825 research outputs found
The Dynamics of Exchanges and References among Scientific Texts, and the Autopoiesis of Discursive Knowledge
Discursive knowledge emerges as codification in flows of communication. The
flows of communication are constrained and enabled by networks of
communications as their historical manifestations at each moment of time. New
publications modify the existing networks by changing the distributions of
attributes and relations in document sets, while the networks are
self-referentially updated along trajectories. Codification operates
reflexively: the network structures are reconstructed from the perspective of
hindsight. Codification along different axes differentiates discursive
knowledge into specialties. These intellectual control structures are
constructed bottom-up, but feed top-down back upon the production of new
knowledge. However, the forward dynamics of diffusion in the development of the
communication networks along trajectories differs from the feedback mechanisms
of control. Analysis of the development of scientific communication in terms of
evolving scientific literatures provides us with a model which makes these
evolutionary processes amenable to measurement
"Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning
The development of discursive knowledge presumes the communication of meaning
as analytically different from the communication of information. Knowledge can
then be considered as a meaning which makes a difference. Whereas the
communication of information is studied in the information sciences and
scientometrics, the communication of meaning has been central to Luhmann's
attempts to make the theory of autopoiesis relevant for sociology. Analytical
techniques such as semantic maps and the simulation of anticipatory systems
enable us to operationalize the distinctions which Luhmann proposed as relevant
to the elaboration of Husserl's "horizons of meaning" in empirical research:
interactions among communications, the organization of meaning in
instantiations, and the self-organization of interhuman communication in terms
of symbolically generalized media such as truth, love, and power. Horizons of
meaning, however, remain uncertain orders of expectations, and one should
caution against reification from the meta-biological perspective of systems
theory
The Communication of Meaning and the Structuration of Expectations: Giddens' "structuration theory" and Luhmann's "self-organization"
The communication of meaning as different from (Shannon-type) information is
central to Luhmann's social systems theory and Giddens' structuration theory of
action. These theories share an emphasis on reflexivity, but focus on meaning
along a divide between inter-human communication and intentful action as two
different systems of reference. Recombining these two theories into a theory
about the structuration of expectations, interactions, organization, and
self-organization of intentional communications can be simulated based on
algorithms from the computation of anticipatory systems. The self-organizing
and organizing layers remain rooted in the double contingency of the human
encounter which provides the variation. Organization and self-organization of
communication are reflexive upon and therefore reconstructive of each other.
Using mutual information in three dimensions, the imprint of meaning processing
in the modeling system on the historical organization of uncertainty in the
modeled system can be measured. This is shown empirically in the case of
intellectual organization as "structurating" structure in the textual domain of
scientific articles
The Evolutionary Dynamics of Discursive Knowledge
This open access book addresses three themes which have been central to Leydesdorff's research: (1) the dynamics of science, technology, and innovation; (2) the scientometric operationalization of these concept; and (3) the elaboration in terms of a Triple Helix of university-industry-government relations. In this study, I discuss the relations among these themes. Using Luhmann's social-systems theory for modelling meaning processing and Shannon's theory for information processing, I show that synergy can add new options to an innovation system as redundancy. The capacity to develop new options is more important for innovation than past performance. Entertaining a model of possible future states makes a knowledge-based system increasingly anticipatory. The trade-off between the incursion of future states on the historical developments can be measured using the Triple-Helix synergy indicator. This is shown, for example, for the Italian national and regional systems of innovation
Can Intellectual Processes in the Sciences Also Be Simulated? The Anticipation and Visualization of Possible Future States
Socio-cognitive action reproduces and changes both social and cognitive
structures. The analytical distinction between these dimensions of structure
provides us with richer models of scientific development. In this study, I
assume that (i) social structures organize expectations into belief structures
that can be attributed to individuals and communities; (ii) expectations are
specified in scholarly literature; and (iii) intellectually the sciences
(disciplines, specialties) tend to self-organize as systems of rationalized
expectations. Whereas social organizations remain localized, academic writings
can circulate, and expectations can be stabilized and globalized using
symbolically generalized codes of communication. The intellectual
restructuring, however, remains latent as a second-order dynamics that can be
accessed by participants only reflexively. Yet, the emerging "horizons of
meaning" provide feedback to the historically developing organizations by
constraining the possible future states as boundary conditions. I propose to
model these possible future states using incursive and hyper-incursive
equations from the computation of anticipatory systems. Simulations of these
equations enable us to visualize the couplings among the historical--i.e.,
recursive--progression of social structures along trajectories, the
evolutionary--i.e., hyper-incursive--development of systems of expectations at
the regime level, and the incursive instantiations of expectations in actions,
organizations, and texts.Comment: accepted for publication in Scientometrics (June 2015
Emerging Search Regimes: Measuring Co-evolutions among Research, Science, and Society
Scientometric data is used to investigate empirically the emergence of search
regimes in Biotechnology, Genomics, and Nanotechnology. Complex regimes can
emerge when three independent sources of variance interact. In our model,
researchers can be considered as the nodes that carry the science system.
Research is geographically situated with site-specific skills, tacit knowledge
and infrastructures. Second, the emergent science level refers to the formal
communication of codified knowledge published in journals. Third, the
socio-economic dynamics indicate the ways in which knowledge production relates
to society. Although Biotechnology, Genomics, and Nanotechnology can all be
characterised by rapid growth and divergent dynamics, the regimes differ in
terms of self-organization among these three sources of variance. The scope of
opportunities for researchers to contribute within the constraints of the
existing body of knowledge are different in each field. Furthermore, the
relevance of the context of application contributes to the knowledge dynamics
to various degrees
Editorial Preface to the OJAKM Special Issue on Knowledge Management: Research, Organization and Applied Innovation
This Special Issue of the Online Journal of Applied Knowledge Management (OJAKM), titled on "Knowledge Management: Research, Organization and Applied Innovation" attempts to give an account of some of the most insightful studies about organizational knowledge and learning, as well as some innovative and useful applications presented at the Knowledge Management (KM) Conference 2018. The KM Conference was held by the International Institute for Applied Knowledge Management (IIAKM) on the campus of the University of Pisa in June 2018, and was conceived as a dialectical context in which scholars from 15 nations and different continents exchanged ideas and perspectives on the more recent theoretical developments along with applications of the articulated, varied, and multifaceted themes of KM
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