We compared the ability of three different contextual models of lexical semantic memory and of a simple associative model to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others (...) on an associative network successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts, and contextual representations may be used to process information about more abstract concepts. (shrink)

Communication, as a discipline that generates a rich body of literature on CSR, has become a critical contributor to CSR knowledge in social science. However, limited research exists to understand how CSR knowledge is constructed and diffused in the discipline. This study thus intends to unpack the knowledge construction process of CSR research in the communication discipline from a network perspective. Invisible college was adopted as the conceptual framework. Article and theory/concept networks were constructed with 290 peer-reviewed articles from (...) 61 communication journals between 1980 and 2018. Results showed that in the past four decades, CSR literature in communication has been growing and maturing, as evidenced by the increasing volume and diversity of theories and concepts applied. Furthermore, this body of literature tends to gravitate toward certain selected groups of theories and concepts, resulting in denser article networks over time. Our findings reflected a substantial influence of management and psychological perspectives on CSR research in communication. Additionally, the results showed that public relations concepts and theories have influenced CSR research across different communication subfields such as advertising and organization communication. The study expects the continuation of the plurality of voices as to how communication researchers will approach CSR and what specific topics may gain popularity in future research. (shrink)

A network of aligned ontologies is a distributed system, whose components are interacting and interoperating, the result of this interaction being, either the extension of local assertions, which are valid within each individual ontology, to global assertions holding between remote ontology syntactic entities through a network path, or to local assertions holding between local entities of an ontology, but induced by remote ontologies, through a cycle in the network. The mechanism for achieving this interaction is the composition of relations. In (...) this perspective, we introduce the notions of local composable relations, which relate ontology entities belonging to the same ontology, remotely induced composable relations, which relate ontology entities belonging to remote ontologies through a path of ontologies and alignments in the network, and network induced local composable relations, which relate ontology entities belonging to the same ontology, but through a path of ontologies and alignments forming a cycle starting and ending at the same ontology, to characterize the logical consequences extracted from a network of aligned ontologies, and we propose a category-based methodology for detecting semantic inconsistencies in networks of aligned ontologies, which is based on contravariant representable functors and on the definition of two composition operators suitable for propagating local knowledge through the network. (shrink)

ObjectiveType 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.MethodsA total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic (...) resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.ResultsIn patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.ConclusionFunctional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM. (shrink)

The rise of mathematical developments in the theories of consciousness has led to new measures to detect consciousness in a system. The Integrated Information Theory is one of the best mathematical rooted attempts to quantify the level of consciousness in a system with Φ as the effective information generated in a system above its parts. Recently, the IIT has inspired the Perturbational Complexity Index to detect conscious states in patients with disorders of consciousness, and it has shown to have almost (...) perfect classification accuracy. In this study, we explore the statistical correspondence between the theoretical Φ and the experimental PCI through a neurocomputational model of coupled oscillators that can be artificially perturbed, which mainly focuses on the dynamics of collective synchronization between subsets of brain areas. Our results reveal that both measures are statistically related but, in principle, this relationship is far to be perfect. These results are discussed in the context of the model of coupled oscillators, which mainly focuses on the dynamics of collective synchronization between subsets of brain areas. (shrink)

Behavioural Network Science provides a comprehensive introduction to network science for social and behavioral researchers and students. It is a self-contained guide to the fundamentals of network science, beginning with principles of representing and making networks, network metrics, and network evolution. It then delves into specific applications of network science to behavioral research including language evolution, learning, memory, aging, creativity, conspiracies, group problem-solving, opinion polarization, and social conflict. Within each application, theoretical aspects surrounding a core problem are discussed, providing (...) readers with an intuitive understanding of how network science can be employed to quantify and generate behavioural phenomena. Accompanying online R code allows readers to replicate simulations and generate figures. This book is an essential reference for graduate students and researchers in cognitive sciences, behavioural economics, and health and social policy seeking a nuanced understanding of the intersection between network science and behavioural research. (shrink)

The emerging area of network biology is seeking to provide insights into organizational principles of life. However, despite significant collaborative efforts, there is still typically a weak link between biological and computational scientists and a lack of understanding of the research issues across the disciplines. This results in the use of simple computational techniques of limited potential that are incapable of explaining these complex data. Hence, the danger is that the community might begin to view the topological properties of network (...) data as mere statistics, rather than rich sources of biological information. A further danger is that such views might result in the imposition of scientific doctrines, such as scale-free-centric (on the modeling side) and genome-centric (on the biological side) opinions onto this area. Here, we take a graph-theoretic perspective on protein-protein interaction networks and present a high-level overview of the area, commenting on possible challenges ahead. (shrink)

Mitochondria can change their shape from discrete isolated organelles to a large continuous reticulum. The cellular advantages underlying these fused networks are still incompletely understood. In this paper, we describe and compare hypotheses regarding the function of mitochondrial networks. We use mathematical and physical tools both to investigate existing hypotheses and to generate new ones, and we suggest experimental and modelling strategies. Among the novel insights we underline from this work are the possibilities that (i) selective mitophagy is (...) not required for quality control because selective fusion is sufficient; (ii) increased connectivity may have non‐linear effects on the diffusion rate of proteins; and (iii) fused networks can act to dampen biochemical fluctuations. We hope to convey to the reader that quantitative approaches can drive advances in the understanding of the physiological advantage of these morphological changes. (shrink)

The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention (...) to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems. (shrink)

This article explores the domain of legal analysis and its methodologies, emphasising the significance of generalisation in legal systems. It discusses the process of generalisation in relation to legal concepts and the development of ideal concepts that form the foundation of law. The article examines the role of logical induction and its similarities with semantic generalisation, highlighting their importance in legal decision-making. It also critiques the formal-deductive approach in legal practice and advocates for more adaptable models, incorporating fuzzy logic, non-monotonic (...) defeasible reasoning, and artificial intelligence. The potential application of neural networks, specifically deep learning algorithms, in legal theory is also discussed. The article discusses how neural networks encode legal knowledge in their synaptic connections, while the syllogistic model condenses legal information into axioms. The article also highlights how neural networks assimilate novel experiences and exhibit evolutionary progression, unlike the deductive model of law. Additionally, the article examines the historical and theoretical foundations of jurisprudence that align with the basic principles of neural networks. It delves into the statistical analysis of legal phenomena and theories that view legal development as an evolutionary process. The article then explores Friedrich Hayek’s theory of law as an autonomous self-organising system and its compatibility with neural network models. It concludes by discussing the implications of Hayek’s theory on the role of a lawyer and the precision of neural networks. (shrink)

Social network analysis (SNA) is an increasingly popular approach that provides researchers with highly developed tools to map and analyze complexes of social relations. Although a number of network scholars have explicated the assumptions that underpin SNA, the approach has yet to be discussed in relation to established philosophies of science. This article argues that there is a tension between applied and methods-oriented SNA studies, on the one hand, and those addressing the social-theoretical nature and implications of networks, on (...) the other. The former, in many cases, exhibits positivist tendencies, whereas the latter incorporate a number of assumptions that are directly compatible with core critical realist views on the nature of social reality and knowledge. This article suggests that SNA may be detached from positivist social science and come to constitute a valuable instrument in the critical realist toolbox. (shrink)

We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some (...) surprising repercussions on the variety-of-evidence thesis and the Duhem-Quine thesis. (shrink)

Social network structure has been argued to shape the structure of languages, as well as affect the spread of innovations and the formation of conventions in the community. Specifically, theoretical and computational models of language change predict that sparsely connected communities develop more systematic languages, while tightly knit communities can maintain high levels of linguistic complexity and variability. However, the role of social network structure in the cultural evolution of languages has never been tested experimentally. Here, we present results from (...) a behavioral group communication study, in which we examined the formation of new languages created in the lab by micro‐societies that varied in their network structure. We contrasted three types of social networks: fully connected, small‐world, and scale‐free. We examined the artificial languages created by these different networks with respect to their linguistic structure, communicative success, stability, and convergence. Results did not reveal any effect of network structure for any measure, with all languages becoming similarly more systematic, more accurate, more stable, and more shared over time. At the same time, small‐world networks showed the greatest variation in their convergence, stabilization, and emerging structure patterns, indicating that network structure can influence the community's susceptibility to random linguistic changes (i.e., drift). (shrink)

The comorbidity of personality disorders and mental disorders is commonly understood through three types of theoretical models: either a) personality disorders precede mental disorders, b) mental disorders precede personality disorders, c) mental disorders and personality disorders share common etiological grounds. Although these hypotheses differ with respect to their idea of causal direction, they all imply a latent variable perspective, in which it is assumed that either personality and mental disorders are latent variables that have certain causal relations [models a) and (...) b)]; or that, as in model c), the common etiology is in fact a latent variable that causes symptomatology of both personality and mental disorders. We aim to provide another perspective on the comorbidity between personality and mental disorders, namely a network perspective. To this end, we investigated Major Depression and Borderline Personality Disorder and hypothesized that symptoms of BPD and MD could interact with one another rather than being caused by a latent variable. To illustrate this theoretical network conceptualization of the comorbidity of BPD and MD we analyzed a cross-sectional clinical dataset of 376 patients who were asked to complete the Structured Clinical Interview for DSM-IV Axis II Disorders and the Beck Depression Inventory II. The results identify direct associations between symptoms of MD and BPD. If we take the links in this empirical network to be ‘substantive', this suggests a radical shift of our current conceptualization of the comorbidity of mental disorders and personality disorders. (shrink)

Languages show substantial variability between their speakers, but it is currently unclear how the structure of the communicative network contributes to the patterning of this variability. While previous studies have highlighted the role of network structure in language change, the specific aspects of network structure that shape language variability remain largely unknown. To address this gap, we developed a Bayesian agent‐based model of language evolution, contrasting between two distinct scenarios: language change and language emergence. By isolating the relative effects of (...) specific global network metrics across thousands of simulations, we show that global characteristics of network structure play a critical role in shaping interindividual variation in language, while intraindividual variation is relatively unaffected. We effectively challenge the long‐held belief that size and density are the main network structural factors influencing language variation, and show that path length and clustering coefficient are the main factors driving interindividual variation. In particular, we show that variation is more likely to occur in populations where individuals are not well‐connected to each other. Additionally, variation is more likely to emerge in populations that are structured in small communities. Our study provides potentially important insights into the theoretical mechanisms underlying language variation. (shrink)

A small consortium of philosophers has begun work on the implications of epistemic networks (Zollman 2008 and forthcoming; Grim 2006, 2007; Weisberg and Muldoon forthcoming), building on theoretical work in economics, computer science, and engineering (Bala and Goyal 1998, Kleinberg 2001; Amaral et. al., 2004) and on some experimental work in social psychology (Mason, Jones, and Goldstone, 2008). This paper outlines core philosophical results and extends those results to the specific question of thresholds. Epistemic maximization of certain types does (...) show clear threshold effects. Intriguingly, however, those effects appear to be importantly independent from more familiar threshold effects in networks. (shrink)

In this wide-ranging conversation, Berry and Galloway explore the implications of undertaking media theoretical work for critiquing the digital in a time when networks proliferate and, as Galloway claims, we need to ‘forget Deleuze’. Through the lens of Galloway’s new book, Laruelle: Against the Digital, the potential of a ‘non-philosophy’ for media is probed. From the import of the allegorical method from excommunication to the question of networks, they discuss Galloway’s recent work and reflect on the implications of (...) computation for media theory, thinking about media objects, and critical theory. (shrink)

Neural network models have recently made significant achievements in solving vehicle scheduling problems. Adaptive ant colony algorithm provides a new idea for neural networks to solve complex system problems of multiconstrained network intensive vehicle routing models. The pheromone in the path is changed by adjusting the volatile factors in the operation process adaptively. It effectively overcomes the tendency of the traditional ant colony algorithm to fall easily into the local optimal solution and slow convergence speed to search for the (...) global optimal solution. The multiconstrained network intensive vehicle routing algorithm based on adaptive ant colony algorithm in this paper refers to the interaction between groups. Adaptive transfer and pheromone update strategies are introduced based on the traditional ant colony algorithm to optimize the selection, update, and coordination mechanisms of the algorithm further. Thus, the search task of the objective function for a feasible solution is completed by the search ants. Through the division and collaboration of different kinds of ants, pheromone adaptive strategy is combined with polymorphic ant colony algorithm. It can effectively overcome some disadvantages, such as premature stagnation, and has a theoretical significance to the study of large-scale multiconstrained vehicle routing problems in complex traffic network systems. (shrink)

We examine recent work in cognitive neuroscience that investigates brain networks. Brain networks are characterized by the ways in which brain regions are functionally and anatomically connected to one another. Cognitive neuroscientists use various noninvasive techniques (e.g., fMRI) to investigate these networks. They represent them formally as graphs. And they use various graph theoretic techniques to analyze them further. We distinguish between knowledge of the graph theoretic structure of such networks (structural knowledge) and knowledge (...) of what instantiates that structure (nonstructural knowledge). And we argue that this work provides structural knowledge of brain networks. We explore the significance of this conclusion for the scientific realism debate. We argue that our conclusion should not be understood as an instance of a global structural realist claim regarding the structure of the unobservable part of the world, but instead, as a local structural realist attitude towards brain networks in particular. And we argue that various local approaches to the realism debate, i.e., approaches that restrict realist commitments to particular theories and/or entities, are problematic insofar as they don't allow for the possibility of such a local structural realist attitude. (shrink)

The current study investigates the influence of variety among online providers and customers' access to knowledge on consumer networks, consumer engagement, and sustainable purchasing. Emphasis is on the underlying relationships among these constructs in the digital economy, which has evolved into a complex structure of multifarious nodes and linkages unfolding in the online environment. The underlying theoretical approaches are knowledge-attitude-behavior (KAB) and customer sovereignty. Against this backdrop, a questionnaire-based survey was given to 200 Millennials (i.e., generation Y) and gen (...) Z Italians—approached as empowered stakeholders requiring accurate information and sustainable solutions from online providers—in January 2023. The data was processed via the structural equation modeling technique PLS-SEM, based on SmartPLS 4. The findings indicated that sustainable purchasing is influenced to some extent by access to knowledge, consumer engagement, and consumer networks. The study endeavors to fill a research gap, as the relationships between variety among online providers and sustainable purchasing, as well as consumer engagement from the empowerment perspective are underexplored. The study provides new evidence of the relationships between consumer networks, consumers' access to knowledge, sustainable purchasing, and consumer engagement in the framework of online retail by inquiring respondents. (shrink)

This article explores some current transformations of the social. It argues for a shift from a model of sociality based on community towards a network sociality. This shift is particularly visible in urban spaces and in the cultural industries. However, it seems to become paradigmatic more widely of the information society. The article is to be read as a cultural hypothesis. In the first part I introduce some examples that document the rise of a network sociality. Most of these examples (...) are drawn from a two-year ethnographic study of London's new media. The second part consists of a critique of some theoretical accounts of contemporary transformations of sociality. The third part is an attempt to outline the concept of network sociality. It is a form of sociality that is ephemeral but intense, it is informational and technological, it combines work and play, it is disembedded and generic, and it emerges in the context of individualization. (shrink)

The excessive use of social networks needs to be addressed, and this phenomenon needs to be measured for the purpose of evaluation, prevention, and intervention among adolescents and young people. The objective of the study was to adapt and psychometrically validate the Brief Scale of Addiction to Social Networks among Mexican adolescents and young adults. The participating sample consisted of 2,789 students from 6 public educational campuses in Cuernavaca. Data collection was carried out through a web platform to (...) strictly maintain anonymity, voluntary participation, and confidentiality. Data analysis first focused on the detection of possible response biases, the quality of the response structure partial credit model, dimensionality, and the relationship with external variables. It was found that when the range of efficient response options was limited to less than five, reliability was high, and unidimensionality was maintained. Response biases slightly affected the dimensional structure of the instrument. Measurement invariance reached scalar invariance in the sex, age, and campus groups. The association with sensation seeking and depression, controlling for sex and age covariates, was statistically significant, small, and theoretically consistent. Implications of the results are discussed. (shrink)

Although the characteristics and advantages of interorganizational governance models based on extensive collaboration are well established in the literature, inquiry has only recently extended to sustainable supply chain management, highlighting the potential benefits of combining the integration of social and environmental issues concerning the supply chain with governance models based on joint decision making and extensive cooperation. Yet, firms still differ in both the pervasiveness of such collaborative approaches along the value chain and the extent to which sustainability issues are (...) addressed to the advantage of all parties involved. In an attempt to predict variety in the governance models related to sustainability along the value chain, we propose a theoretical model that identifies and frames four sustainable supply chain governance (SSCG) models, resulting from combinations of supply chain network density and centrality of the focal organizations. We show how, as centrality increases, firms are able to exert influence over their network, coordinating integrated approaches along the value chain. Moreover, as high centrality combines with increasing interconnectedness of the actors within a supply chain network, instrumental approaches are progressively replaced by more relational attitudes aimed at joint value creation among partners. Conditions for SSCG models' success and the main benefits gained by firms in different structural contexts are also discussed. (shrink)

How can we deal with the diversity of theories in mathematics education? This was the main question that led the authors of this book to found the Networking Theories Group. Starting from the shared assumption that the existence of different theories is a resource for mathematics education research, the authors have explored the possibilities of interactions between theories, such as contrasting, coordinating, and locally integrating them. The book explains and illustrates what it means to network theories; it presents networking as (...) a challenging but fruitful research practice and shows how the Group dealt with this challenge considering five theoretical approaches, namely the approach of Action, Production, and Communication (APC), the Theory of Didactical Situations (TDS), the Anthropological Theory of the Didactic (ATD), the approach of Abstraction in Context (AiC), and the Theory of Interest-Dense Situations (IDS). A synthetic presentation of each theory and their connections shows how the activity of networking generates questions at the theoretical, methodological and practical levels and how the work on these questions leads to both theoretical and practical progress. The core of the book consists of four new networking case studies which illustrate what exactly can be gained by this approach and what kind of difficulties might arise. (shrink)

How can we deal with the diversity of theories in mathematics education? This was the main question that led the authors of this book to found the Networking Theories Group. Starting from the shared assumption that the existence of different theories is a resource for mathematics education research, the authors have explored the possibilities of interactions between theories, such as contrasting, coordinating, and locally integrating them. The book explains and illustrates what it means to network theories; it presents networking as (...) a challenging but fruitful research practice and shows how the Group dealt with this challenge considering five theoretical approaches, namely the approach of Action, Production, and Communication (APC), the Theory of Didactical Situations (TDS), the Anthropological Theory of the Didactic (ATD), the approach of Abstraction in Context (AiC), and the Theory of Interest-Dense Situations (IDS). A synthetic presentation of each theory and their connections shows how the activity of networking generates questions at the theoretical, methodological and practical levels and how the work on these questions leads to both theoretical and practical progress. The core of the book consists of four new networking case studies which illustrate what exactly can be gained by this approach and what kind of difficulties might arise. (shrink)

Background and PurposeTranscranial direct current stimulation is an emerging non-invasive neuromodulation technique for focal epilepsy. Because epilepsy is a disease affecting the brain network, our study was aimed to evaluate and predict the treatment outcome of cathodal tDCS by analyzing the ctDCS-induced functional network alterations.MethodsEither the active 5-day, −1.0 mA, 20-min ctDCS or sham ctDCS targeting at the most active interictal epileptiform discharge regions was applied to 27 subjects suffering from focal epilepsy. The functional networks before and after ctDCS (...) were compared employing graph theoretical analysis based on the functional magnetic resonance imaging data. A support vector machine prediction model was built to predict the treatment outcome of ctDCS using the graph theoretical measures as markers.ResultsOur results revealed that the mean clustering coefficient and the global efficiency decreased significantly, as well as the characteristic path length and the mean shortest path length at the stimulation sites in the fMRI functional networks increased significantly after ctDCS only for the patients with response to the active ctDCS. Our prediction model achieved the mean prediction accuracy of 68.3% after the nested cross validation. The mean area under the receiver operating curve was 0.75, which showed good prediction performance.ConclusionThe study demonstrated that the response to ctDCS was related to the topological alterations in the functional networks of epilepsy patients detected by fMRI. The graph theoretical measures were promising for clinical prediction of ctDCS treatment outcome. (shrink)

After a short description of the major sociological theories based on the concept of risk (Douglas, Beck, Luhmann, Giddens) I propose to integrate the concept of risk with the concept of trust. On a less theoretical level I propose to consider governance as the institutional response to the growing complexity of the risk society. Above all, network governance – that is institutional steering based on a high community participation – seems to give good results in the field of health care (...) policies, as has been shown in the Emilia-Romagna area (Italy). (shrink)

After a short description of the major sociological theories based on the concept of risk (Douglas, Beck, Luhmann, Giddens) I propose to integrate the concept of risk with the concept of trust. On a less theoretical level I propose to consider governance as the institutional response to the growing complexity of the risk society. Above all, network governance – that is institutional steering based on a high community participation – seems to give good results in the field of health care (...) policies, as has been shown in the Emilia-Romagna area (Italy). (shrink)

A complement to _Researching Schools_ by the same authors, this book provides readers with a strong theoretical framework for school-based research as well as valuable advice on the ways in which networks of specialist groups can work together to create a broad-ranging approach to educational research. Through a critical examination of existing research and current thinking, the authors draw out implications for the effective policy and practice of school-based research. Illustrated throughout with case studies and including a full and (...) detailed literature review, this book will be a vital resource for all academics pursuing research into education. (shrink)

JEL Classifications: L13, K42, L15 Keywords: anarcho-capitalism, networks, collusion Abstract: There is a tension between libertarians' optimism about private supply of public goods and their skeptical of the viability of voluntary collusion. (Cowen 1992; Cowen and Sutter 1999) Playing off this asymmetry, Cowen (1992) advances the novel argument that the "free market in defense services" favored by anarcho-capitalists is a network industry where collusion is especially feasible. The current article dissolves Cowen's asymmetry, showing that he fails to distinguish between (...) self-enforcing and non-self-enforcing interaction. Case study evidence on network behavior before and after antitrust supports our analysis. Furthermore, libertarians' joint beliefs on public goods and collusion are more theoretically defensible than Cowen and Sutter (1999) indicate. (shrink)

This book develops an original theoretical framework for understanding human-technology relations. The author's approach, which he calls technoanalysis, analyzes artificial intelligence based on Freudian psychoanalysis, biosemiotics, and Latour's actor-network theory. How can we communicate with AI to determine shared values and objectives? And what, ultimately, do we want from machines? These are crucial questions in our world, where the influence of AI-based technologies is rapidly growing. Unconscious dynamics influence AI and digital technology and understanding them is essential to better controlling (...) AI systems. This book's unique methodology- which combines psychoanalysis, biosemiotics, and actor-network theory-reveals a radical reformulation of the problem of the human mind. Technoanalysis views the mind as a hybrid network of humans and nonhuman actants in constant interaction with one another. The author argues that human unconscious dynamics influence and shape technology, just as technology influences and shapes human unconscious dynamics. He proceeds to show how this conception of the relationship between the unconscious and technology can be applied to social robotics and AI. Unconscious Networks will appeal to scholars and advanced students interested in philosophy of technology, philosophy of artificial intelligence, psychoanalysis, and science and technology studies. (shrink)

The author presents an historical account of scientific work conducted at a commercial biotech firm in San Diego called Hybritech. It tells of disruptions in research programs following the acquisition of the company by the pharmaceutical giant Eli Lilly in 1986. The story centers on responses to an organizational challenge that research managers and scientists in any setting, academic or industrial, must confront—how to create and sustain an organizational culture that is conducive to creativity and innovation. The case provides an (...) occasion for evaluating the strengths and weaknesses of two leading theoretical accounts of innovation in social studies of science and technology—sociological network analysis and actor-network theory. (shrink)

The article aims at exploring the social constituents of anxiety, which is considered to be a phenomenological cost of late modern social distortions. Firstly, the social theoretical background is elaborated based on a network theoretical synthesis of Bourdieu’s and Habermas’ phenomenologically grounded social theories, which aim at elaborating the social suffering caused by unfair competition and distorted communication. Secondly, an attempt is made to identify the key phenomenological characteristics of anxiety: based on psychoanalytic and cognitive psychological descriptions, it is defined (...) as a non-reactive, non-targeted fear, resulting in the generalization of worry. These two approaches are connected in order to identify those social distortions, which contribute to the emergence of such diffuse fear. The most typical examples are networks characterized by unstable competition and non-transparent and volatile competition or collective traumas, distrust or inefficient systems. (shrink)

In the following article, we propose an analytical framework for the analysis of Corporate Social Responsibility (CSR) Standards based on the paradigmatic nexus of voice and entitlement. We follow the theory of decentration and present the concept of Transnational Norm-Building Networks (TNNs), which — as we argue — comprise a new nexus of voice and entitlement beyond the nation—state level. Furthermore, we apply the analytical framework to the ISO 26000 initiative and the Global Compact. We conclude the article with (...) remarks on the legitimacy and the effectiveness of norms generated by TNNs. Through this, we aim to contribute a new theoretical foundation to the analysis of CSR standards, which enables us to undertake a more differentiated description of TNN structures which have hitherto been ignored in academic literature. Secondly, we will contribute to the practical debate on ISO 26000 and the Global Compact by proposing new perspectives on the conditions of their legitimacy and effectiveness based on the voice-entitlement nexus. (shrink)