Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of the system's parts if it depends upon their mode of organization--a view consistent with reduction. Emergence can be analyzed as a failure of aggregativity--a state in which "the whole is nothing more than the sum of its parts." Aggregativity requires four conditions, giving tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different (...) degrees, these conditions provide powerful evaluation criteria for choosing decompositions, and heuristics for detecting biases of vulgar reductionisms. This analysis of emergence is compatible with reduction. (shrink)
Methodological reductionists practice ‘wannabe reductionism’. They claim that one should pursue reductionism, but never propose how. I integrate two strains in prior work to do so. Three kinds of activities are pursued as “reductionist”. “Successional reduction” and inter-level mechanistic explanation are legitimate and powerful strategies. Eliminativism is generally ill-conceived. Specific problem-solving heuristics for constructing inter-level mechanistic explanations show why and when they can provide powerful and fruitful tools and insights, but sometimes lead to erroneous results. I show how traditional metaphysical (...) approaches fail to engage how science is done. The methods used do so, and support a pragmatic and non-eliminativist realism. (shrink)
Most philosophical accounts of emergence are incompatible with reduction. Most scientists regard a system property as emergent relative to properties of its parts if it depends upon their mode of organization-a view consistent with reduction. Emergence is a failure of aggregativity, in which ``the whole is nothing more than the sum of its parts''. Aggregativity requires four conditions, giving powerful tools for analyzing modes of organization. Differently met for different decompositions of the system, and in different degrees, the structural conditions (...) can provide evaluation criteria for choosing decompositions, ``natural kinds'', and detecting functional localization fallacies, approximations, and various biases of vulgar reductionisms. This analysis of emergence and use of these conditions as heuristics is consistent with a broader reductionistic methodology. (shrink)
Richard Levins’ distinction between aggregate, composed and evolved systems acquires new significance as we recognize the importance of mechanistic explanation. Criteria for aggregativity provide limiting cases for absence of organization, so through their failure, can provide rich detectors for organizational properties. I explore the use of failures of aggregativity for the analysis of mechanistic systems in diverse contexts. Aggregativity appears theoretically desireable, but we are easily fooled. It may be exaggerated through approximation, conditions of derivation, and extrapolating from some conditions (...) of decomposition illegtimately to others. Evolved systems particularly may require analyses under alternative complementary decompositions. Exploring these conditions helps us to better understand the strengths and limits of reductionistic methods. (shrink)
The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)
The generative entrenchment of an entity is a measure of how much of the generated structure or activity of a complex system depends upon the presence or activity of that entity. It is argued that entities with higher degrees of generative entrenchment are more conservative in evolutionary changes of such systems. A variety of models of complex structures incorporating the effects of generative entrenchment are presented and we demonstrate their relevance in analyzing and explaining a variety of developmental and evolutionary (...) phenomena, both on a macroscopic developmental and evolutionary scale, and using models and strategies pioneered by Kauffman, on the more microscopic scale appropriate to the analysis of the structure and behavior of gene control networks. The resulting picture suggests that generative entrenchment acts as a powerful and constructive developmental constraint on the course of evolutionary processes. Since virtually any system exhibits varying degrees of generative entrenchment among its parts and activities, these studies and results have in addition broad potential application for the analysis of generative structures in other areas. (shrink)
Scientific models may be more useful for false assumptions they make than true ones when one is interested not in the fit of the model, but in the form of the residuals. Modeling Darwin’s “blending” theory of inheritance shows how it illuminates features of Mendelian theory. Insufficient understanding of it leads to incorrect moves in modeling population structure. But it may prove even more useful for organizing a theory of cultural evolution. Analysis of “blending” inheritance gives new tools for recognizing (...) population structure for culture and for understanding differences between biological and cultural inheritance. (shrink)
The reductionistic vision of evolutionary theory, "the gene's eye view of evolution" is the dominant view among evolutionary biologists today. On this view, the gene is the only unit with sufficient stability to act as a unit of selection, with individuals and groups being more ephemeral units of function, but not of selection. This view is argued to be incorrect, on several grounds. The empirical and theoretical bases for the existence of higher-level units of selection are explored, and alternative analyses (...) discussed critically. The success of a multi-level selection theory demands the recognition and development of a multi-level genetics. The way to accomplish this is suggested. The genotype/phenotype distinction also requires further analysis to see how it applies at higher levels of organization. This analysis provides a way of defining genotype and phenotype for cultural evolution, and a treatment of the innate-acquired distinction which are both generalizeable to analyze problems of the nature and focus of scientific change. (shrink)
Scientific models may be more useful for false assumptions they make than true ones when one is interested not in the fit of the model, but in the form of the residuals. Modeling Darwin’s “blending” theory of inheritance shows how it illuminates features of Mendelian theory. Insufficient understanding of it leads to incorrect moves in modeling population structure. But it may prove even more useful for organizing a theory of cultural evolution. Analysis of “blending” inheritance gives new tools for recognizing (...) population structure for culture and for understanding differences between biological and cultural inheritance. (shrink)
Mesoudi et al.'s new synthesis for cultural evolution closely parallels the evolutionary synthesis of Neo-Darwinism. It too draws inspiration from population genetics, recruits other fields, and, unfortunately, also ignores development. Enculturation involves many serially acquired skills and dependencies that allow us to build a rich cumulative culture. The newer synthesis, evolutionary developmental biology, provides a key tool, generative entrenchment, to analyze them. (Published Online November 9 2006).
After an initial discussion of the character of interdisciplinary linkages between complex disciplines, I consider an area with confluences of many diverse disciplines—the study of cultural evolution. This must embrace not only the traditional biological sciences, but also the multiple often warring disciplines of the human sciences. This interdisciplinary articulation is in its early stages compared, e.g., to that of evolutionary biology or evolutionary developmental biology, and I try to lay out major axes along which its articulation should plausibly occur, (...) given the relevant causal processes acting at different levels. One cannot have an adequate account of cultural evolution without recognizing a central role for cognitive and social development and the social and cultural organizations and institutions and artifactual tools and infrastructure that support and structure these developmental processes. These induce a population structure that mediates the transmission, expression, and elaboration of culture, and in particular the different ways in which they scaffold learning and the development and articulation of complex skills. I consider how these elements should articulate the disciplines that tend to focus separately on them. Intentions and the market are not explicitly included in this account, and I consider ways in which these perspectives might enter. (shrink)
The role of pictures and visual modes of presentation of data in science is a topic of increasing interest to workers in artificial intelligence, problem solving, and scientists in all fields who must deal with large quantities of complex multidimensional data. Drawing on studies of animal motion, aerodynamics, morphological transformations, the history of linkage mapping, and the analysis of deterministic chaos, I focus on the strengths and limitations of our visual system, the analysis of problems particularly suited to visualization-the analysis (...) of similarities and differences between complex objects, and problems making conjoint use of information from several complex images. (shrink)
The simple systems methodology is a powerful reductionistic research strategy. It has problems as implemented in developmental genetics because the organisms studied are few and unrepresentative. Stronger inferences require independent arguments that key traits are widely distributed phylogenetically. Evolutionary and developmental mechanisms of generative entrenchment and self-organization provide possible support, and are also necessary components of a developmental systems approach.
Michael Weisberg has given us a lovely book on models. It has very broad coverage of issues intersecting the nature of models and their use, an extensive consideration of long ignored “concrete” models with a rich case study, a discussion and classification of the many diverse kinds of models, and a particularly groundbreaking and innovative discussion of similarity concerning how models relate to the world. Included are insightful discussions of increasingly used “agent based” models, and the conjoint use of multiple (...) models in looking for robust results. Weisberg fills in some discussions with modeling and simulation results of his own.In addition, he considers and critiques other recent competing views on models, including the increasingly popular “models as fictions” account. His discussion is clear and technically precise without being needlessly so, and his distinctions are useful. The scientist is more likely to recognize his objects than the semantic theorist, and that is how it .. (shrink)
The subject of this edited volume is the idea of levels of organization: roughly, the idea that the natural world is segregated into part-whole relationships of increasing spatiotemporal scale and complexity. The book comprises a collection of essays that raise the idea of levels into its own topic of analysis. Owing to the wide prominence of the idea of levels, the scope of the volume is aimed at theoreticians, philosophers, and practicing researchers of all stripes in the life sciences. The (...) volume’s contributions reflect this diversity, and draw from fields such as developmental biology, evolutionary biology, molecular biology, ecology, cell biology, and neuroscience. The book presents wide-ranging novel insights on causation and levels, the hierarchical structure of evolution, the role of levels in biological theory, and more. (shrink)
Gigerenzer et al.'s is an extremely important book. The ecological validity of the key heuristics is strengthened by their relation to ubiquitous Poisson processes. The recognition heuristic is also used in conspecific cueing processes in ecology. Three additional classes of problem-solving heuristics are proposed for further study: families based on near-decomposability analysis, exaptive construction of functional structures, and robustness.
