An Evolutionary Framework for Culture: Selectionism versus Communal Exchange

Dawkins' replicator-based conception of evolution has led to widespread mis-application selectionism across the social sciences because it does not address the paradox that inspired the theory of natural selection in the first place: how do organisms accumulate change when traits acquired over their lifetime are obliterated? This is addressed by von Neumann's concept of a self-replicating automaton (SRA). A SRA consists of a self-assembly code that is used in two distinct ways: (1) actively deciphered during development to construct a self-similar replicant, and (2) passively copied to the replicant to ensure that it can reproduce. Information that is acquired over a lifetime is not transmitted to offspring, whereas information that is inherited during copying is transmitted. In cultural evolution there is no mechanism for discarding acquired change. Acquired change can accumulate orders of magnitude faster than, and quickly overwhelm, inherited change due to differential replication of variants in response to selection. This prohibits a selectionist but not an evolutionary framework for culture. Recent work on the origin of life suggests that early life evolved through a non-Darwinian process referred to as communal exchange that does not involve a self-assembly code, and that natural selection emerged from this more haphazard, ancestral evolutionary process. It is proposed that communal exchange provides a more appropriate evolutionary framework for culture than selectionism. This is supported by a computational model of cultural evolution and a network-based program for documenting material cultural history, and it is consistent with high levels of human cooperation.Comment: 18 pages; 2 tables and 11 figures embedded in tex

Cultural Evolution as Distributed Computation

The speed and transformative power of human cultural evolution is evident from the change it has wrought on our planet. This chapter proposes a human computation program aimed at (1) distinguishing algorithmic from non-algorithmic components of cultural evolution, (2) computationally modeling the algorithmic components, and amassing human solutions to the non-algorithmic (generally, creative) components, and (3) combining them to develop human-machine hybrids with previously unforeseen computational power that can be used to solve real problems. Drawing on recent insights into the origins of evolutionary processes from biology and complexity theory, human minds are modeled as self-organizing, interacting, autopoietic networks that evolve through a Lamarckian (non-Darwinian) process of communal exchange. Existing computational models as well as directions for future research are discussed.Comment: 13 pages Gabora, L. (2013). Cultural evolution as distributed human computation. In P. Michelucci (Ed.) Handbook of Human Computation. Berlin: Springe

Book Review of \u27Evolutionary and Interpretive Archaeologies\u27 Edited by Ethan E. Cochrane and Andrew Gardner

Evolutionary and Interpretive Archaeologies, edited by Ethan E. Cochrane andAndrew Gardner, grew out of a seminar at the Institute for Archaeology atUniversity College London in 2007. It consists of 15 chapters by archaeologistswho self-identify themselves as practitioners who emphasize the benefits ofevolutionary or interpretive approaches to the study of the archaeologicalrecord. While the authors\u27 theoretical views are dichotomous, the editors\u27 aimfor the book as a whole is not to expound on the differences between these twokinds of archaeology but to bring forward a richer understanding of thediscipline and to highlight areas of mutual concern. Some chapters come acrossas a bit of a sales pitch, but the majority of the contributions emphasize howeach approach can be productively used to address the goals of the other. Thebook seeks to contribute to a mutually beneficial and more productivediscipline, and overall, it succeeds in this effort

An Evolutionary Perspective of Radical Innovation and its implications for Management and Organizations

The thesis develops an evolutionary perspective of technological change based on a complex analogy between biological and technological evolution. The theoretical framework is based on a rich tradition of interdisciplinary research, integrating Herbert Simon\u2019s seminal theory on modular complex systems, artifact-centered evolutionary models of innovation (e.g. Basalla\u2019s), and fundamental evolutionary processes recently researched in microbiology \u2013 including in particular exaptation and horizontal transfer. The novel evolutionary perspective is supported by analytical narratives of paradigmatic historical and prehistorical cases \u2013 including the bow-and-arrow and the turbojet revolution \u2013 emphasizing its explanatory power in understanding presumptive anomalies and the inception of radical innovation. Finally, some implications for innovation management (managing creative radical engineering), organizations (rethinking the mirror hypothesis) are explored as promising implications of this novel perspective of technological change.The thesis develops an evolutionary perspective of technological change based on a complex analogy between biological and technological evolution. The theoretical framework is based on a rich tradition of interdisciplinary research, integrating Herbert Simon\u2019s seminal theory on modular complex systems, artifact-centered evolutionary models of innovation (e.g. Basalla\u2019s), and fundamental evolutionary processes recently researched in microbiology \u2013 including in particular exaptation and horizontal transfer. The novel evolutionary perspective is supported by analytical narratives of paradigmatic historical and prehistorical cases \u2013 including the bow-and-arrow and the turbojet revolution \u2013 emphasizing its explanatory power in understanding presumptive anomalies and the inception of radical innovation. Finally, some implications for innovation management (managing creative radical engineering), organizations (rethinking the mirror hypothesis) are explored as promising implications of this novel perspective of technological change

‘The uses of ethnography in the science of cultural evolution’. Commentary on Mesoudi, A., Whiten, A. and K. Laland ‘Toward a unified science of cultural evolution’

There is considerable scope for developing a more explicit role for ethnography within the research program proposed in the article. Ethnographic studies of cultural micro-evolution would complement experimental approaches by providing insights into the “natural” settings in which cultural behaviours occur. Ethnography can also contribute to the study of cultural macro-evolution by shedding light on the conditions that generate and maintain cultural lineages

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

Macroevolution: Explanation, Interpretation and Evidence

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