Configurational Information as Potentially Negative Entropy: The Triple Helix Model

Configurational information is generated when three or more sources of variance interact. The variations not only disturb each other relationally, but by selecting upon each other, they are also positioned in a configuration. A configuration can be stabilized and/or globalized. Different stabilizations can be considered as second-order variation, and globalization as a second-order selection. The positive manifestations and the negative selections operate upon one another by adding and reducing uncertainty, respectively. Reduction of uncertainty in a configuration can be measured in bits of information. The variables can also be considered as dimensions of the probabilistic entropy in the system(s) under study. The configurational information then provides us with a measure of synergy within a complex system. For example, the knowledge base of an economy can be considered as such a synergy in the otherwise virtual (that is, fourth) dimension of a regime

Sociological and Communication-Theoretical Perspectives on the Commercialization of the Sciences

Both self-organization and organization are important for the further development of the sciences: the two dynamics condition and enable each other. Commercial and public considerations can interact and "interpenetrate" in historical organization; different codes of communication are then "recombined." However, self-organization in the symbolically generalized codes of communication can be expected to operate at the global level. The Triple Helix model allows for both a neo-institutional appreciation in terms of historical networks of university-industry-government relations and a neo-evolutionary interpretation in terms of three functions: (i) novelty production, (i) wealth generation, and (iii) political control. Using this model, one can appreciate both subdynamics. The mutual information in three dimensions enables us to measure the trade-off between organization and self-organization as a possible synergy. The question of optimization between commercial and public interests in the different sciences can thus be made empirical.Comment: Science & Education (forthcoming

Measuring the Knowledge Base of Regional Innovation Systems in Germany in terms of a Triple Helix Dynamics

While a market economy seeks equilibrium, a knowledge-based economy may upset this tendency towards stabilization by adding the feedback of globalization. The interaction among the three subdynamics of economic exchange, technological innovation, and institutional control can be captured with a generalized Triple Helix model. We propose to use the mutual information as an indicator of integration among the three subdynamics at the systems level. This probabilistic entropy can be positive or negative. On the basis of data at the district level in Germany the conclusions of a previous study about the Netherlands are tested: medium-tech manufacturing is the main driver of a knowledge-based configuration in a regional economy, while knowledge-intensive services tend to uncouple the economy from the regional configuration. At the level of regions (NUTS-2) the knowledge-based economy is no longer structured by the previous East-West divide of the country, while this divide has remained the main structure at the level of the states (NUTS-1) which constitute the Federal Republic. -- Während eine Marktwirtschaft nach Gleichgewicht strebt, kann diese Stabilisierungs-tendenz in einer Wissensgesellschaft durch einen zusätzlichen Feedback-Effekt der Globalisierung gestört werden. Das Zusammenspiel der drei Teildynamiken ökonomi-scher Austausch, technologische Innovation und institutionelle Kontrolle kann mit ei-nem allgemeinen Triple Helix-Model erfasst werden. Wir nutzen die gegenseitigen Informationsflüsse zwischen diesen drei Teildynamiken als einen Indikator für die systemische Integration dieser drei Bereiche. Dies probabilistische Entropy kann positiv oder negativ sein. Wir untersuchen, ob Ergebnisse einer früheren, für die Niederlande durchgeführten Studie auch auf Deutschland zutreffen. Wie in den Niederlanden erweist sich auch in Deutschland die medium-tech Industrie als wesentliche Triebkraft der regionalen Wissensbasis während die wissensintensiven Dienstleistungen offenbar weitgehend losgelöst von regionalen Gegebenheiten sind. Während auf der Ebene von Bundesländern (NUTS-1 Regionen) noch ein klarer Ost-West-Unterschied festgestellt werden kann ist das Bild auf der feineren Ebene von NUTS-2 Regionen wesentlich differenzierter.Wissensgesellschaft,Triple Helix,Regionale Innovationssysteme,Deutschland,Probabilistische Entropy,Knowledge economy,Triple Helix,regional innovation systems,Germany,probabilistic entropy

Can Synergy in Triple-Helix Relations be Quantified? A Review of the Development of the Triple-Helix Indicator

Triple-Helix arrangements of bi- and trilateral relations can be considered as adaptive eco-systems. During the last decade, we have further developed a Triple-Helix indicator of synergy as reduction of uncertainty in niches that can be shaped among three or more distributions. Reduction of uncertainty can be generated in correlations among distributions of relations, but this (next-order) effect can be counterbalanced by uncertainty generated in the relations. We first explain the indicator, and then review possible results when this indicator is applied to (i) co-author networks of academic, industrial, and governmental authors and (ii) synergies in the distributions of firms over geographical addresses, technological classes, and industrial-size classes for a number of nations. Co-variation is then considered as a measure of relationship. The balance between globalizing and localizing dynamics can be quantified. Too much synergy locally can also be considered as lock-in. Tendencies are different for the globalizing knowledge dynamics versus locally retaining wealth from knowledge in industrial innovations

NASREN: Standard reference model for telerobot control

A hierarchical architecture is described which supports space station telerobots in a variety of modes. The system is divided into three hierarchies: task decomposition, world model, and sensory processing. Goals at each level of the task dedomposition heirarchy are divided both spatially and temporally into simpler commands for the next lower level. This decomposition is repreated until, at the lowest level, the drive signals to the robot actuators are generated. To accomplish its goals, task decomposition modules must often use information stored it the world model. The purpose of the sensory system is to update the world model as rapidly as possible to keep the model in registration with the physical world. The architecture of the entire control system hierarch is described and how it can be applied to space telerobot applications