1,720,968 research outputs found
Incertitude, causalité et décision : Le cas des risques sociaux et du risque nucléaire en particulier
No full textProbability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area.When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequencesand are causally interconnected. The model provides a causal interpretation of Savage’s conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem’s causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a common understanding of the precautionary principle.La probabilité et la causalité sont deux outils indispensables à la prise en compte des situations de risque social. Lesrelations causales sont le fondement des représentations à partir desquelles on peut évaluer le risque et concevoirdes actions de prévention, de mitigation ou d’indemnisation. La probabilité permet de quantifier cette évaluation et de calibrer ces actions. Dès lors, il semble non seulement naturel, mais nécessaire d’expliciter la place de la causalité et de la probabilité dans la définition d’un problème de décision en situation de risque social. C’est l’objet de cette thèse.Un tour d’horizon de la terminologie du risque et des logiques d’intervention publique dans différentes catégories de risque social nous permettent de mieux comprendre la notion et les problèmes soulevés par sa représentation. Nous approfondissons notre analyse dans le cas de la sûreté nucléaire, en examinant en détail les méthodes et doctrinesdéveloppées dans ce domaine et leur évolution au cours du temps, ce qui nous conduit à formuler différentesobservations au sujet des évaluations de risque et de sûreté.En généralisant la notion d’intervention dans les réseaux bayésiens, nous développons une forme de réseau bayésien causal qui répond à nos besoins. Nous parvenons, par son biais, à une définition du risque qui semble pertinente pour un grand nombre de situations. Nous proposons ensuite des applications simples de ce modèle à certains aspects de l’accident de Fukushima et d’autres problèmes de sûreté nucléaire. Outre certains enseignements spécifiques, ceci nous amène à souligner la nécessité d’une démarche systématique d’identification des incertitudes dans ce domaine.Étendu en direction de la théorie de la décision, notre outil débouche naturellement sur un modèle de décision dynamique dans lequel les actes causent les conséquences et sont causalement liés entre eux. Il apporte en outre une interprétation causale au cadre conceptuel de Savage et permet d’en résoudre certains paradoxes et clarifier certains aspects. Il conduit enfin à envisager la question de l’ambigüité comme incertitude concernant la structure causale d’un problème de décision, ce qui correspond à une vision courante du principe de précaution
Uncertainty, causality and decision : The case of social risks and nuclear risk in particular
No full textLa probabilité et la causalité sont deux outils indispensables à la prise en compte des situations de risque social. Lesrelations causales sont le fondement des représentations à partir desquelles on peut évaluer le risque et concevoirdes actions de prévention, de mitigation ou d’indemnisation. La probabilité permet de quantifier cette évaluation et de calibrer ces actions. Dès lors, il semble non seulement naturel, mais nécessaire d’expliciter la place de la causalité et de la probabilité dans la définition d’un problème de décision en situation de risque social. C’est l’objet de cette thèse.Un tour d’horizon de la terminologie du risque et des logiques d’intervention publique dans différentes catégories de risque social nous permettent de mieux comprendre la notion et les problèmes soulevés par sa représentation. Nous approfondissons notre analyse dans le cas de la sûreté nucléaire, en examinant en détail les méthodes et doctrinesdéveloppées dans ce domaine et leur évolution au cours du temps, ce qui nous conduit à formuler différentesobservations au sujet des évaluations de risque et de sûreté.En généralisant la notion d’intervention dans les réseaux bayésiens, nous développons une forme de réseau bayésien causal qui répond à nos besoins. Nous parvenons, par son biais, à une définition du risque qui semble pertinente pour un grand nombre de situations. Nous proposons ensuite des applications simples de ce modèle à certains aspects de l’accident de Fukushima et d’autres problèmes de sûreté nucléaire. Outre certains enseignements spécifiques, ceci nous amène à souligner la nécessité d’une démarche systématique d’identification des incertitudes dans ce domaine.Étendu en direction de la théorie de la décision, notre outil débouche naturellement sur un modèle de décision dynamique dans lequel les actes causent les conséquences et sont causalement liés entre eux. Il apporte en outre une interprétation causale au cadre conceptuel de Savage et permet d’en résoudre certains paradoxes et clarifier certains aspects. Il conduit enfin à envisager la question de l’ambigüité comme incertitude concernant la structure causale d’un problème de décision, ce qui correspond à une vision courante du principe de précaution.Probability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area.When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequencesand are causally interconnected. The model provides a causal interpretation of Savage’s conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem’s causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a common understanding of the precautionary principle
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Comparison of Risk Management Policies in OECD Countries
Get PDFThe Organisation for Economic Cooperation and Development started in 2003 a series of country studies and reviews aimed at assisting its Member countries in evaluating the effectiveness of their risk management systems, notably in terms of their ability to contend with large-scale risks of the future, and at offering them guidance in making the requisite improvements. The project, entitled the OECD Futures Project on Risk Management Policies, focuses on the consistency of risk management policies and on their ability to deal with the challenges, present and future, created by the evolution of the risk landscape.
The Project gathers eight Member countries from Europe, Asia and North America, and covers three risk clusters: natural disasters (floods, earthquakes), critical infrastructure protection (information systems and networks, transport systems), and health and safety risks for specific segments of the population (older people, ethnic minorities). Diverse risk management issues and contexts falling within these clusters are analysed following a common methodology.
Risk management is a complex process involving many different phases, from the evaluation of threats and the elaboration of protection strategies to the settling of liability issues and investigations after an accident or a disaster happens. Failure to consider risk management in its entirety can lead to some important linkages between these activities being overlooked, thereby undermining the overall effectiveness of policy. To address the complexity of risk management issues, the methodology used in the project considers risk management as a multi-layered system encompassing all actors, institutions and rules performing one of the following functions with regard to a specific risk: assessment; policy decision-making; framework conditions; protection; alert and early warning; rescue; recovery enhancement; and experience feedback and organisational change.
This series of issue-oriented evaluations of risk management systems is to be completed by 2007. It is expected to provide the material for a cross-sectoral analysis of risk management policies in the reviewed countries, and to lay the foundations of a cross-country toolkit of risk management.
The keynote lecture will discuss some of the findings of the overviews and evaluations of risk management systems performed in the context of the OECD Project, and use these as a basis to shed new light on some classical issues in risk management, such as risk acceptability, government crisis management, the prevention vs response tradeoff, and public/private complementarity
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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