This book offers a philosophy for error-prone humans trying to understand messy systems in the real world.

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)

Willard van Orman Quine once said that he had a preference for a desert ontology. This was in an earlier day when concerns with logical structure and ontological simplicity reigned supreme. Ontological genocide was practiced upon whole classes of upper-level or ‘derivative’ entities in the name of elegance, and we were secure in the belief that one strayed irremediably into the realm of conceptual confusion and possible error the further one got from ontic fundamentalism. In those days, one paid more (...) attention to generic worries about possible errors than to actual errors derived from distancing oneself too far from the nitty-gritty details of actual theory, actual inferences from actual data, the actual conditions under which we posited and detected entities, calibrated and ‘burned in’ instruments, identified and rejected artifacts, debugged programs and procedures, explained the mechanisms behind regularities, judged correlations to be spurious, and in general, to the real complexities and richness of actual scientific practice. (shrink)

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)

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)

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)

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)

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 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 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)

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.

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).

Contributors: Sabina Leonelli Nancy J. Nersessian Michel Janssen Jacob G. Foster James A. Evans Mark A. Bedau Marshall Abrams Gilbert B. Tostevin Salikoko S. Mufwene Massimo Maiocchi Joseph D. Martin Paul E. Smaldino Claes Andersson Anton Törnberg Petter Törnberg Beyond the Meme assembles interdisciplinary perspectives on cultural evolution, providing a nuanced understanding of it as a process in which dynamic structures interact on different scales of size and time. The volume demonstrates how a thick understanding of change in culture emerges (...) from multiple disciplinary vantage points, each of which is required to understand cultural evolution in all its complexity. (shrink)

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 role of pictures and visual modes of presentation of data in science is a topic of increasing interest to workers in artificial intelligence, the psychology of problem solving, and increasing numbers of scientists in all fields who must deal with problems of how to represent large quantities of complex multidimensional data in an intelligible fashion. The use of pictures is marvelously illustrated by but not limited to the biological sciences, so I will use examples from elsewhere as appropriate. With (...) the development of our visual technology—television, videotape, and the computer, the uses (and misuses) of visualization has properly become a matter not only of theoretical but also of practical concern. I will start with a practical story because it has multiple morals, both practical and theoretical—most of which lead elsewhere than I wish to go here. (shrink)

This chapter contains sections titled: Introduction Some Commonalities Can a Memetic Approach to Cultural Change Work? Memetics and Genetics Memetics and Epidemiology The Myth of Self‐replication An Alternative Approach Differential Dependency and Generative Entrenchment as Bases for a Theory of Evolutionary Change Elements of a Developmental Theory of Cultural Evolution New Predictions of This Theory Conclusion Postscript: Counterpoint Notes References.

A square tabular array was introduced by R. C. Punnett in (1907) to visualize systematically and economically the combination of gametes to make genotypes according to Mendel’s theory. This mode of representation evolved and rapidly became standardized as the canonical way of representing like problems in genetics. Its advantages over other contemporary methods are discussed, as are ways in which it evolved to increase its power and efficiency, and responded to changing theoretical perspectives. It provided a natural visual decomposition of (...) a complex problem into a number of inter-related stages. This explains its computational and conceptual power, for one could simply “read off” answers to a wide variety of questions simply from the “right” visual representation of the problem, and represent multiple problems, and multiple layers of problems in the same diagram. I relate it to prior work on the evolution of Weismann diagrams by Griesemer and Wimsatt (What Philosophy of Biology Is, Martinus-Nijhoff, the Hague, 1989), and discuss a crucial change in how it was interpreted that midwifed its success. (shrink)

I see in the nature of our minds and the character of our problem-solving methodologies a search for simplifying tools that will let us model a complex world and get away with it far more often than we might suppose. As it turns out, this broad a reach to mind and world is possible because both turn on common properties of evolved complex adaptive systems. These are in effect “design principles” for the architecture of nature—all of it, from biological systems (...) to ourselves and the technologies that we engineer.I explore how generative systems may, under some circumstances lead to adaptive radiations, and how the growth of complexity is entailed by their compositional embedding of prior systems, their stabilizing their features as architecture thru a process that I call generative entrenchment. I also explore how modularity has two forms: top-down modularity or “quasi-independence” in which evolving systems require the possibility of changing parts of the system without scrambling the organization of the rest, and bottom-up modularity in which a stable alphabet of standardized parts can be combined in various ways to generate an adaptive radiation of diverse systems to accomplish different things. (shrink)

Reductionism concerns a set of ontological and epistemological claims, and methodological strictures based on them, about the relationship between two different scientific domains. The critical assumption is that one of these domains is privileged over the other in the sense that the concepts, rules, laws, and other elements of the privileged domain can be used to specify, constitute, or account for those of the other “reduced” domain. This specification often consists of explanation, such that the “reducing” domain is epistemically privileged (...) over the reduced one. Explanations of this type are “reductionist” (or, are “reductions”) and reductionism is then the thesis that such explanations will always be forthcoming or at least are possible in principle. Reductionism is most plausible if the entities of the reduced domain can be interpreted as arising from (e.g., as aggregates of) entities of the reduced domain. This ontological claim is controversial but motivates many reductionist theses and associated scientific research programs. Thus, epistemological and ontological claims about reductionism have the methodological implication that they should govern and guide scientific research. When such research proves to be fruitless over a period of time, the associated reductionist claims themselves become suspect. Although issues connected with reductionism arise in the physical and social sciences, most attention to reductionism in philosophy of science over the last few decades has focused on the biological sciences, especially after the advent of molecular biology made it plausible to believe that biological phenomena can be uniformly explained (in detail) from their physical basis. However, the program of finding such explanations has a long philosophical history often couched in terms of seeking “mechanical,” “mechanistic,” or “materialistic” explanations. The contrast here is with traditional vitalism and various forms of teleology and holism. (shrink)

Philosophy and Phenomenological Research , L, Supplement, 177-94, Fall 1990. Reprinted in M. Losonsky, ed., Language and Mind: Contemporary Readings in Philosopohy and Cognitive Science, Blackwells, 1995.