Relevant bibliographies by topics / Risk representation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Risk representation'

Author: Grafiati
Published: 9 November 2024

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Journal articles on the topic "Risk representation"

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Kountzakis, Christos E., and Damiano Rossello. "Risk Measures’ Duality on Ordered Linear Spaces." Mathematics 12, no. 8 (April 12, 2024): 1165. http://dx.doi.org/10.3390/math12081165.

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The aim of this paper is to provide a dual representation of convex and coherent risk measures in partially ordered linear spaces with respect to the algebraic dual space. An algebraic robust representation is deduced by weak separation of convex sets by functionals, which are assumed to be only linear; thus, our framework does not require any topological structure of the underlying spaces, and our robust representations are found without any continuity requirement for the risk measures. We also use such extensions to the representation of acceptability indices.
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Chepurnaya, А. N. "Cardiomyopathy. Risk factors. Modern representation." Clinical Medicine (Russian Journal) 99, no. 9-10 (January 26, 2022): 501–8. http://dx.doi.org/10.30629/0023-2149-2021-99-9-10-501-508.

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The article is a review of the literature, which deals with the classifi cation, etiology, pathogenesis and risk factors of cardiomyopathies, analyzes the results of diagnostics with the use of modern technologies. The presence of cardiomyopathy always means a diffi cult life prognosis in patients. It determines the social signifi cance of the problem connected with this pathology, which is the cause of disability and mortality of most active working age patients.
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Harvard, Stephanie, and Eric Winsberg. "The Epistemic Risk in Representation." Kennedy Institute of Ethics Journal 32, no. 1 (March 2022): 1–31. http://dx.doi.org/10.1353/ken.2022.0001.

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Watson, Karli K. "Evolution, Risk, and Neural Representation." Annals of the New York Academy of Sciences 1128, no. 1 (April 2008): 8–12. http://dx.doi.org/10.1196/annals.1399.002.

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Kleinhesselink, Randall R., and Eugene A. Rosa. "Cognitive Representation of Risk Perceptions." Journal of Cross-Cultural Psychology 22, no. 1 (March 1991): 11–28. http://dx.doi.org/10.1177/0022022191221004.

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TSUCHIDA, Shoji. "Risk perception and Linguistic Representation." Proceedings of the National Symposium on Power and Energy Systems 2011.16 (2011): A3—A4. http://dx.doi.org/10.1299/jsmepes.2011.16.a3.

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Amarante, Massimiliano. "A representation of risk measures." Decisions in Economics and Finance 39, no. 1 (January 28, 2016): 95–103. http://dx.doi.org/10.1007/s10203-016-0170-8.

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Roland-Lévy, Christine, Ruxanda Kmiec, and Jérémy Lemoine. "How is the economic crisis socially assessed?" Social Science Information 55, no. 2 (February 8, 2016): 235–54. http://dx.doi.org/10.1177/0539018416629228.

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Based on the Social Representation Theory, the purpose of this article is to explore how lay-people consider both the economic crisis and risk, and to link these social representations to behavior. The article offers an original approach with the articulation of two studies about the social construction of risk and crises. It also contributes to the development of research methods for studying the connections between representations and practical implications. Based on this, the impact of the social representation of the crisis on the perceived ability to act is approached. The first study focuses on free-association tasks, with two distinct target terms: ‘risk’ and ‘crisis’. The structural approach, with a prototypical analysis, allowed the identification of two different representations: (1) for risk, ‘danger’ is the central element; (2) for crisis, ‘economy’ and ‘money’ constitute the main components of the representation. The second study investigates the links between the two previously detected structures and their relations with the perceived ability to act in a financial crisis context. Some aspects of social knowledge were found to have an impact on perceived ability to act.
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Schilling, Katja, Daniel Bauer, Marcus C. Christiansen, and Alexander Kling. "Decomposing Dynamic Risks into Risk Components." Management Science 66, no. 12 (December 2020): 5738–56. http://dx.doi.org/10.1287/mnsc.2019.3522.

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The decomposition of dynamic risks a company faces into components associated with various sources of risk, such as financial risks, aggregate economic risks, or industry-specific risk drivers, is of significant relevance in view of risk management and product design, particularly in (life) insurance. Nevertheless, although several decomposition approaches have been proposed, no systematic analysis is available. This paper closes this gap in literature by introducing properties for meaningful risk decompositions and demonstrating that proposed approaches violate at least one of these properties. As an alternative, we propose a novel martingale representation theorem (MRT) decomposition that relies on martingale representation and show that it satisfies all of the properties. We discuss its calculation and present detailed examples illustrating its applicability. This paper was accepted by Baris Ata, stochastic models and simulation.
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Wolford, Jackson. "Finding Words: Risk and Requirements in Theological Ethnographic Writing." Ecclesial Practices 11, no. 1 (August 14, 2024): 64–82. http://dx.doi.org/10.1163/22144417-bja10059.

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Abstract Scholars have written extensively on theological ethnographic research. Comparatively little has been written about theological ethnographic representations. Despite influential efforts since 2011 to move methods of theological ethnographic research toward an incarnate mode, the genres of theological ethnographic representation have not similarly advanced. This article argues: 1) That limiting theological ethnographic representations to the genre of the social-scientific case study or treatise risks replicating the analytical violence ethnography was designed to fight against; 2) That if we write in such a way that an abstract such as this one conveys the fullness of our written representation, we have failed to fulfill the obligations of the ethnographic task. Ethnography ought to be non-abstractable; this abstract should fall short. It then proposes two necessary qualities for theological ethnographic writing: 1) Writing in ways that needs to be read; 2) Writing in ways that can be read. I then proceed to get emotional.
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Dissertations / Theses on the topic "Risk representation"

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Drapeau, Samuel. "Risk preferences and their robust representation." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2010. http://dx.doi.org/10.18452/16135.

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Ziel dieser Dissertation ist es, den Begriff des Risikos unter den Aspekten seiner Quantifizierung durch robuste Darstellungen zu untersuchen. In einem ersten Teil wird Risiko anhand Kontext-Invarianter Merkmale betrachtet: Diversifizierung und Monotonie. Wir führen die drei Schlüsselkonzepte, Risikoordnung, Risikomaß und Risikoakzeptanzfamilen ein, und studieren deren eins-zu-eins Beziehung. Unser Hauptresultat stellt eine eindeutige duale robuste Darstellung jedes unterhalbstetigen Risikomaßes auf topologischen Vektorräumen her. Wir zeigen auch automatische Stetigkeitsergebnisse und robuste Darstellungen für Risikomaße auf diversen Arten von konvexen Mengen. Diese Herangehensweise lässt bei der Wahl der konvexen Menge viel Spielraum, und erlaubt damit eine Vielfalt von Interpretationen von Risiko: Modellrisiko im Falle von Zufallsvariablen, Verteilungsrisiko im Falle von Lotterien, Abdiskontierungsrisiko im Falle von Konsumströmen... Diverse Beispiele sind dann in diesen verschiedenen Situationen explizit berechnet (Sicherheitsäquivalent, ökonomischer Risikoindex, VaR für Lotterien, "variational preferences"...). Im zweiten Teil, betrachten wir Präferenzordnungen, die möglicherweise zusätzliche Informationen benötigen, um ausgedrückt zu werden. Hierzu führen wir einen axiomatischen Rahmen in Form von bedingten Präferenzordungen ein, die lokal mit der Information kompatibel sind. Dies erlaubt die Konstruktion einer bedingten numerischen Darstellung. Wir erhalten eine bedingte Variante der von Neumann und Morgenstern Darstellung für messbare stochastische Kerne und erweitern dieses Ergebnis zur einer bedingten Version der "variational preferences". Abschließend, klären wir das Zusammenpiel zwischen Modellrisiko und Verteilungsrisiko auf der axiomatischen Ebene.
The goal of this thesis is the conceptual study of risk and its quantification via robust representations. We concentrate in a first part on context invariant features related to this notion: diversification and monotonicity. We introduce and study the general properties of three key concepts, risk order, risk measure and risk acceptance family and their one-to-one relations. Our main result is a uniquely characterized dual robust representation of lower semicontinuous risk orders on topological vector space. We also provide automatic continuity and robust representation results on specific convex sets. This approach allows multiple interpretation of risk depending on the setting: model risk in the case of random variables, distributional risk in the case of lotteries, discounting risk in the case of consumption streams... Various explicit computations in those different settings are then treated (economic index of riskiness, certainty equivalent, VaR on lotteries, variational preferences...). In the second part, we consider preferences which might require additional information in order to be expressed. We provide a mathematical framework for this idea in terms of preorders, called conditional preference orders, which are locally compatible with the available information. This allows us to construct conditional numerical representations of conditional preferences. We obtain a conditional version of the von Neumann and Morgenstern representation for measurable stochastic kernels and extend then to a conditional version of the variational preferences. We finally clarify the interplay between model risk and distributional risk on the axiomatic level.
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Ghose, Rana Janak. "Regulating GMOs in India : pragmatism, politics, representation, and risk." Thesis, University of Sussex, 2011. http://sro.sussex.ac.uk/id/eprint/7579/.

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At the core of any effort by a nation state to regulate new technologies for public release is an implicit navigation of uncertainty. The case of Bt cotton in India presents a very timely and pragmatic example of how nation states grapple with uncertainty in a regulatory context. While much attention has been given to how government actors form regulation, far less is given to how actors outside of the government spheres act as catalysts for regulatory reform. In practice, it is often these parties that drive regulation as a process. The question is how. This paper outlines the findings of fieldwork conducted in India between March 2007 and July 2009 in addressing this central question: what does regulation really mean in a context where new technologies burdened with uncertain consequences are introduced? How do preferences, decisions, and regulatory norms adapt to this introduction based on the interactions of a multitude of parties acting on multiple framings of understanding what risk means? The conclusion is that regulation – in the context of Bt cotton in India - is far from a set of government policies derived from scientific measures of risk assessment. Civil society, firms, and farmers themselves all have tremendous influence on how a nation state navigates uncertainty in a regulatory context. It is a process forged on risk interfaces, where constructions of risk both complement and oppose one another. The actors involved enter these spaces, invited or otherwise. What the government may have initially imagined as ‘regulation' is subject to multiple technical, economic, and political framings of risk from each actor. As a result, regulation is a coevolutionary, co-constructed process. This process of negotiating these spaces is what regulation really means.
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Waldron, Cherry-Ann. "Cardiovascular risk prediction : how useful are web-based tools and do risk representation formats matter?" Thesis, Cardiff University, 2011. http://orca.cf.ac.uk/55126/.

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Cardiovascular risk prediction tools are becoming increasing available on the web for people to use at home. However, research into the most effective ways of communicating cardiovascular risk has been limited. This thesis examined how well web-based cardiovascular risk prediction tools present cardiovascular risk and encourage risk reduction. Variation was found in both the quality of the risk communication and the number of features incorporated into the tools to facilitate decisions about lifestyle change and treatment. Additionally, past literature into the effectiveness of cardiovascular risk representation formats was systematically reviewed. This highlighted the need for more methodologically sound studies, using actual risk assessment rather than hypothetical risk scenarios. This thesis also described a four-armed web-based randomised controlled trial (RCT) conducted to examine the effects of different cardiovascular risk representation formats on patient-based outcomes. It comprised a cardiovascular risk formatter that presented risk in one of three formats: bar graph, pictogram and metonym (e.g. image depicting the seriousness of having a myocardial infarction). There were two control groups to examine the Hawthorne effect. In total, 903 respondents took part in the trial. The most successful recruitment methods were web-based, including staff electronic noticeboards and social networking sites. The RCT found that viewing cardiovascular risk significantly reduces negative emotions in the 'worried well', thus helping to correct inaccurate risk perceptions. There were no main effects of risk representation formats, suggesting that the way risk is presented had little influence on the population that were recruited, in terms of motivating behaviour change, facilitating understanding of risk information or altering emotion. However, a possible type II error occurred as the sample was unrepresentative, highly educated and biased towards those of low cardiovascular risk. Further research is needed to reach target audiences and engage those who would benefit the most from using risk assessment tools.
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Polley, Jason S. "Acts of justice : risk and representation in contemporary American fiction." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102824.

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Spectacles of justice preoccupy contemporary American culture. Legal culture---including the Watergate trials, the Lewinsky scandal, and OJ Simpson's trial for alleged murder---assumes a central place in the American imaginary. Configurations of the law are not limited to media reportage and televised docudramas. Nor are arbitrations confined to law faculties and the spaces of formal courts. Working through depictions of due process in different ways and in different zones, contemporary American writers point up the prevalence of legality in everyday life. Whether on college campuses, in TV studios and suburban homes, or at theatres and racetracks, justice mediates interpersonal relations. Personal narratives proliferate as modes of self-justification. Everyone has a right to represent her side of a story. As interpretations of reality, however, none of these stories can claim absolute justness. No one has a monopoly on the law or victimhood.
This dissertation inspects how Jonathan Franzen, Don DeLillo, and Jane Smiley present the inconsistencies of the law. These American novelists emplot global escapes into their work as a means to inform notions of liberty and jurisprudence. For these writers, freedom requires the recognition of contradictory---and unanticipated---narratives. "Justice Theory" emerges where media, gambling, performance, and suburban studies intersect with ethics, globalism, and narratology. In Franzen's novel The Corrections and essay collection How to Be Alone, self-validation requires the appreciation of the stories of others. In DeLillo's later works, particularly the plays The Day Room and Valparaiso, justice materializes in terms of isolation and the will to alter personal stories. For Smiley, as construed in her long novels The Greenlanders and Horse Heaven, dynamic responsive actions attend risky, unpredictable encounters in competitive milieus like the racetrack. These authors reveal that executions of justice and the perpetration of injustice involve varied consequences. The law is not only about punishment and recompense. Rather, legality directs the consequences of its applications toward the ideal of justice, which evolves alongside the subjects that it serves and the stories that they relate.
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Morrier, Michael Joseph. "Disproportionate Representation of Preschool-Aged Children with Disabilities." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/epse_diss/48.

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Historically, students from ethnically diverse backgrounds in grades K-12 have been over-represented in special education, yet little research on disproportionate representation has been conducted with preschool-aged children. This study examined if 72,525 preschool-aged children with disabilities from ethnically diverse backgrounds were disproportionately represented in special education within and across five southern states. Data were gathered from the 2006 December 1st Child Count reported by each State Department of Education to the U.S. Department of Education. Chosen states offered state-funded pre-kindergarten programs, which should have provided equal opportunities for inclusion across states. Analyses compared children with disabilities for disproportionate representation across state of residence, across special education eligibilities, across educational placements, and amount of inclusion provided. Data were analyzed for child and placement characteristics. Due to data suppression by individual states, analyses were conducted using children from Black and White backgrounds, and children from Hispanic backgrounds were used when reported by individual states. Child characteristics considered included the child’s: (a) type of disability eligibility category, (b) age, and (c) ethnicity. Placement characteristics included: (a) type of educational placement, (b) state in which child resided, and (c) amount of inclusion received. Indices of disproportionate representation were calculated using: (a) composition index, (b) risk index, (c) odds ratio, and (d) relative risk ratio. A 3 x 5 ANOVA was used to calculate placement differences between states. Factorial analysis was used to calculate determinants of placement status for preschool-aged children with disabilities. Results revealed disproportionate representation does occur at the preschool level, although between state variability was great, and patterns differed from the K-12 literature. Children from American Indian backgrounds were over-represented due to high proportions in states of Alabama and North Carolina, while children from Asian and Hispanic backgrounds were under-represented. Children from Black and White backgrounds were represented in special education at expected rates. The most common eligibility categories were speech/language impairments and developmental delay. Placement results revealed over-representation for White preschoolers and males, although type of state-funded pre-k program was a non-significant factor. Inclusion analyses favored Whites and males. Child demographic factors explained the majority of variability in inclusion status.
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Ghassemi, Marzyeh. "Representation learning in multi-dimensional clinical timeseries for risk and event prediction." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112389.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 99-108).
There are major practical and technical barriers to understanding human health, and therefore a need for methods that thrive on large, complex, noisy data. In this work, we present machine learning methods that distill large amounts of heterogeneous health data into latent state representations. These representations are then used to estimate risks of poor outcomes, and response to intervention in multivariate physiological signals. We evaluate the reduced latent representations by 1) establishing their predictive value in important clinical tasks and 2) showing that the latent space representations themselves provide useful insight into underlying systems. In particular, we focus on case studies that can provide evidence-based risk assessment and forecasting in settings with guidelines that have not traditionally been data-driven. In this thesis we evaluate several methods to create patient representations, and use these features to predict important outcomes. Representation learning can be thought of as a form of phenotype discovery, where we attempt to discover spaces in the new representation that are markers of important events. We argue that these latent representations are useful markers when they 1) create better prediction results on outcomes of interest, and 2) do not duplicate features that are currently known bio-markers. We present four case studies of learning representations, and evaluate the representations on real predictive tasks. First, we create forward-facing prediction models using baseline clinical features, and those from a Latent Dirichlet Allocation (LDA) model trained with clinical progress notes. We then evaluate the per-patient latent state membership to predict mortality in an intensive care setting as time moves forward. Second, we use non-parametric Multi-task Gaussian Process (MTGP) hyper-parameters as latent features to estimate correlations within and between signals in sparse, heterogeneous time series data. We evaluate the hyper-parameters for forecasting missing signals in traumatic brain injury patients, and predicting mortality in intensive care unit patients. Third, we train switching-state autoregressive models (SSAMs) to model the underlying states that emit patient vital signs over time. We evaluate the time-specific latent state distributions as features to predict vasopressor onset and weaning in intensive care unit patients. Finally, we use statistical and symbolic features extracted from wearable ambulatory accelerometers (ACC) mounted to the neck to classify patient pathology, and stratify patients' risk of voice misuse. We evaluate the utility of both statistically generated features and symbolic representations of glottal pulses towards patient classification.
by Marzyeh Ghassemi.
Ph. D.
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Aaron, Michele Suzanne. "Un/safe texts : 'madmen', masochists and the representation of self-endangerment." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323788.

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Chattopadhyay, Jacqueline. "Representation and Household Risk Exposure: Attention to Access and Quality in Domestic Policy." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10196.

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This project defines a concept, “attention to quality,” and proposes that legislative attention to quality is a dependent variable that political science can use to evaluate the content of representation the political system offers, specifically to trace a means by which politics may influence household exposure to financial risk and possibly income inequality. Upstream of regulation or other formal policy solutions, attention to quality is observable consideration of the possibility that a good poses risk, or fails to shield consumers from risk, due to features of its own design. The project studies congressional attention to quality for three privately-vended, middle-class goods with the capacity to impact household risk exposure: health insurance, home loans, and prescription drugs. It also examines attention to quality in risk-modulating pieces of the welfare-state, taking Medicare as an example. The project explicitly contrasts attention to quality with attention to access for each good. Second, based on original datasets, this project reports robust evidence that legislative attention to access exceeds legislative attention to quality for the privately vended goods, particularly insurance and loans. It finds the reverse true of welfare-state goods. In doing so, the project contributes new quantitative evidence to the emergent body of research in American politics on how political processes, as opposed to strictly the macro-economy, may influence household financial insecurity. Third, the project makes progress in uncovering the underpinnings of quality attention. It finds senator attention to quality linked to partisan considerations—particularly the other political party’s degree of dominance in quality talk—in ways that appear to depress quality attention for privately-vended goods but buoy it for welfare-state goods. Quality’s visibility to the public appears to heighten the degree to which legislators consider the other party’s degree of dominance in quality talk when deciding whether to give quality attention. These patterns occur against a backdrop of what appears to be electorally-minded access attention: incumbents attend to the access facet of privately-vended goods as reelection dates approach, while not exhibiting such behavior around the quality facet. These findings have implications for research on congressional agenda setting and representation.
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Lu, Danni. "Representation Learning Based Causal Inference in Observational Studies." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/102426.

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This dissertation investigates novel statistical approaches for causal effect estimation in observational settings, where controlled experimentation is infeasible and confounding is the main hurdle in estimating causal effect. As such, deconfounding constructs the main subject of this dissertation, that is (i) to restore the covariate balance between treatment groups and (ii) to attenuate spurious correlations in training data to derive valid causal conclusions that generalize. By incorporating ideas from representation learning, adversarial matching, generative causal estimation, and invariant risk modeling, this dissertation establishes a causal framework that balances the covariate distribution in latent representation space to yield individualized estimations, and further contributes novel perspectives on causal effect estimation based on invariance principles. The dissertation begins with a systematic review and examination of classical propensity score based balancing schemes for population-level causal effect estimation, presented in Chapter 2. Three causal estimands that target different foci in the population are considered: average treatment effect on the whole population (ATE), average treatment effect on the treated population (ATT), and average treatment effect on the overlap population (ATO). The procedure is demonstrated in a naturalistic driving study (NDS) to evaluate the causal effect of cellphone distraction on crash risk. While highlighting the importance of adopting causal perspectives in analyzing risk factors, discussions on the limitations in balance efficiency, robustness against high-dimensional data and complex interactions, and the need for individualization are provided to motivate subsequent developments. Chapter 3 presents a novel generative Bayesian causal estimation framework named Balancing Variational Neural Inference of Causal Effects (BV-NICE). Via appealing to the Robinson factorization and a latent Bayesian model, a novel variational bound on likelihood is derived, explicitly characterized by the causal effect and propensity score. Notably, by treating observed variables as noisy proxies of unmeasurable latent confounders, the variational posterior approximation is re-purposed as a stochastic feature encoder that fully acknowledges representation uncertainties. To resolve the imbalance in representations, BV-NICE enforces KL-regularization on the respective representation marginals using Fenchel mini-max learning, justified by a new generalization bound on the counterfactual prediction accuracy. The robustness and effectiveness of this framework are demonstrated through an extensive set of tests against competing solutions on semi-synthetic and real-world datasets. In recognition of the reliability issue when extending causal conclusions beyond training distributions, Chapter 4 argues ascertaining causal stability is the key and introduces a novel procedure called Risk Invariant Causal Estimation (RICE). By carefully re-examining the relationship between statistical invariance and causality, RICE cleverly leverages the observed data disparities to enable the identification of stable causal effects. Concretely, the causal inference objective is reformulated under the framework of invariant risk modeling (IRM), where a population-optimality penalty is enforced to filter out un-generalizable effects across heterogeneous populations. Importantly, RICE allows settings where counterfactual reasoning with unobserved confounding or biased sampling designs become feasible. The effectiveness of this new proposal is verified with respect to a variety of study designs on real and synthetic data. In summary, this dissertation presents a flexible causal inference framework that acknowledges the representation uncertainties and data heterogeneities. It enjoys three merits: improved balance to complex covariate interactions, enhanced robustness to unobservable latent confounders, and better generalizability to novel populations.
Doctor of Philosophy
Reasoning cause and effect is the innate ability of a human. While the drive to understand cause and effect is instinct, the rigorous reasoning process is usually trained through the observation of countless trials and failures. In this dissertation, we embark on a journey to explore various principles and novel statistical approaches for causal inference in observational studies. Throughout the dissertation, we focus on the causal effect estimation which answers questions like ``what if" and ``what could have happened". The causal effect of a treatment is measured by comparing the outcomes corresponding to different treatment levels of the same unit, e.g. ``what if the unit is treated instead of not treated?". The challenge lies in the fact that i) a unit only receives one treatment at a time and therefore it is impossible to directly compare outcomes of different treatment levels; ii) comparing the outcomes across different units may involve bias due to confounding as the treatment assignment potentially follows a systematic mechanism. Therefore, deconfounding constructs the main hurdle in estimating causal effects. This dissertation presents two parallel principles of deconfounding: i) balancing, i.e., comparing difference under similar conditions; ii) contrasting, i.e., extracting invariance under heterogeneous conditions. Chapter 2 and Chapter 3 explore causal effect through balancing, with the former systematically reviews a classical propensity score weighting approach in a conventional data setting and the latter presents a novel generative Bayesian framework named Balancing Variational Neural Inference of Causal Effects(BV-NICE) for high-dimensional, complex, and noisy observational data. It incorporates the advance deep learning techniques of representation learning, adversarial learning, and variational inference. The robustness and effectiveness of the proposed framework are demonstrated through an extensive set of experiments. Chapter 4 extracts causal effect through contrasting, emphasizing that ascertaining stability is the key of causality. A novel causal effect estimating procedure called Risk Invariant Causal Estimation(RICE) is proposed that leverages the observed data disparities to enable the identification of stable causal effects. The improved generalizability of RICE is demonstrated through synthetic data with different structures, compared with state-of-art models. In summary, this dissertation presents a flexible causal inference framework that acknowledges the data uncertainties and heterogeneities. By promoting two different aspects of causal principles and integrating advance deep learning techniques, the proposed framework shows improved balance for complex covariate interactions, enhanced robustness for unobservable latent confounders, and better generalizability for novel populations.
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Demers, Jean-Simon. "Racing Heroes and Grieving Widows: A Study of the Representation of Death in Motorsport." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38195.

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Gilles Villeneuve, Ayrton Senna, Greg Moore, Dale Earnhardt. Only four of a number of high-profile race car drivers to have lost their lives taking part in events at the highest levels of motorsport. The aim of the present study is to analyze the coverage of death in high-level motorsport in the printed sports news of La Presse and The Toronto Star in Canada for the 1982 to 2017 period inclusively. Mobilizing the existing literature on risk-taking, namely Lyng’s concept of edgework, as well as Hall’s work on representation, a thematic analysis of a sample of sports news articles (N=488) was conducted. Three main themes emerged from the analysis. The discussion surrounding motorsport fatalities revolved around the individual (the deceased driver), the social aspect of the death (primarily the family members left behind), and journalistic practices (how to cover death). In conclusion, the coverage of death in motorsport was found to be an instance where the athlete is heroized and sometimes revered even decades after their death. In this aspect, the figure of Gilles Villeneuve remains pivotal to motorsport discussions in Canada, even to this day. It also was found that sports journalists, through their coverage of deadly accidents, enact the traditional roles of the journalist in offering social criticism of their subject matter to their readers, and that motorsport drivers enact a highly specific type of masculinity when practicing their sport.
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Books on the topic "Risk representation"

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Dilla, William N. Information representation, scaling, and experience in inherent risk judgments. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1991.

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Wyn, Grant. Corporatism in Britain: Effective representation or democracy at risk?. [s.l.]: Social Studies Review, 1986.

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Stone, Walter J. Republic at risk: Self-interest in American politics. Pacific Grove, Calif: Brooks/Cole Pub. Co., 1990.

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J, Quinn D., and Great Britain. Health and Safety Executive., eds. Development of an intermediate societal risk methodology: An investigation of FN curve representation. Norwich: HSE Books, 2003.

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Aven, Terje. Uncertainty in risk assessment: The representation and treatment of uncertainties by probabilistic and non-probabilistic methods. Chichester, West Sussex, United Kingdom: Wiley, 2014.

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Richard, Zielinski, and Massachusetts Continuing Legal Education, Inc. (1982- ), eds. Avoiding malpractice claims for family lawyers: Managing professional risk while providing high-quality representation. [Boston, Mass.]: MCLE, 2006.

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Zhao, Yongmao. She hui dai yi de jue qi: Taiwan zheng zhi yu she hui de ping xing fa zhan = The rise of social representation : the parallel development of politics and society in Taiwan. Taibei Shi: Han Lu tu shu chu ban you xian gong si, 2018.

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Lynnette, Fallon, and Massachusetts Continuing Legal Education, Inc. (1982- ), eds. Representations and warranties: Allocating the risk in acquisition agreements. Boston, MA: MCLE, 1993.

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E, Klechefski George, Hoel Michael K, National Media Laboratory, and Library of Congress. Preservation Directorate., eds. Risk analysis study for a representative magnetic tape collection. Washington, DC: Library of Congress, Preservation Directorate, 1998.

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Thomas, Dohmen, ed. Individual risk attitudes: New evidence from a large, representative, experimentally-validated survey. Bonn, Germany: IZA, 2005.

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Book chapters on the topic "Risk representation"

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Zimmermann, Heinz. "Risk and Representation: The Limits of Risk Management." In Equity Markets in Transition, 429–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45848-9_16.

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Hatcher, Pascale. "Mining, Multilateral Safeguards, and Political Representation in Laos." In Regimes of Risk, 76–100. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137031327_4.

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Mendes, Emilia. "Effort and Risk Prediction for Healthcare Software Projects Delivered on the Web." In Practitioner's Knowledge Representation, 107–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54157-5_7.

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Croyle, Robert T., and John B. Jemmott. "Psychological Reactions to Risk Factor Testing." In Mental Representation in Health and Illness, 85–107. New York, NY: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4613-9074-9_5.

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Lambert, James H., and Priya Sarda. "Representation of Risk Scenarios via Euler Diagrams." In Probabilistic Safety Assessment and Management, 3148–52. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-410-4_504.

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Unali, Maurizio. "More History of Representation! Images Risk Homologation." In Proceedings of the 2nd International and Interdisciplinary Conference on Image and Imagination, 669–79. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41018-6_54.

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Mues, Christophe, Bart Baesens, Craig M. Files, and Jan Vanthienen. "Decision Diagrams in Machine Learning: An Empirical Study on Real-Life Credit-Risk Data." In Diagrammatic Representation and Inference, 395–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25931-2_49.

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Murphy, John. "Public Representation and the Legal Regulation of Assisted Conception in Britain." In Nature, Risk and Responsibility, 117–29. London: Palgrave Macmillan UK, 1999. http://dx.doi.org/10.1007/978-1-349-27241-9_8.

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Jones, Natalie, Mark O’Brien, and Thomas Ryan. "22. Representation of Future Generations in United Kingdom Policy-Making." In An Anthology of Global Risk, 613–40. Cambridge, UK: Open Book Publishers, 2024. http://dx.doi.org/10.11647/obp.0360.22.

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Concerned with the issues of intergenerational justice which arise from global existential risks, this chapter presents a solution-based approach by examining the options for representing future generations in our present policy making structures. Utilising a range of case studies, the authors put forth a series of lessons and recommendations that can be applied to UK policy-making, describing not only changes to be made at policy level, but also at an institutional level. The authors call for the monitoring of future legislation and its effect on future generations, and a more general awareness of intergenerational inequality issues.
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Tonn, Bruce E., Richard T. Goeltz, Cheryl B. Travis, and Raymond H. Phillippi. "Risk Communication and the Cognitive Representation of Uncertainty." In The Analysis, Communication, and Perception of Risk, 213–27. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2370-7_21.

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Conference papers on the topic "Risk representation"

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Xiao, Xuesu, Jan Dufek, and Robin Murphy. "Explicit Motion Risk Representation." In 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). IEEE, 2019. http://dx.doi.org/10.1109/ssrr.2019.8848960.

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Falcone, F., and M. Dolen. "Technical public representation for health risk assessments in a highly urbanized region." In Environmental Health Risk 2001. Southampton, UK: WIT Press, 2001. http://dx.doi.org/10.2495/ehr010231.

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Bai, Yang, Min Cao, Daming Gao, Ziqiang Cao, Chen Chen, Zhenfeng Fan, Liqiang Nie, and Min Zhang. "RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/62.

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Text-based person search aims to retrieve the specified person images given a textual description. The key to tackling such a challenging task is to learn powerful multi-modal representations. Towards this, we propose a Relation and Sensitivity aware representation learning method (RaSa), including two novel tasks: Relation-Aware learning (RA) and Sensitivity-Aware learning (SA). For one thing, existing methods cluster representations of all positive pairs without distinction and overlook the noise problem caused by the weak positive pairs where the text and the paired image have noise correspondences, thus leading to overfitting learning. RA offsets the overfitting risk by introducing a novel positive relation detection task (i.e., learning to distinguish strong and weak positive pairs). For another thing, learning invariant representation under data augmentation (i.e., being insensitive to some transformations) is a general practice for improving representation's robustness in existing methods. Beyond that, we encourage the representation to perceive the sensitive transformation by SA (i.e., learning to detect the replaced words), thus promoting the representation's robustness. Experiments demonstrate that RaSa outperforms existing state-of-the-art methods by 6.94%, 4.45% and 15.35% in terms of Rank@1 on CUHK-PEDES, ICFG-PEDES and RSTPReid datasets, respectively. Code is available at: https://github.com/Flame-Chasers/RaSa.
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Gladyshev, Maksim, Natasha Alechina, Mehdi Dastani, and Dragan Doder. "Group Responsibility for Exceeding Risk Threshold." In 20th International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/kr.2023/32.

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The need for tools and techniques to formally analyze and trace the responsibility for unsafe outcomes to decision-making actors is urgent. Existing formal approaches assume that the unsafe outcomes for which actors can be held responsible are actually realized. This paper considers a broader notion of responsibility where unsafe outcomes are not necessarily realized, but their probabilities are unacceptably high. We present a logic combining strategic, probabilistic and temporal primitives designed to express concepts such as the risk of an undesirable outcome and being responsible for exceeding a risk threshold. We demonstrate that the proposed logic is complete and decidable.
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Bojanić, Tamara, and Branislav Stevanov. "AN OVERVIEW OF RISK MODELING AND REPRESENTATION IN BUSINESS PROCESS MODELING LANGUAGES." In 19th International Scientific Conference on Industrial Systems. Faculty of Technical Sciences, 2023. http://dx.doi.org/10.24867/is-2023-t6.1-5_00441.

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Business process modeling is important because it allows us to clearly and unambiguously define business processes, to identify the company's operations. It provides formal knowledge about work performance, work standardization, process analysis, and risk detection, leading to process improvement and automation possibilities. This paper focuses on the BPMN (Business Process Modeling Notation) modeling language, which aims to facilitate understanding and usability for all business users, participants, analysts, and software engineers. Before creating the model, it is crucial to determine the modeling goal, as companies encounter unforeseen events that can impact business objectives. Timely identification and assessment of risks, along with consideration of their consequences, are essential to prevent adverse effects. BPMN allows comprehensive process mapping and real-time monitoring to aid in risk identification. By integrating risk management into the process model, proactive identification and mitigation of risks can be achieved, reducing the likelihood of risk occurrence. While BPMN 2.0 lacks risk management constructs, various authors offer suggestions that will be presented in this paper.
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Entekhabi, Dara, and Peter S. Eagleson. "The representation of landsurface-atmosphere interaction in atmospheric general circulation models." In The world at risk: Natural hazards and climate change. AIP, 1992. http://dx.doi.org/10.1063/1.43903.

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Zhang, Kejiang, Gopal Achari, and Cheryl Kluck. "Uncertainty Representation in Health Risk Assessment of Contaminated Sites." In GeoCongress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40972(311)116.

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Miller, Thomas, Miriam Sturdee, and Daniel Prince. "Exploring the Representation of Cyber-Risk Data Through Sketching." In 2023 IEEE Symposium on Visualization for Cyber Security (VizSec). IEEE, 2023. http://dx.doi.org/10.1109/vizsec60606.2023.00010.

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Qiu, Wei, Andy W. H. Khong, and Fun Siong Lim. "Enhanced Student-graph Representation for At-risk Student Detection." In 2024 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2024. http://dx.doi.org/10.1109/iscas58744.2024.10557981.

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Wu, Ta, Dongyang Sun, and Tianxiang Yu. "Knowledge representation method for spacecraft health status telemetry monitoring." In 2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2013. http://dx.doi.org/10.1109/qr2mse.2013.6625919.

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Reports on the topic "Risk representation"

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Lee, Michael Junho, Antoine Martin, and Robert M. Townsend. Zero Settlement Risk Token Systems. Federal Reserve Bank of New York, September 2024. http://dx.doi.org/10.59576/sr.1120.

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How might modern settlement systems with distributed ledger technology achieve zero settlement risk? We consider the design of settlement systems that satisfies two integral features: information-leakage proof and zero settlement risk. Legacy settlement systems partition private information but are vulnerable to settlement fails. A token system with dynamic ownership representation, or a dynamic ledger, can be designed to achieve both, as long as it employs a protocol that enforces two restrictions: programs must be immediately implemented and must involve transactions based on verifiable claims. We show how such a system can support various arrangements, including insurance, derivatives, collateralized loans, and securitization.
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Zio, Enrico, and Nicola Pedroni. Literature review of methods for representing uncertainty. Fondation pour une culture de sécurité industrielle, December 2013. http://dx.doi.org/10.57071/124ure.

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This document provides a critical review of different frameworks for uncertainty analysis, in a risk analysis context: classical probabilistic analysis, imprecise probability (interval analysis), probability bound analysis, evidence theory, and possibility theory. The driver of the critical analysis is the decision-making process and the need to feed it with representative information derived from the risk assessment, to robustly support the decision. Technical details of the different frameworks are exposed only to the extent necessary to analyze and judge how these contribute to the communication of risk and the representation of the associated uncertainties to decision-makers, in the typical settings of high-consequence risk analysis of complex systems with limited knowledge on their behaviour.
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Nalla, Vineetha, and Nihal Ranjit. Afterwards: Graphic Narratives of Disaster Risk and Recovery from India. Indian Institute for Human Settlements, 2022. http://dx.doi.org/10.24943/9788195648559.

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Afterwards is an anthology of visual narratives of disaster impacts and the process of recovery that follows. These stories were drawn from the testimonies of disaster-affected individuals, households, and communities documented between 2018-19 from the Indian states of Odisha, Tamil Nadu, and Kerala. They communicate challenges related to housing resettlement, loss of livelihoods, gender-based exclusion among others. At the heart of this anthology lies the idea of ‘representation’: how are those affected portrayed by the media, state actors, official documents; how are their needs represented and how do these portrayals impact the lives of those at risk and shape their recovery? Graphically illustrating these themes provides a platform to relay personal experiences of disaster risk and recovery.
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Zio, Enrico, and Nicola Pedroni. Uncertainty characterization in risk analysis for decision-making practice. Fondation pour une culture de sécurité industrielle, May 2012. http://dx.doi.org/10.57071/155chr.

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This document provides an overview of sources of uncertainty in probabilistic risk analysis. For each phase of the risk analysis process (system modeling, hazard identification, estimation of the probability and consequences of accident sequences, risk evaluation), the authors describe and classify the types of uncertainty that can arise. The document provides: a description of the risk assessment process, as used in hazardous industries such as nuclear power and offshore oil and gas extraction; a classification of sources of uncertainty (both epistemic and aleatory) and a description of techniques for uncertainty representation; a description of the different steps involved in a Probabilistic Risk Assessment (PRA) or Quantitative Risk Assessment (QRA), and an analysis of the types of uncertainty that can affect each of these steps; annexes giving an overview of a number of tools used during probabilistic risk assessment, including the HAZID technique, fault trees and event tree analysis.
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Nalla, Vineetha, Nihal Ranjit, Yashodara Udupa, Mythili Madhavan, Jasmitha Arvind, Garima Jain, and Teja Malladi. Afterwards – Graphic Narratives of Disaster Risk and Recovery from India (Volume Set). Indian Institute for Human Settlements, 2022. http://dx.doi.org/10.24943/9788195648573.

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Afterwards is an anthology of graphic narratives of disaster impacts and the process of recovery that follows. These stories were drawn from the testimonies of disaster-affected individuals, households, and communities documented from the Indian states of Odisha, Tamil Nadu, and Kerala. The book has been translated into the regional languages of these states – Odia, Tamil, and Malayalam. They communicate challenges related to housing resettlement, loss of livelihoods, and gender-based exclusion among others. At the heart of this anthology lies the idea of ‘representation’: how are disaster-affected people portrayed by the media, state actors, and official documents; how are their needs represented and how do these portrayals impact the lives of those at risk and shape their recovery?
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Bragge, Peter, Veronica Delafosse, Ngo Cong-Lem, Diki Tsering, and Breanna Wright. General practitioners raising and discussing sensitive health issues with patients. The Sax Institute, June 2023. http://dx.doi.org/10.57022/rseh3974.

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This Evidence Check was commissioned by the NSW Ministry of Health, as part of a project to improve how preventive, sensitive health issues are raised in general practice. The review looked at what is known about discussing sensitive preventive health issues from both patients and GPs perspectives and approaches and factors that have been shown to be effective. The identified evidence was generally of moderate to high methodological quality. General behaviour change approaches that are applicable to this challenge include creating non-judgemental environments that normalise sensitive health issues; simulation training; and public campaigns that reduce stigma and challenge unhelpful cultural norms. Lack of time in consultations was identified as a challenging issue. Significant system-level change would be required to extend standard consultation times; focusing on optimising workflows may therefore be more feasible. Addressing GP patient–gender mismatch through diverse GP representation may also be feasible in larger practices. The key theme identified was the use of prompting, screening or other structured tools by GPs. Collectively, these approaches have two main features. First, they are a way of approaching sensitive health conversations less directly, for example by focusing on underlying risk factors for sensitive health conditions such as obesity and mental illness rather than addressing the issues directly. Second, through either risk-factor or more general question prompts, these approaches take the onus away from GPs and patients to come up with a way of asking the question using their own words.
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Idris, Iffat. Conditions for Elections to Succeed in Reducing Conflict and Instability. Institute of Development Studies, July 2022. http://dx.doi.org/10.19088/k4d.2022.124.

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Post-conflict elections can pave the way for democratisation and peacebuilding, but can also lead to renewed conflict. Minimum conditions for ensuring that elections promote the former and reduce conflict and instability include: peace and demilitarisation; international involvement; not holding post-conflict elections too early; holding national and local elections separately – ideally, local before national; election systems (notably proportional representation) that distribute rather than concentrate power; independent, permanent and well-resourced election management bodies; and media that promote voter education, messaging by parties and candidates, and election transparency. However, it is important to stress that specific criteria needed for successful post-conflict elections will be context-dependent.Post-conflict elections have the potential to establish legitimate government and can pave the way for democratisation and sustained peace. However, because they determine the distribution of power, they can also trigger renewed conflict. The risk of this is exacerbated by the difficult circumstances in which post-conflict elections are typically held (e.g. damaged infrastructure, weak institutions). The challenge is how to achieve the potential benefits while avoiding the risks. What are the conditions or criteria needed to ensure that post-conflict elections do not lead to conflict and instability?This review looks at the conditions needed to ensure that post-conflict election reduce conflict and instability. It draws on a mixture of academic and grey literature. While there was substantial literature on the various criteria, notably international involvement and election administration, it was largely gender-blind, as well as disability-blind.
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Salter, R., Natàlia Garcia-Reyero, Alicia Ruvinsky, Maria Seale, and Edward Perkins. Adverse outcome pathways for engineered systems. Engineer Research and Development Center (U.S.), July 2023. http://dx.doi.org/10.21079/11681/47336.

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Companies and organizations around the world spend massive amounts of money each year to discover, predict, and remediate failures within engineered systems. These tasks require individuals with specialized knowledge in a variety of topics related to failure. This knowledge is often acquired through years of academic and on-the-job training centered around the review of scientific documentation such as books, reports, manuals, and peer-reviewed publications. The loss of this knowledge through employee attrition can be detrimental to a group as knowledge is often difficult to reacquire. The aggregation and representation of known failure mechanisms for engineered materials could aid in the sharing of knowledge, the acquisition of knowledge, and the discovery of failure causes, reducing the risk of failure. Thus, the current work proposes the Adverse Outcome Pathway for Engineered Systems (AOP-ES) framework, an extension of the Adverse Outcome Pathway used in toxicology. The AOP-ES is designed to document failure knowledge, enabling knowledge transfer and the prediction of failures of novel engineered materials based on the performance of similar materials. This paper introduces the AOP-ES framework and its key elements alongside the principles that govern the framework. An application of the framework is presented, and additional benefits are explored.
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Beal, Samuel, Matthew Bigl, and Charles Ramsey. Live-fire validation of command-detonation residues testing using an 81 mm IMX-104 munition. Engineer Research and Development Center (U.S.), April 2023. http://dx.doi.org/10.21079/11681/46913.

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Postdetonation energetic residues can have environmental impacts that present a risk to military training-range sustainment. As munitions with new explosive formulations are developed and fielded, quantitative methods for assessing their residues are needed. Command detonation (i.e., static firing) allows residue testing to occur early in the acquisition process; however, its representation of live-fire residue production is uncertain due to differences in the initiation mechanism and cartridge orientation. This study aims to validate residue testing by command detonation through statistical comparison of residue deposition rates between live fire and command detonation. Live-fire residues were collected from fourteen 81 mm IMX-104 mortar cartridges fired onto snow, and deposition rates were compared with previous command-detonation tests of the same munition. Average live-fire deposition rates were 8000 mg NTO (3-nitro-1,2,4-triazol-5-one), 60 mg DNAN (2,4-dinitroanisole), 20 mg RDX (1,3,5-trinitroperhydro-1,3,5-triazine), and 2 mg HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane) per cartridge. Compared to command detonation, live fire of the study munition produced significantly greater residues of NTO (p < 0.0001) and RDX (p = 0.01) but not DNAN (p = 0.067). Although absolute deposition rates of some IMX-104 compounds differed, command detonation was successful at predicting the order of magnitude of each IMX-104 compound for the studied 81 mm munition.
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Monasterolo, Irene, María J. Nieto, and Edo Schets. The good, the bad and the hot house world: conceptual underpinnings of the NGFS scenarios and suggestions for improvement. Madrid: Banco de España, February 2023. http://dx.doi.org/10.53479/29533.

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Climate mitigation scenarios are an essential tool for analyzing the macroeconomic and financial implications of climate change (physical risk), and how the transition to a low-carbon economy could unfold (transition risk). The Network for Greening the Financial System (NGFS) has co-developed a set of climate mitigation scenarios for climate financial risk assessment. Despite the important role that these scenarios play in climate stress tests, the understanding of their main characteristics and limitations is still poor. In this paper, we contribute to filling this gap by focusing on the following issues: comparison of the process-based Integrated Assessment Models (IAMs) used by the NGFS with alternative models; the role of Representative Concentration Pathways (RCPs) and Shared Socioeconomic Pathways (SSPs) in shaping the scenario narratives, and their shortcomings; the interpretation and sensitivities of carbon price pathways; and, comparison with other climate mitigation scenarios. We then draw lessons on how to increase the relevance of the NGFS scenarios. These include updating the SSP narratives; considering the potential trade-offs between different types of climate policies; assessing acute physical risks and their compounding; integrating physical risks within transition scenarios; and, taking into account the role of the financial sector and investors’ expectations.
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