PurposeThe purpose of this paper is to conduct a critical analysis to address cultural metaphors – a much overlooked aspect of cross-cultural studies. Mainstream cultural metaphors (e.g. the iceberg, the software of the mind, the onion, and the distance) are not only limited in number, but are also overwhelmingly based on the static paradigm – as opposed to the dynamic paradigm that is often sidelined in academic discourse.Design/methodology/approachThe paper introduces the Diagram of Diversity Pathways – an interdisciplinary framework that sheds some light on how the inherent meaning and heuristic orientation of static cultural metaphors may stand at odds with evidence from the newly emerged field of neurobiology.FindingsThe implications of these metaphors are called into question, namely, culture is all about differences; values are stable; values guide behaviors; and values are seen as binaries.Research limitations/implicationsThe paper suggests that theorists and practitioners should pay more attention to the contribution and scholarly work of the dynamic paradigm since there appears to be substantial compatibility between them.Originality/valueThe matching of neurobiology and dynamic paradigm brings into focus alternative metaphors which not only offer insightful perspectives but also may open doors to perceive culture in a new way. Furthermore, cultural metaphors deserve more academic scrutiny because metaphors and theory development can have a symbiotic existence.
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Recently several attempts were undertaken to unite the field of metaphor studies, trying to reconcile the conceptual/cognition and linguistic/discourse approaches to metaphor (Hampe, 2017b). The dynamic view of metaphor espoused by amongst others Gibbs (2017a) as a way to unify the field of metaphor studies is said to converge on findings and theoretical predictions found in cognition and discourse approaches. The author argues this focus on dynamical models to explain the multi-scale socio-cognitive aspects of metaphor as an emergent phenomenon is not robust enough. Complexity and dynamical systems are merely a modelling technique to deploy theory for empirical testing of hypotheses; a dynamic view of metaphor needs a coherent background theory to base its dynamic modelling of metaphor in action on (Chemero, 2009). I argue that it can be successfully based on the ecological-enactive framework available within the modern paradigm of 4E cognitive science. This framework makes possible explanation of both 'lower' cognition and 'higher' cognition emerging in the interaction of an organism with its environment. In addition, I sketch how recent theoretical insights from ecological-enactivism (Baggs and Chemero, 2018) concerning Gibson's notion of environment apply to the attempted unification of the field of metaphor studies. I close by suggesting how an understanding of metaphor as an ecological affordance of the socio-cultural environment can provide a rich basis for empirical hypotheses within a dynamical science of metaphor.
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In: Frank Gadinger, Martina Kopf, Ayşem Mert, and Christopher Smith (eds.). Political Storytelling: From Fact to Fiction (Global Dialogues 12) This essay presents a summary of important perspectives concerning the distinction between what counts as truth or fiction. As a source of inspiration, it starts with two examples found in literature – the first a classical Spanish novel and the second a collection of stories written by the leader of a social movement in Mexico. These two examples of the conflictive relations between truth and fiction, authenticity and imagination serve as a source of inspiration for the rest of this article, which shows that this issue has been a subject of intense debate in philosophy and in the philosophy of science and still presents a challenge in the 21st century. The essay states that absolute, objective truth is a myth. It describes that what counts as ‘truth’ in a particular era, is, among other things, the result of power relations. It suggests productive ways to deal with this problem in modern society, through deliberative, emancipatory processes of reflexivity (Weick 1999), participatory research and dialogue, facilitating innovation and generation of new solutions.
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The transition towards an economy of wellbeing is complex, systemic, dynamic and uncertain. Individuals and organizations struggle to connect with and embrace their changing context. They need to create a mindset for the emergence of a culture of economic well-being. This requires a paradigm shift in the way reality is constructed. This emergence begins with the mindset of each individual, starting bottom-up. A mindset of economic well-being is built using agency, freedom, and responsibility to understand personal values, the multi-identity self, the mental models, and the individual context. A culture is created by waving individual mindsets together and allowing shared values, and new stories for their joint context to emerge. It is from this place of connection with the self and the other, that individuals' intrinsic motivation to act is found to engage in the transitions towards an economy of well-being. This project explores this theoretical framework further. Businesses play a key role in the transition toward an economy of well-being; they are instrumental in generating multiple types of value and redefining growth. They are key in the creation of the resilient world needed to respond to the complex and uncertain of our era. Varta-Valorisatielab, De-Kleine-Aarde, and Het Groene Brein are frontrunner organizations that understand their impact and influence. They are making bold strategic choices to lead their organizations towards an economy of well-being. Unfortunately, they often experience resistance from stakeholders. To address this resistance, the consortium in the proposal seeks to answer the research question: How can individuals who connect with their multi-identity-self, (via personal values, mental models, and personal context) develop a mindset of well-being that enables them to better connect with their stakeholders (the other) and together address the transitional needs of their collective context for the emergence of a culture of the economy of wellbeing?
DISCO aims at fast-tracking upscaling to new generation of urban logistics and smart planning unblocking the transition to decarbonised and digital cities, delivering innovative frameworks and tools, Physical Internet (PI) inspired. To this scope, DISCO will deploy and demonstrate innovative and inclusive urban logistics and planning solutions for dynamic space re-allocation integrating urban freight at local level, within efficiently operated network-of-networks (PI) where the nodes and infrastructure are fixed and mobile based on throughput demands. Solutions are co-designed with the urban logistics community – e.g., cities, logistics service providers, retailers, real estate/public and private infrastructure owners, fleet owners, transport operators, research community, civil society - all together moving a paradigm change from sprawl to data driven, zero-emission and nearby-delivery-based models.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
