Two controversies exist regarding the appropriate characterization of hierarchical and adaptive evolution in natural populations. In biology, there is the Wright-Fisher controversy over the relative roles of random genetic drift, natural selection, population structure, and interdemic selection in adaptive evolution begun by Sewall Wright and Ronald Aylmer Fisher. There is also the Units of Selection debate, spanning both the biological and the philosophical literature and including the impassioned group-selection debate. Why do these two discourses exist separately, and interact relatively little? (...) We postulate that the reason for this schism can be found in the differing focus of each controversy, a deep difference itself determined by distinct general styles of scientific research guiding each discourse. That is, the Wright-Fisher debate focuses on adaptive process, and tends to be instructed by the mathematical modeling style, while the focus of the Units of Selection controversy is adaptive product, and is typically guided by the function style. The differences between the two discourses can be usefully tracked by examining their interpretations of two contested strategies for theorizing hierarchical selection: horizontal and vertical averaging. (shrink)

The relationship between statistical mechanics and population genetics has a long history. Both take advantage of statistics to address the behavior of large groups of entities. The main objective of this article is to assess the obstacles population genetics is meeting in its claim to explain biological phenomena from the conceptual apparatus of statistical mechanics according to two recent articles. Several tools available to the latter are missing in the former. Thus, in the absence of an adequate justification of the (...) relevance of the analogy and without the satisfaction of certain basic assumptions, I argue that the explanatory strategy of the analogously based model is seriously compromised. La relation entre mécanique statistique et génétique des populations a une longue histoire. À l’instar de la première, la seconde tire profit des statistiques afin de traiter le comportement des grands ensembles d’entités. L’objectif principal du présent article est d’identifier les obstacles que rencontre la génétique des populations dans sa prétention d’explication des phénomènes biologiques à partir de l’appareillage conceptuel de la mécanique statistique selon deux articles récents. Or, plusieurs outils dont dispose cette dernière manque à la première. Ainsi, en l’absence d’une justification adéquate de la pertinence de l’analogie et sans la satisfaction de certaines hypothèses fondamentales, je soutiens que la stratégie explicative du modèle analogue est sérieusement compromise. (shrink)

A newly emerged field within economics, known as geographical economics claims to have provided a unified approach to the study of spatial agglomerations at different spatial scales by showing how these can be traced back to the same basic economic mechanisms. We analyze this contemporary episode of explanatory unification in relation to major philosophical accounts of unification. In particular, we examine the role of argument patterns in unifying derivations, the role of ontological convictions and mathematical structures in shaping unification, the (...) distinction between derivational and ontological unification, the issue of how explanation and unification relate and finally the idea that unification comes in degrees. (shrink)

This paper argues for two related theses. The first is that mathematical abstraction can play an important role in shaping the way we think about and hence understand certain phenomena, an enterprise that extends well beyond simply representing those phenomena for the purpose of calculating/predicting their behaviour. The second is that much of our contemporary understanding and interpretation of natural selection has resulted from the way it has been described in the context of statistics and mathematics. I argue for these (...) claims by tracing attempts to understand the basis of natural selection from its early formulation as a statistical theory to its later development by R.A. Fisher, one of the founders of modern population genetics. Not only did these developments put natural selection of a firm theoretical foundation but its mathematization changed the way it was understood as a biological process. Instead of simply clarifying its status, mathematical techniques were responsible for redefining or reconceptualising selection. As a corollary I show how a highly idealised mathematical law that seemingly fails to describe any concrete system can nevertheless contain a great deal of accurate information that can enhance our understanding far beyond simply predictive capabilities. (shrink)