Publication Type |
Journal Article |
School or College |
College of Social & Behavioral Science |
Department |
Psychology |
Creator |
Malloy, Thomas E. |
Other Author |
St. Clair, Carmen Bostic; Grinder, John |
Title |
Steps to an ecology of emergence |
Date |
2005 |
Description |
To begin to take steps to a mental ecology of emergence we first establish two fundamental assumptions from the methodology of transformational grammar-the centrality of human judgment based on direct experience and the proposition that the systematic nature of human behavior is algorithmically driven. We then set a double criterion for understanding any formalism such as emergence: What is formalism X, that a human may know it; and a human, that a human may know formalism X? In the cybernetic sense, the two are defined in relation to each other. In answer to the first question, we examine emergence as a formalism, using Turing's work as a defining case and an NK Boolean system as a specific working model. In answer to the second question, we frame the knowing of emergence in a Batesonian epistemological approach informed by modern developments in discrete dynamic systems. This epistemology specifies mental process as the transformation of differences across a richly connected network. The relational reference point which integrates the two sides of the cybernetic question is human judgment of perceptual similarity which links emergent hierarchies in a formal NK Boolean model to hierarchies of perceptual similarity based on direct experience. |
Type |
Text |
Publisher |
Imprint Academic |
Volume |
12 |
Issue |
02-Jan |
First Page |
102 |
Last Page |
119 |
Subject |
Emergence; Perceptual Categories; Dynamic Constancy; Hierarchies; Boolean Models; Epistemology; Knowledge; Bateson; Kauffman |
Subject LCSH |
Knowledge, Theory of |
Language |
eng |
Bibliographic Citation |
Malloy, T. E., St. Clair, C. B., & Grinder, J. (2005). Steps to an ecology of emergence. Cybernetics & Human Knowing, 12(1-2), 102-19. |
Rights Management |
(c) Imprint Academic |
Format Medium |
application/pdf |
Format Extent |
1,484,196 bytes |
Identifier |
ir-main,2784 |
ARK |
ark:/87278/s6988rf1 |
Setname |
ir_uspace |
ID |
705152 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6988rf1 |