer que cette conclusion, ainsi que les visions qui y conduisent, ne tiennent pas compte d’épisodes importants dans l’histoire de la métaphore du langage. Ces visions proviennent plutôt de thèses générales, en philosophie des sciences, quant au rôle des métaphores dans les théories scientifiques. L’analyse sémantique que je propose met en lumière le fait que la fonction première du concept de relief adaptatif, au cours de la synthèse évolutionniste, a été de servir de cadre général d’unification conceptuelle, qui a rendu possible la conciliation de phénomènes empiriques hétérogènes. De ce point de vue, la métaphore du paysage est un outil linguistique-théorique qui ne doit pas être abandonné (et qui ne l’est de fait pas) suite à la falsification des modèles construits et interprétés au moyen de la métaphore. (shrink)

The debate between the dynamical and the statistical interpretations of natural selection is centred on the question of whether all explanations that employ the concepts of natural selection and drift are reducible to causal explanations. The proponents of the statistical interpretation answer negatively, but insist on the fact that selection/drift arguments are explanatory. However, they remain unclear on where the explanatory power comes from. The proponents of the dynamical interpretation answer positively and try to reduce selection/drift arguments to some of (...) the most prominent accounts of causal explanation. In turn, they face the criticism raised by statisticalists that current accounts of causation have to be violated in some of their core conditions or otherwise used in a very loose manner in order to account for selection/drift explanations. We propose a reconciliation of both interpretations by conveying evolutionary explanations within the unificationist model of scientific explanation. Therefore, we argue that the explanatory power in natural selection arguments is a result of successful unification of individual- and population-level facts. A short case study based on research on sympatric speciation will be presented as an example of how population- and individual-level facts are unified to explain the morphological mosaic of bill shape in island scrub jays. (shrink)

My aim here is to show that approximate truth as a paraconsistent notion can be successfully incorporated into the analysis of scientific unification, thus advancing towards a more realistic representation of theory development that takes into account the controversies that often loom alongside the progress of research programmes. I support my analysis with a case study of the recent debate in ecology centred around the existence of the paradox of enrichment and the controversy between ecological models of predation that employ (...) prey-dependent and ratio-dependent functional responses. These models were initially proposed as equally good representations of the basic aspects of predator–prey dynamics. However, both models generated inconsistent observational consequences and, therefore, introduced a contradiction within predator–prey theory. I argue that by accepting these models as approximately true representations of predator–prey dynamics we can convey how the available observational data have been successfully systematized in a consistent way under them. This first step in resolving the controversy relied on building a series of contrastive arguments based on both models’ derivations about population dynamics and the available empirical data. The heightening of this contrast between the models, in turn, was also essential in defining a limiting function which can be used to integrate both models and reach a new unified expression of predator–prey dynamics. (shrink)

This paper discusses the polemical question of whether explanations that produce understanding must be true. It argues positively for the role of truth in reaching explanatory understanding, by presenting three lines of criticism of alternative accounts. The first is that by rejecting truth as a criterion for evaluating explanations, any non-factual account thereby effectively cuts ties with the central theories of explanations, which provide at least partial criteria for explanatory understanding. The second line of criticism is that some of the (...) most well-known non-factual accounts implicitly operate over a notion of partial-truth, and as such, they do not provide a valid alternative. The final critical argument is that, in the place of truth evaluations, these accounts often offer a multiplicity of other criteria, and by changing a unitary criterion such as truth for a collection of other requirements, these non-factive theories introduce a level of ad hoc-ness, which diminishes their normative value. (shrink)