The state of methods and tools for social systems change

The last decade or so has seen an increase in the rate of attention to systems change and the application of multiple theories to study and influence change in systems. This article considers how these theories, described in other articles in this issues, plus theories about complex adaptive systems open opportunities for us to continue to expand our repertoire of tools and methods to address systems change. These conceptual frameworks, tools, and methods are expected to help us increase our capacity to study and influence both planned and self-organizing systems change. New tools and methods have emerged and others are needed to help us continue to explore and influence the complex social systems within which we operate.     

Belief systems in administration and training

Belief systems are instruments for observing events, classifying information, communicating with others, and doing therapy. A belief system is a combination of feelings, thoughts, actions, and expectations. Belief systems operating in the training environment affect how therapists are able to deal with transference and countertransference. Belief systems must be evaluated in terms of whether they are comprehensive, delusional, absent, sinelusional, and the extent to which they are structuring us. The use of belief systems provides us with an appreciation of our own activities, an instrument for conveying our feelings, and, most importantly, a means for understanding the views of others.     

网络使用经验对动作动词加工的影响

具身认知理论认为高级概念认知和低级感知觉认知紧密关联, 且两者共享相同的神经系统。本研究设计了3个实验：实验1观察面部表情动词加工是否受面部情绪表达的影响, 结果发现网络使用经验多的被试在促进和抑制面部积极表情条件下对动词的反应没有表现出显著差异。实验2探讨网络使用经验对肢体动作词汇加工的影响, 结果发现网络使用经验多的被试在动词?名词转换时没有产生显著认知损耗。实验3探讨两类被试对正常序列和随机序列图式动词加工是否有差异, 结果发现网络使用经验多的个体对随机序列和正常序列的回忆成绩并无显著差异。本研究从动词认知加工角度验证了高级认知与低级感知觉加工间的紧密联系, 揭示了网络行为与高级认知加工间的相关关系。     

A Utility Based Evaluation of Logico-probabilistic Systems

Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to the dominant paradigm for assessing the rationality of actions and decisions, our present evaluation complements our previous work, since our previous evaluation may have been too severe in its assessment of inferences to false and uninformative conclusions. In the end, our new results provide additional support for the conclusion that (of the four systems considered) inference by system Z offers the best balance of error avoidance and inferential power. Our new results also suggest that improved performance could be achieved by a modest strengthening of system Z.     

A satellite system for controlling real-time experiments

In this paper, we describe a computer system for controlling real-time psychology experiments. We begin by considering the kinds of experiments that are performed in our laboratory and examining the hardware and software requirements of these experiments. We then review various systems along a continuum ranging from general-purpose timesharing systems to stand-alone dedicated processors. The capabilities of these systems are described in comparison with our requirements. The features of the PARASITE-FS system are then described. This host-satellite system includes a local file system and monitor program, real-time device drivers with flexible interrupt processing capabilities, user-level routines for controlling the real-time devices, and a package for controlling the timing of experimental events.     

The Simplest Axiom System for Hyperbolic Geometry Revisited,Again

Dependencies are identified in two recently proposed first-order axiom systems for plane hyperbolic geometry. Since the dependencies do not specifically concern hyperbolic geometry, our results yield two simpler axiom systems for absolute geometry.     

Turtle Soup: Establishing Innovation-Friendly Conditions' for School Reform

Pressure groups in today's complex society present our school systems with diverse, conflicting demands for school reform. Educators can retain eroding public support only through pervasive innovations in our school systems. In order for our schools to survive and thrive in changing times, educators must overcome serious organizational and contextual barriers that inhibit innovation in the schools. Educational leaders must address these barriers by attending to the essential nature of creative thought, and to some basic tenets of organizational change. These concepts are portrayed in the form of a visual metaphor, which captures the essence of creative organizational development and recommends some specific Jeadership initiatives.     

Streams and consciousness: visual awareness and the brain

Vision is our most powerful sense and, arguably, it gives us our most vivid sensory and imaginal experiences. It is also one of the best understood systems in contemporary neuroscience. Yet, contrary to both traditional assumptions and our phenomenological intuition, recent research has shown that vision is not a monolithic system that creates a single general-purpose representation in the brain. For example, selective brain damage can compromise visuomotor control while leaving perception intact, and damage elsewhere can compromise visual perception while leaving visuomotor control intact. Thus, it is becoming apparent that we have two (largely) separate visual systems. One of them is dedicated to the rapid and accurate guidance of our movements: it is a complex and powerful system, and yet it lies outside the realm of our conscious visual awareness. The other seems to provide our perceptual phenomenology, although its primary purpose is probably to provide suitably coded visual inputs for storage in and retrieval from memory. According to this conceptualization, both systems can be seen as serving our behaviour, but each does so on a different time scale. Recent studies suggest that neuropsychological research in humans can play a central role in bridging the gap between neurobiological studies of the monkey's visual system and the search to narrow down the brain mechanisms that mediate our visual awareness.     

A probabilistic model of theory formation

Concept learning is challenging in part because the meanings of many concepts depend on their relationships to other concepts. Learning these concepts in isolation can be difficult, but we present a model that discovers entire systems of related concepts. These systems can be viewed as simple theories that specify the concepts that exist in a domain, and the laws or principles that relate these concepts. We apply our model to several real-world problems, including learning the structure of kinship systems and learning ontologies. We also compare its predictions to data collected in two behavioral experiments. Experiment 1 shows that our model helps to explain how simple theories are acquired and used for inductive inference. Experiment 2 suggests that our model provides a better account of theory discovery than a more traditional alternative that focuses on features rather than relations.     

Learning to learn causal models

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning.     

Apple II/FIRST-Corvus networks

Our Apple II/FIRST hardware-software configuration is a cost-effective, powerful, and efficient system for experimental control, data collection, and signal analysis of research in conditioning, neurophysiology, psychopharmacology, and psychophysiology. The present report describes the enhancement of our data-processing capabilities by the addition of peripheral hardware configured to form Corvus multiplexer networks. These networks have transformed our array of Apple II/FIRST systems into multiprocessor facilities possessing the data-processing power and flexibility of far larger and more costly mainframe systems while retaining the benefits of the markedly reduced cost, great flexibility, and high processing speed of microprocessor-based systems.     

The Cultural Underpinnings of Subjectivity and Inter-Subjectivity: A Discussion of “Trump Cards and Klein Bottles: On the Collective of the Individual”

In “Trump Cards and Klein Bottles: On the Collective of the Individual,” Dr. González (this issue) argues for the centrality of dynamic and shifting group identifications in shaping our subjectivity and our inter-subjective linking from moment to moment. My commentary about this paper is organized around the themes of cultural dislocation and cultural displacement, experiences related to large-group identifications and identity. These constructs, cultural dislocation and displacement, can deepen our understanding of how inter/intra-group tensions (historic and current) can play a determinative role in shaping individual subjectivity and inter-subjective linking. They complement and amplify claims regarding the centrality of our group identifications on ego functions. They also point toward the determinative impact of context and clashing cultural systems on our object relations and unconscious fantasies. Studying the links between individuals, collectives, and the cultural systems that structure them will deepen our theories and extend our relevance.     

FINITE MODELS CONSTRUCTED FROM CANONICAL FORMULAS

This paper obtains the weak completeness and decidability results for standard systems of modal logic using models built from formulas themselves. This line of work began with Fine (Notre Dame J. Form. Log. 16:229–237, 1975). There are two ways in which our work advances on that paper: First, the definition of our models is mainly based on the relation Kozen and Parikh used in their proof of the completeness of PDL, see (Theor. Comp. Sci. 113–118, 1981). The point is to develop a general model-construction method based on this definition. We do this and thereby obtain the completeness of most of the standard modal systems, and in addition apply the method to some other systems of interest. None of the results use filtration, but in our final section we explore the connection.     

Open source and these United States

Over the past forty years a collaborative form of systems development has evolved on the electronic networks of the world. In the wake of the information technology revolution has come a proven method for developing, deploying, and maintaining these systems. This method, developed under the auspices of Department of Defense research grants, has resulted in the most successful and reliable software in existence. The method, based on collaborative intelligence, peer review and functional evolution, has rippled through the world of Information Technology. Its success depends on the uninhibited distribution of the currency of this realm: the source code, documentation and data that are the building blocks of complex information systems. To enhance collaboration and protect its creators, cutting edge source code is commonly released under Open Source licensing. The associated electronic information is released under open content licensing. Together, I call this duo Open Licensing. The Department of Defense can realize significant gains by the formal adoption, support and use of open licensed systems. We can lower costs and improve the quality of our systems and the speed at which they are developed. Open Licensing can improve the morale and retention of airmen and improve our ability to defend the nation. These benefits are accessible at any point in the acquisition cycle and even benefit deployed and operational systems. Open Licensing can reduce acquisition, development, maintenance and support costs and increased interoperability among our own systems and those of our allies. He has been stationed at the Pentagon and Phillips Laboratory. In addition to his military duties, he has taught at George Washington University and the University of Massachusetts at Lowell. He has an undergraduate degree in Electrical Engineering and Computer Science and graduate degrees in Business Administration and Computer Science.     

Hypothesizing about signaling networks

The current knowledge about signaling networks is largely incomplete. Thus biologists constantly need to revise or extend existing knowledge. The revision and/or extension is first formulated as theoretical hypotheses, then verified experimentally. Many computer-aided systems have been developed to assist biologists in undertaking this challenge. The majority of the systems help in finding “patterns” in data and leave the reasoning to biologists. A few systems have tried to automate the reasoning process of hypothesis formation. These systems generate hypotheses from a knowledge base and given observations. A main drawback of these knowledge-based systems is the knowledge representation formalism they use. These formalisms are mostly monotonic and are now known to be not quite suitable for knowledge representation, especially in dealing with the inherently incomplete knowledge about signaling networks. We propose an action language based framework for hypothesis formation for signaling networks. We show that the hypothesis formation problem can be translated into an abduction problem. This translation facilitates the complexity analysis and an efficient implementation of our system. We illustrate the applicability of our system with an example of hypothesis formation in the signaling network of the p53 protein.     

Facing up to Complexity: Implications for Our Social Experiments

Biological systems are highly complex, and for this reason there is a considerable degree of uncertainty as to the consequences of making significant interventions into their workings. Since a number of new technologies are already impinging on living systems, including our bodies, many of us have become participants in large-scale “social experiments”. I will discuss biological complexity and its relevance to the technologies that brought us BSE/vCJD and the controversy over GM foods. Then I will consider some of the complexities of our social dynamics, and argue for making a shift from using the precautionary principle to employing the approach of evaluating the introduction of new technologies by conceiving of them as social experiments.     

The holistic paradigm

Our present age is characterized by rapid processes of social transformation due to the rise of the systems sciences, computers and information technology. Part I of this paper distinguishes two perspectives for an interpretation of the ongoing evolution of our society as influenced by these newer developments in science and technology. From a structural perspective we argue that they have not created a society with entirely new structures, but just an expansion and intensification of the organizational‐technical systems which have typified the technological society since the Industrial Revolution. From a worldview perspective on our society we conclude that “systems rationalism” reinforces the prevailing technical worldview which fosters a progressive technical control and streamlining of society and human adaptation to its framework.     

Systemic therapy and attachment narratives

In this paper we describe how we bring together three major systems of thought: attachment theory; family systems theories; and theories of narrative development, in an integrated approach to systemic practice that we call attachment narrative therapy (ANT). ANT provides a four‐stage framework for practice: creating a secure base; exploring narratives and attachment experiences within a systemic framework; considering alternatives and taking action; and the future and maintenance of the therapeutic base. Formulation, especially regarding the role of emotions and attachments in family dynamics and narratives, is at the heart of our approach and helps us hold ourselves accountable for our particular weave of theory and practice.