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VII. Our Earthuman Ascent: A Major Evolutionary Transition in Individuality

1. A Cultural (Geonome) Code : Systems Linguistics

Markos,, Anton, et al. Living as Languaging: Distributed Knowledge in Living Beings. Stephen Cowley, ed. Cognition Beyond the Brain. Dordrecht: Springer, 2013. Reviewed more in Rosetta Cosmos, Charles University, Prague, scholars continue their interpretation that nature, evolution, and human are best known as a natural literacy project.

Markosova, Maria. Network Model of Human Language. Physica A. 387/661, 2008. A study from the Dept. of Applied Informatics, Comenius University, Bratislava, Slovakia, concurs with other recent work (Google article abstract, search Steyvers here) that similar to all natural phenomena, linguistic discourse likewise takes on the form of self-organized, scale-invariant dynamic networks. By extrapolation, one might consider that our encompassing cosmic and earthly nature could be appreciated as textual (scriptural) in kind.

Martin, Andrea and Giosue Baggio. Modelling Meaning Composition from Formalism to Mechanism. Philosophical Transactions of the Royal Society B. 375/20190298, 2019. MPI Psycholinguistics and Norwegian University of Science and Technology scholars introduce a special issue with this title in search of a more thoroughly parsed explanation. Among the authoritative contributors are Peter Hagoort, Laura Gwilliams, Marco Baroni, Liina Pylkkanen, Alona Fyshe and Petra Hendricks.

Human thought and language have expressive power because meaningful parts can be assembled into more complex semantic structures. This quality underlies our ability to compose meanings into novel configurations, and sets us apart from other species and current computing devices. Furthermore, composing parts into complex structures does not threaten the existence of constituent parts as independent units: parts and wholes exist simultaneously yet independently from one another. This independence is evident in human behaviour, but it seems at odds with the brain's sensitivity to statistical patterns. Everyday language is productive and expressively accurate because it goes beyond statistical regularities. Philosophy and linguistics explain this by realizing that language and thought are “compositional” in kind. (Abstract excerpt)

Massip-Bonet, Angels and Albert Bastardas-Boada, eds. Complexity Perspectives on Language, Communication and Society. Berlin: Springer, 2012. Reviewed more in Rosetta Cosmos as a robust association of universal self-organizing network dynamics with our grammar and conversation.

Moore, David. The Dependent Gene. New York: Freeman, 2001. To counter an older emphasis on particulate DNA determinism, Moore explains how genetic expression depends as much on interactive developmental systems.

To produce such an understanding, we need to adopt a more complex and genuine interactionism - a developmental systems perspective - born of the detailed study of how traits emerge from gene-environment interactions. (10)

Mufwene, Salikoko. The Ecology of Language Evolution. Cambridge: Cambridge University Press, 2001. The University of Chicago linguist contends that languages are somewhat akin to bacterial or parasitic species which compete and evolve by both Darwinian and Lamarckian means. Their macroecology is also influenced by nonlinear dynamics.

This section presupposes that languages are complex adaptive systems….They consist of numerous components of many different kinds which interface with each other - some linguists will argue that such systems are modular…..The components interact nonlinearly and on different temporal and spatial scales….They organize themselves to produce complex structures and behaviors. (157)

Mullins, Daniel, et al. The Role of Writing and Recordkeeping in the Cultural Evolution of Human Cooperation. Journal of Economic Behavior & Organization. Online March, 2013. With Harvey Whitehouse and Quentin Atkinson, Oxford University, Institute of Cognitive and Evolutionary Anthropology, researchers argue that a ramifying human literacy was a crucial, underrated factor in historical achievements of workable group identities and reciprocal empathies. See also Atkinson above for further evidence.

Efforts to account for the emergence of large-scale cooperative human societies have focused on a range of cultural advances, from the advent of agriculture to the emergence of new forms of political regulation and social identification. Little attention has been accorded to the role of writing and recordkeeping in cultural evolution. Recent insights garnered here from behavioural economics, paleography, grammatology, evolutionary psychology, and anthropology suggest that writing and recordkeeping helps to solve the problem of cooperation in large groups by transcending the severe limitations of our evolved psychology through the elaboration of four cooperative tools – (1) reciprocal behaviours, (2) reputation formation and maintenance, (3) social norms and norm enforcement, and (4) group identity and empathy. (Abstract)

Namhee, Lee, et al, eds. The Interactional Instinct: The Evolution and Acquisition of Language. Oxford: Oxford University Press, 2009. From the UCLA Neurobiology of Language Research Group, led by co-author John Schumann, a good example of the apt use of complexity principles to explain, as not possible earlier, how we hominids learned to speak and write in increasingly effective ways. In such regard, linguistic form becomes a nonlinear CAS as it generates multistrata interactive flow. (See also Larsen-Freeman and Cameron) A wider import may then accrue. By such insights, language is found to display the same recurrent dynamics that serve to self-organize genomes. By further extension, since language and its content may be considered as genetic in kind, their commonality could imply an independent source with the guise of a cosmic genetic code.

From our perspective, linguistic structure emerges as a complex adaptive system from the verbal interaction of hominids attempting to communicate with one another. Individuals organize lexical items into structures, and if the structures are efficiently producible, comprehensible, and learnable, then their use will spread throughout the community and become part of the “grammar” of the language. (4)

Newman, Stuart and Ramray Bhat. Dynamical Patterning Modules: A "Pattern Language" for Development and Evolution of Multicellular Form. International Journal of Developmental Biology. 53/5-6, 2009. From an issue on “Pattern Formation Today,” the New York Medical College biologists envision an innate textual guidance for life’s phenotypic radiation from microbe to mammal. See also in this issue articles by Robert Hazen, Ken Weiss and Anne Buchanan, and others.

Comparative anatomists have long recognized that animal bodies share a common morphological phrase book. More recently, molecular evolutionists have discovered that the metazoan share a common developmental-genetic vocabulary. Both of these findings, as we have shown, stem from the existence of a pattern language for animal development. The grammar of this language emerged abruptly more than 500 million years ago when a group of proteins and pathways of the unicellular world, by coming to operate on the mesoscale, mobilized the physical laws pertaining to soft-matter and excitable media in the construction of multicellular organisms. (702)

Ninio, Anat. Language and the Learning Curve. Oxford: Oxford University Press, 2006. In so many diverse fields, the application of complex systems science brings a novel, heretofore elusive, theoretical illumination. Compare with Eric Beinhocker’s new book on economics. And each subject area draws upon the same self-organizing, scale invariant network dynamics, which are lately found to manifestly recur everywhere. By the integral perspective of a worldwide humankind, a life and people-friendly genesis universe is revealed.

Anat Ninio is a professor of psychology at the Hebrew University of Jerusalem. In this breakthrough book she tells how children develop articulate syntax and learn language by plugging into their parent’s linguistic networks in the same way as one logs onto the identical structure of the Internet. This insight is reached after duly noting existing models of valency, lexicality, grammar, and so on. Complexity theory can then chart a middle course between Chomskyesque nativism and constructive social interactionism.

We can test this theoretical model in quite a direct way, which, as far as I know, has not been attempted before in the complexity literature. This test translates the term self-organization to a clear process of continuing to build an existing network with the same power-law features as before. If we take a group of young children just starting to produce some type of linguistic structure and track the gradual development of the syntactic network that they construct as a group, we should find that they literally recreate the global statistical features of the adult network constructed of the same type of linguistic items that they are said to (virtually) link into. (129)

Apparently, syntactic knowledge grows in a fractal manner. In a true scale-free manner, the link structure of the language network is the same at every stage, regardless of the size of the system. Such a process of propagation well suits language, the archetypical complex system. (137) Developmental data shows that children act just like Google when it searches the Web: they pick popular items, but only if their content is relevant for them. The results support a view of children as free agents exercising Preferential Attachment when they develop their minds and acquire knowledge in a social environment. (141)

Niyogi, Partha. The Computational Nature of Language Learning and Evolution. Cambridge: MIT Press, 2006. A theme that runs through this technical work by a University of Chicago computer scientist is an evolving communication due to the emergent properties of complex adaptive systems.

Noll, Hans. The Digital Origin of Human Language. BioEssays. 25/5, 2003. Exchanges of information which involve both digital encoding and analog pattern recognition and a discrete alphabet fueled the emergence of the modern human. By these views based on an array of studies, an accord is noted between the genetic code, immune system, neural networks and linguistic patterns since evolving nature uses the same script over and over. It is then implied that a child recapitulates the way that language developed in hominids.

The rapid spread, universal adoption and exclusive survival of a digital phonetic language has its parallel in the emergence of an universal genetic code since the inception of life more than three billion years ago. (491) It is therefore not surprising that structure and evolution of language are a reflection of information processing at the molecular, cellular and multicellular level. (496)

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