The Structure and Dynamics eJournal welcomes articles, book reviews, data, simulations, research material, and special issues that examine aspects of human evolution, social structure and behavior, culture, cognition, or related topics. Our goal is to advance the historic mission of anthropology in the broadest sense to describe and explain the range of variation in human biology, society, culture and civilization across time and space. Submissions of databases, software tutorials, programs, and teaching materials are welcomed, as are communications on research materials of interest to a wide variety of science and social science researchers, including networks, dynamical models, and complexity research and related genre.
Volume 1, Issue 3, 2005
We institute here a policy of occasionally publishing noteworthy PhD dissertations that advance anthropology or related sciences. Such publications are to be copy edited by the dissertation author, nominated by the author's PhD committee, and must receive unqualified support in our review process of at least two assigned referees, as well as by the editors of Structure and Dynamics.
Agents producing and exchanging knowledge are forming as a whole a socio-semantic complex system. Studying such knowledge communities offers theoretical challenges, with the perspective of naturalizing further social sciences, as well as practical challenges, with potential applications enabling agents to know the dynamics of the system they are participating in. The present thesis lies within the framework of this research program. Alongside and more broadly, we address the question of reconstruction in social science. Reconstruction is a reverse problem consisting of two issues: (i) deduce a given high-level observation for a considered system from low-level phenomena; and (ii) reconstruct the evolution of high-level observations from the dynamics of lower-level objects.
In this respect, we argue that several significant aspects of the structure of a knowledge community are primarily produced by the co-evolution between agents and concepts, i.e. the evolution of an epistemic network. In particular, we address the first reconstruction issue by using Galois lattices to rebuild taxonomies of knowledge communities from low-level observation of relationships between agents and concepts; achieving ultimately an historical description (inter alia field progress, decline, specialization, interaction – merging or splitting). We then micro-found various stylized facts regarding this particular structure, by exhibiting processes at the level of agents accounting for the emergence of epistemic community structure. After assessing the empirical interaction and growth processes, and assuming that agents and concepts are co-evolving, we successfully propose a morphogenesis model rebuilding relevant high-level stylized facts. We finally defend a general epistemological point related to the methodology of complex system reconstruction, eventually supporting our choice of a co-evolutionary framework.