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complexity, multiple uncertainties, major ambiguities, and transgressive effects on other systems outside of the system of origin. due to these characteristics, systemic risks are overextending established risk management and create new, unsolved challenges for policymaking in risk assessment and risk governance. their negative effects are often pervasive, impacting fields beyond the obvious primary areas of harm. this article addresses these challenges of systemic risks from different disciplinary and sectorial perspectives. it highlights the special contributions of these perspectives and approaches and provides a synthesis for an interdisciplinary understanding of systemic risks and effective governance. the main argument is that understanding systemic risks and providing good governance advice relies on an approach that integrates novel modeling tools from complexity sciences with empirical data from observations, experiments, or simulations and evidence-based insights about social and cultural response patterns revealed by quantitative (e.g., surveys) or qualitative (e.g., participatory appraisals) investigations. systemic risks cannot be easily characterized by single numerical estimations but can be assessed by using multiple indicators and including several dynamic gradients that can be aggregated into diverse but coherent scenarios. lastly, governance of systemic risks requires interdisciplinary and cross-sectoral cooperation, a close monitoring system, and the engagement of scientists, regulators, and stakeholders to be effective as well as socially acceptable. 2. title: systemic risk: the threat to societal diversity and coherence authors: ortwin renn, klaus lucas abstract: insights from complexity science can be applied to the analysis of social processes in heterogeneous societies. many features that characterize and influence complex structures in nearly every domain of nature, technology, and society can be derived from simple modeling processes in physics and chemistry. if one applies these features to the structure of social risks, a number of insights are gained that can be subject to further empirical analysis. in particular, they add�to the well-known steering mechanisms of hierarchy, competition, and cooperation�the contribution of self-organization, the effect of which is underestimated in almost all theories of social science. but in view of the crises facing modern democracy, such as migration and populism, it is precisely this mechanism of dynamic structure generation that is decisive for an effective and fair risk governance. in this article, we analyze the threat to societal diversity and coherence on the basis of complexity science. 3. title: theory of systemic risks: insights from physics and chemistry authors: klaus lucas abstract: systemic risks, as opposed to conventional risks, bear the danger of destroying entire systems. their understanding and governance remain a serious challenge. the phenomena of systemic risks show many analogies with those of dynamic structure generation in the systems of nature, technology, and society, including simple model systems of physics and chemistry. by analyzing these model systems, the elementary processes and the generic mechanisms by which they generate macroscopic dynamic structures become evident. generalizing these insights makes it possible to formulate the basic framework of a theory of systemic risks with elements providing hints for adequate governance strategies. although these insights cannot be applied to societal processes one by one, they reveal generic patterns and clusters. 4. title: a proposal for integrating theories of complexity for better understanding global systemic risks authors: armin haas, manfred laubichler, joffa applegate, gesine steudle, carlo c. jaeger abstract: the global financial crisis of 2008 has shown that the present financial system involves global systemic risks. the dimension of these risks is hard to grasp with the conceptual tools that have been developed to tackle conventional risks like fire or car accidents. while modern societies know quite well how to deal with conventional risks, we have not yet been equally successful at dealing with global systemic risks. for managing this kind of risks, one needs to understand critical features of specific global systems where many human agents interact in ever changing complex networks. here we apply two specific dimensions of complexity theory for dealing with global systemic risk in an integrated fashion: normal accidents and extended evolution. both of them have successfully been applied to the analysis of systemic risks. as a paradigmatic example of global systemic risks, we focus on the global financial crisis that began in 2008, and suggest that the future evolution of the financial system could either see a further increase in complexity, or a reversal to a less complex system. we explore and contrast the implications of normal accident theory and extended evolution perspectives and suggest a four-point research strategy informed by complexity theory for better understanding global systemic risks in financial systems. 5. title: volatility as a transmitter of systemic risk: is there a structural risk in finance? authors: harald a. mieg abstract: this article discusses the role of volatility in the context of systemic risk in finance. the main argument is that volatility transmits risks within the financial system and beyond, shaking the financial system and threatening in particular small or vulnerable clients (smes, households, and also low- and middle-income countries). in addition, it is argued that volatility-induced threats result from structural characteristics of the financial markets themselves (reactivity, reflexivity, and recursivity). the article introduces the concept of volatility, and different approaches to understanding risks related to the financial system (e.g., financial analysis, systems analysis). two cases related to systemic risk are presented. the first concerns the role of volatility in three major financial crises (stock crash 1987, asian crisis 1996�1997, global banking crisis 2007�2008), documenting that volatility spillovers have become a �new normal.� the second case concerns the moderate reflection of systemic risk within the journal of finance (the leading financial journal). the two cases show that volatility plays a role in systemic risks, but that this role has not yet been examined in detail by the scientific community. 6. title: a precautionary assessment of systemic projections and promises from sunlight reflection and carbon removal modeling authors: sean low, matthias honegger abstract: climate change is a paradigmatic example of systemic risk. recently, proposals for large-scale interventions�carbon dioxide removal (cdr) and solar radiation management (srm)�have started to redefine climate governance strategies. we describe how evolving modeling practices are trending toward optimized and �best-case� projections�portraying deployment schemes that create both technically slanted and politically sanitized profiles of risk, as well as ideal objectives for cdr and srm as mitigation-enhancing, time-buying mechanisms for carbon transitions or vulnerable populations. as promises, stylized and hopeful projections may selectively reinforce industry and political activities built around the inertia of the carbon economy. some evidence suggests this is the emerging case for certain kinds of cdr, where the prospect of future carbon capture substitutes for present mitigation. either of these implications are systemic: explorations of climatic futures may entrench certain carbon infrastructures. we point out efforts and recommendations to forestall this trend in the implementation of the paris agreement, by creating more stakeholder input and strengthening political realism in modeling and other assessments, as well as through policy guardrails. 7. title: to blame is human: a quantitative systematic review of the relationship between outcome severity of large-scale crises and attributions of blame authors: christine gilbert abstract: in crisis situations, time is of the essence. effective messaging to individuals at risk is critical to mitigating the most severe outcomes. extant crisis communication literature has focused on differentiating crisis types based on perceived blame, particularly in cases of for-profit company malfeasance, but less work has been done to understand how the public makes these types of attributions. this quantitative systematic review investigates the relationship between severity of a large-scale crisis outcome and attributions of blame toward relevant entities. moderators of interest include the attribution term used with participants (e.g., blame, responsibility), the type of crisis event, and the entity presented as at fault. overall, a small but significant positive relationship is identified in the majority of studies between severity of a large-scale crisis outcome and attributions of blame. results suggest that while crisis type and entity to blame are moderators, the attribution term(s) used with participants plays a less significant role. implications and future directions are considered. 8. title: learning from the failure of autonomous and intelligent systems: accidents, safety, and sociotechnical sources of risk authors: carl macrae abstract: efforts to develop autonomous and intelligent systems (ais) have exploded across a range of settings in recent years, from self-driving cars to medical diagnostic chatbots. these have the potential to bring enormous benefits to society but also have the potential to introduce new�or amplify existing�risks. as these emerging technologies become more widespread, one of the most critical risk management challenges is to ensure that failures of ais can be rigorously analyzed and understood so that the safety of these systems can be effectively governed and improved. ais are necessarily developed and deployed within complex human, social, and organizational systems, but to date there has been little systematic examination of the sociotechnical sources of risk and failure in ais. accordingly, this article develops a conceptual framework that characterizes key sociotechnical sources of risk in ais by reanalyzing one of the most publicly reported failures to date: the 2018 fatal crash of uber's self-driving car. publicly available investigative reports were systematically analyzed using constant comparative analysis to identify key sources and patterns of sociotechnical risk. five fundamental domains of sociotechnical risk were conceptualized�structural, organizational, technological, epistemic, and cultural�each indicated by particular patterns of sociotechnical failure. the resulting sotec framework of sociotechnical risk in ais extends existing theories of risk in complex systems and highlights important practical and theoretical implications for managing risk and developing infrastructures of learning in ais. 9. title: disaster risk planning with fuzzy goal programming authors: terry r. rakes, jason k. deane, loren p. rees, david m. goldberg abstract: the uncertainty in the timing and severity of disaster events makes the long-term planning of mitigation and recovery actions both critical and extremely difficult. planners often use expected values for hazard occurrences, leaving communities vulnerable to worse-than-usual and even so-called �black swan� events. this research models disasters in terms of their best-case, most-likely, and worst-case damage estimates. these values are then embedded in a fuzzy goal programming model to provide community planners and stakeholders with the ability to strategize for any range of events from best-case to worst-case by adjusting goal weights. examples are given illustrating the modeling approach, and an analysis is provided to illustrate how planners might use the model as a planning tool. 10. title: agent-based modeling to evaluate human�environment interactions in community flood risk mitigation authors: yu han, liang mao, xuqi chen, wei zhai, zhong-ren peng, pallab mozumder abstract: this article deals with household-level flood risk mitigation. we present an agent-based modeling framework to simulate the mechanism of natural hazard and human interactions, to allow evaluation of community flood risk, and to predict various adaptation outcomes. the framework considers each household as an autonomous, yet socially connected, agent. a beta�bernoulli bayesian learning model is first applied to measure changes of agents� risk perceptions in response to stochastic storm surges. then the risk appraisal behaviors of agents, as a function of willingness-to-pay for flood insurance, are measured. using miami-dade county, florida as a case study, we simulated four scenarios to evaluate the outcomes of alternative adaptation strategies. results show that community damage decreases significantly after a few years when agents become cognizant of flood risks. compared to insurance policies with pre-flood insurance rate maps subsidies, risk-based insurance policies are more effective in promoting community resilience, but it will decrease motivations to purchase flood insurance, especially for households outside of high-risk areas. we evaluated vital model parameters using a local sensitivity analysis. simulation results demonstrate the importance of an integrated adaptation strategy in community flood risk management. 11. title: on some foundational issues concerning the relationship between risk and resilience authors: terje aven abstract: �risk� and �resilience� are both terms with a long history, but how they are related and should be related are strongly debated. this article discusses the appropriateness of a perspective advocated by an active �resilience school� that sees risk as a change in critical system functionality, as a result of an event (disturbance, hazard, threat, accident), but not covering the recovery from the event. from this perspective, two theses are examined: risk and resilience are disjunct concepts, and risk is an aspect of resilience. through the use of several examples and reasoning, the article shows that this perspective challenges daily-life uses of the risk term, common practices of risk assessments and risk management, as well as contemporary risk science. a fundamental problem with the perspective is that system recovery is also an important aspect of risk, not only of resilience. risk and resilience analysis and management implications of the conceptual analysis are also discussed. 12. title: a quantitative risk estimation platform for indoor aerosol transmission of covid-19 authors: hooman parhizkar, kevin g. van den wymelenberg, charles n. haas, richard l. corsi abstract: aerosol transmission has played a significant role in the transmission of covid-19 disease worldwide. we developed a covid-19 aerosol transmission risk estimation model to better understand how key parameters associated with indoor spaces and infector emissions affect inhaled deposited dose of aerosol particles that convey the sars-cov-2 virus. the model calculates the concentration of size-resolved, virus-laden aerosol particles in well-mixed indoor air challenged by emissions from an index case(s). the model uses a mechanistic approach, accounting for particle emission dynamics, particle deposition to indoor surfaces, ventilation rate, and single-zone filtration. the novelty of this model relates to the concept of  inhaled & deposited dose in the respiratory system of receptors linked to a dose response curve for human coronavirus hcov-229e. we estimated the volume of inhaled & deposited dose of particles in the 0.5 4 �m range expressed in picoliters (pl) in a well-documented covid-19 outbreak in restaurant x in guangzhou china. we anchored the attack rate with the dose response curve of hcov-229e which provides a preliminary estimate of the average sars-cov-2 dose per person, expressed in plaque forming units (pfus). for a reasonable emission scenario, we estimate approximately three pfu per pl deposited, yielding roughly 10 pfus deposited in the respiratory system of those infected in restaurant x. to explore the model's utility, we tested it with four covid-19 outbreaks. the risk estimates from the model fit reasonably well with the reported number of confirmed cases given available metadata from the outbreaks and uncertainties associated with model assumptions. 13. title: modeling of farmers� vegetable safety production based on identification of key risk factors from beijing, china authors: zhengqing yin, bo li, dongyue gu, jian huang, lingxian zhang abstract: food safety emphasizes risk control in the production process, and has attracted much attention from food regulators and consumers in recent years. the objectives of this study were to conduct early key risk factors identification and risk modeling for vegetable safety production. to achieve these objectives, this article quantitatively identified the key direct and indirect risk factors in vegetable safety production through questionnaire surveys and a multivariate linear model, and modeled the effects of key risk factors affecting vegetable safety production based on the catastrophe progression method. based on 973 valid farmers� questionnaires from beijing, china, the results showed that key direct risk factors are production violation, farmland biological control, pesticide and fertilizer use criteria, and agricultural consumable handling; key indirect risk factors included cooperative participation, planting years, prohibited pesticide knowledge, production recording, and product type. through the empirical analysis, it can be seen that there are regional differences in the production risk of vegetable farmers in beijing. the production risks of changping, huairou, and shunyi are the most serious; from a city-wide perspective, the risk of farmland biological control is greatest, followed by risk aversion ability. the findings of this research have important implications for safe vegetable production and farmers� production risk control. 14. title: risk-based decision making definition: a scoping review of food, agricultural, environmental, and medical literature authors: kara m. morgan, ashley crawford, barbara b. kowalcyk abstract: risk-based decision making (rbdm) is a term that is used frequently as an aspirational goal in many fields, including health, engineering, environmental science, regulatory and, more recently, food safety. when rbdm is used in the literature, many different types of criteria are used to characterize a decision process as being �risk-based.� like the parable about the blind men and the elephant, everyone is confident they know what rbdm means even though there is no universal definition. the use of rbdm is gaining wide acceptance and implies a level of rigor and focus that many decisionmakers and stakeholders are interested in adopting. however, without one clear definition, there are questions about what a rbdm approach really means. this study summarizes peer-reviewed and gray literature that uses the term �rbdm� from the last 50 years in the agricultural, environmental, and medical areas. the criteria discussed were identified and organized into themes. a foundational definition is proposed to represent the most fundamental use of rbdm in the literature, and three themes covering the additional concepts presented in some of the literature were identified and added as themes within the definition. results from this research will inform practitioners interested in following the principles of rbdm, and will help guide researchers who are interested in advancing this approach. the most immediate use will be to guide the development of a roadmap for a risk-based food safety system for low- and middle-income countries and to aid the global food safety community in moving toward rbdm.   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