Médecine sociate en 2013: quand la précarité précède la pauvrete [Social medicine: does it still make sense in 2013?].

Social medicine is a medicine that seeks to understand the impact of socio-economic conditions on human health and diseases in order to improve the health of a society and its individuals. In this field of medicine, determining the socio-economic status of individuals is generally not sufficient to explain and/or understand the underlying mechanisms leading to social inequalities in health. Other factors must be considered such as environmental, psychosocial, behavioral and biological factors that, together, can lead to more or less permanent damages to the health of the individuals in a society. In a time where considerable progresses have been made in the field of the biomedicine, does the practice of social medicine in a primary care setting still make sense?

Social Interaction Effects on Fertility: Intentions and Behaviors

The existing literature shows that social interactions in individuals' networks affect their reproductive attitudes and behaviors through three mechanisms: social influence, social learning, and social support. In this paper, we discuss to what extent the Theory of Planned Behavior (TPB), an individual based theorization of intentions and behavior used to model fertility, takes these social mechanisms into account. We argue that the TPB already integrates social influence and that it could easily accommodate the two other social network mechanisms. By doing so, the theory would be enriched in two respects. First, it will explain more completely how macro level changes eventually ends in micro level changes in behavioral intentions. Indeed, mechanisms of social influence may explain why changes in representations of parenthood and ideal family size can be slower than changes in socio-economic conditions and institutions. Social learning mechanisms should also be considered, since they are crucial to distinguish who adopts new behavioral beliefs and practices, when change at the macro level finally sinks in. Secondly, relationships are a capital of services that can complement institutional offering (informal child care) as well as a capital of knowledge which help individuals navigate in a complex institutional reality, providing a crucial element to explain heterogeneity in the successful realization of fertility intentions across individuals. We develop specific hypotheses concerning the effect of social interactions on fertility intentions and their realization to conclude with a critical review of the existing surveys suitable to test them and their limits.

Three essays in international finance

Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.

Médecine sociale en 2013 : quand la précarité précède la pauvreté [Social medicine : does it still make sense in 2013?]

Social medicine is a medicine that seeks to understand the impact of socio-economic conditions on human health and diseases in order to improve the health of a society and its individuals. In this field of medicine, determining the socio-economic status of individuals is generally not sufficient to explain and/or understand the underlying mechanisms leading to social inequalities in health. Other factors must be considered such as environmental, psychosocial, behavioral and biological factors that, together, can lead to more or less permanent damages to the health of the individuals in a society. In a time where considerable progresses have been made in the field of the biomedicine, does the practice of social medicine in a primary care setting still make sense? La médecine sociale est une médecine qui cherche à comprendre l'impact des conditions socio-économiques sur la santé humaine et les maladies, dans la perspective d'améliorer l'état de santé d'une société et de ses individus. Dans ce domaine, la détermination du statut socio-économique des individus ne suffit généralement pas à elle seule pour expliquer et comprendre les mécanismes qui sous-tendent les inégalités sociales de santé. D'autres facteurs doivent être pris en considération, tels que les facteurs environnementaux, psychosociaux, comportementaux et biologiques, facteurs qui peuvent conduire de manière synergique à des atteintes plus ou moins durables de l'état de santé des individus d'une société. A une époque où les connaissances, les compétences et les moyens à disposition en biomédecine ont fait des progrès considérables, la pratique de la médecine sociale en cabinet a-t-elle encore sa place en 2013?

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The chapter provides an account of the changing role played by active labour market policies (ALMPs) in Europe since the post-war years. Focusing on six countries (Sweden, Denmark, France, Germany, Italy, and the United Kingdom), it shows that the role of ALMPs is related to the broad economic situation. At times of rapid expansion and labour shortage, like the 1950s and 1960s, their key objective was to upskill the workforce. After the oil shocks of the 1970s, the raison d'être of ALMPs shifted from economic to social policy, and since the mid-1990s, we see the development of a new function, well captured by the notion of activation, which refers to the strengthening of work incentives and the removal of obstacles to employment, mostly for low-skilled people. The adequacy between economic context and policy is not always optimal, though. Like other ones, this policy domain suffers from inertia, with the result that the countries that have led the way in one period have more difficulty adapting to the economic conditions prevailing in the following one.

Contextual Effects on Hopelessness in the Second Half of the Life

Depression and suicidal ideation are tightly linked to the lack of hope in the future. Hopelessness begins with the occurrence of negative life events and develops through the perception that negative outcomes are stable and pervasive. Most of the research has investigated individual factors predicting hopelessness. However, other studies have shown that the social context may also play an important role: disadvantaged contexts exacerbate the feeling that future is unreachable and hopeless. In this study we investigate the role of shared emotions (emotional climates) on the sense of hopelessness during the second half of the life. Emotional climates have been defined as the emotional relationships constructed between members of a society and describe the quality of the environment within a particular community. We present results of multilevel analyses using data from the NCCR-LIVES769 project «Vulnerability and growth», the Swiss Household Panel and official statistics, that explore the relationship between characteristics of the Swiss cantons and hopelessness. Although hopelessness is mainly affected by individual factors as life events and personality, results show that canton socio-economic conditions and climates of optimism or pessimism have an effect on the individual perception of hopelessness. Individuals are more likely to feel hopeless after having experienced critical events (i.e., loss of the partner in the late life) in cantons with high rates of unemployment and with a high share of negative emotions. On the contrary, positive emotional climates play a protective role against hopelessness.

European Integration Without EU Membership : Models, Experiences, Perspectives

At the beginning of the 1990s, the concept of "European integration" could still be said to be fairly unambiguous. Nowadays, it has become plural and complex almost to the point of unintelligibility. This is due, of course, to the internal differentiation of EU membership, with several Member States pulling out of key integrative projects such as establishing an area without frontiers, the "Schengen" area, and a common currency. But this is also due to the differentiated extension of key integrative projects to European non-EU countries - Schengen is again a case in point. Such processes of "integration without membership", the focus of the present publication, are acquiring an ever-growing topicality both in the political arena and in academia. International relations between the EU and its neighbouring countries are crucial for both, and their development through new agreements features prominently on the continent's political agenda. Over and above this aspect, the dissemination of EU values and standards beyond the Union's borders raises a whole host of theoretical and methodological questions, unsettling in some cases traditional conceptions of the autonomy and separation of national legal orders. This publication brings together the papers presented at the Integration without EU Membership workshop held in May 2008 at the EUI (Max Weber Programme and Department of Law). It aims to compare different models and experiences of integration between the EU, on the one hand, and those European countries that do not currently have an accession perspective on the other hand. In delimiting the geographical scope of the inquiry, so as to scale it down to manageable proportions, the guiding principles have been to include both the "Eastern" and "Western" neighbours of the EU, and to examine both structured frameworks of cooperation, such as the European Neighbourhood Policy and the European Economic Area, and bilateral relations developing on a more ad hoc basis. These principles are reflected in the arrangement of the papers, which consider in turn the positions of Ukraine, Russia, Norway, and Switzerland in European integration - current standing, perspectives for evolution, consequences in terms of the EU-ization of their respective legal orders1. These subjects are examined from several perspectives. We had the privilege of receiving contributions from leading practitioners and scholars from the countries concerned, from EU highranking officials, from prominent specialists in EU external relations law, and from young and talented researchers. We wish to thank them all here for their invaluable insights. We are moreover deeply indebted to Marise Cremona (EUI, Law Department, EUI) for her inspiring advice and encouragement, as well as to Ramon Marimon, Karin Tilmans, Lotte Holm, Alyson Price and Susan Garvin (Max Weber Programme, EUI) for their unflinching support throughout this project. A word is perhaps needed on the propriety and usefulness of the research concept embodied in this publication. Does it make sense to compare the integration models and experiences of countries as different as Norway, Russia, Switzerland, and Ukraine? Needless to say, this list of four evokes a staggering diversity of political, social, cultural, and economic conditions, and at least as great a diversity of approaches to European integration. Still, we would argue that such diversity only makes comparisons more meaningful. Indeed, while the particularities and idiosyncratic elements of each "model" of integration are fully displayed in the present volume, common themes and preoccupations run through the pages of every contribution: the difficulty in conceptualizing the finalité and essence of integration, which is evident in the EU today but which is greatly amplified for non-EU countries; the asymmetries and tradeoffs between integration and autonomy that are inherent in any attempt to participate in European integration from outside; the alteration of deeply seated legal concepts, and concepts about the law, that are already observable in the most integrated of the non-EU countries concerned. These issues are not transient or coincidental: they are inextricably bound up with the integration of non-EU countries in the EU project. By publishing this collection, we make no claim to have dealt with them in an exhaustive, still less in a definitive manner. Our ambition is more modest: to highlight the relevance of these themes, to place them more firmly on the scientific agenda, and to provide a stimulating basis for future research and reflection.

Du retraité méritant au senior actif : genèse et transformations de la figure sociale de la vieillesse en Suisse

«Crise de l'assurance-vieillesse », «déséquilibre démographique», «vieillissement de la population », « faillite des systèmes de retraite », voilà des expressions qui occupent une place prépondérante dans tes discours portant sur l'avenir de la sécurité sociale aujourd'hui. Les autorités politiques suisses comme européennes font part de leur inquiétude face à la situation d'urgence que présenteraient les « sociétés vieillissantes ». En effet, alors que F assurance-vieillesse s'adressait initialement à une catégorie résiduelle de personnes qui parvenait à vivre plusieurs années au-delà de 65 ans, elle couvre maintenant près d'un cinquième de la population globale. Partant, les autorités fédérales appellent à une restriction des conditions d'accès à la rente de vieillesse. À première vue, les débats qui portent sur cette question dans l'arène politique relèvent de considérations essentiellement techniques liées aux conditions économiques de perpétuation de l'assurances-vieillesse. Il s'agit de modifier les règles d'accès à l'assurance ainsi que le montant des prestations afin d'assainir les caisses tout en faisant face à l'augmentation du nombre de retraités. Ce travail de thèse aborde cette question par une autre approche. Nous partons du postulat que les débats portant sur l'avenir de la politique de la vieillesse sont révélateurs d'une lutte entre acteurs du champ de régulation sociale qui participent d'un travail d'élaboration d'une pensée d'Etat, au sens de P Bourdieu. Cette lutte a pour objet l'imposition de catégories de pensées, soit la définition de ce qu'est un âgé aujourd'hui et de ce qu'il est moralement acceptable d'attendre de lui Nous montrons que cette question peut être comprise à l'aune de l'histoire du traitement social de la vieillesse dont nous relatons ici la genèse et les transformations. Nous soulignons également combien cette pensée d'Etat marque la manière dont les retraités aujourd'hui cherchent à se valoriser face à la déstabilisation de leur statut social. Summary "Crisis of social insurance for older people", "demographic imbalance", "aging of the population", "bankruptcy of pensions systems" ; these are some of the many expressions that today play a importance part in discussion about the future of social security. The Swiss and European political authorities show they are concerned about the crisis that "aging societies" are said to be facing. Indeed, while social insurance for old age used to concern a residual category of people who managet! to live to more than 65 years old, it now covers about a fifth of the global population. Hence, the Federal authorities are calling for a tightening of the conditions for access to retirement benefits. At first glance, the debates in the political arena »elated to (his question mainly deal with technical considerations linked to the economic conditions for the perpetuation of the insurance for old age. Ease of access and the level of the benefits have to be reduced in order to balance the funds, in the face of the rise of the number beneficiaries. This thesis study addresses this question through a different approach. We start from the proposition that debates concerning the future of social policy for old age reveal a struggle between those involved in (he field of social regulation ; this struggle is part of the development of the thought of the State as conceived by P. Bourdieu. The aim of this fight is to impose normative categories of thought, that is to say in relation to our subject, the definition of what an older person is today and what is morally acceptable to expect of him or her. We show that this question can be understood in the light of the the history of the social treatment of old age that we report here. Moreover, we show that this thought of the State explains the way retired people seek to value themselves and confront the destabilisation of their social status.

Screening primary-care patients forgoing health care for economic reasons.

BACKGROUND: Growing social inequities have made it important for general practitioners to verify if patients can afford treatment and procedures. Incorporating social conditions into clinical decision-making allows general practitioners to address mismatches between patients' health-care needs and financial resources. OBJECTIVES: Identify a screening question to, indirectly, rule out patients' social risk of forgoing health care for economic reasons, and estimate prevalence of forgoing health care and the influence of physicians' attitudes toward deprivation. DESIGN: Multicenter cross-sectional survey. PARTICIPANTS: Forty-seven general practitioners working in the French-speaking part of Switzerland enrolled a random sample of patients attending their private practices. MAIN MEASURES: Patients who had forgone health care were defined as those reporting a household member (including themselves) having forgone treatment for economic reasons during the previous 12 months, through a self-administered questionnaire. Patients were also asked about education and income levels, self-perceived social position, and deprivation levels. KEY RESULTS: Overall, 2,026 patients were included in the analysis; 10.7% (CI95% 9.4-12.1) reported a member of their household to have forgone health care during the 12 previous months. The question "Did you have difficulties paying your household bills during the last 12 months" performed better in identifying patients at risk of forgoing health care than a combination of four objective measures of socio-economic status (gender, age, education level, and income) (R(2) = 0.184 vs. 0.083). This question effectively ruled out that patients had forgone health care, with a negative predictive value of 96%. Furthermore, for physicians who felt powerless in the face of deprivation, we observed an increase in the odds of patients forgoing health care of 1.5 times. CONCLUSION: General practitioners should systematically evaluate the socio-economic status of their patients. Asking patients whether they experience any difficulties in paying their bills is an effective means of identifying patients who might forgo health care.

Maps as risk mitigation tools. Adaptation of the Swiss hazard assessment and mapping methodology to a Moroccan site: Beni Mellal

Dans le contexte climatique actuel, les régions méditerranéennes connaissent une intensification des phénomènes hydrométéorologiques extrêmes. Au Maroc, le risque lié aux inondations est devenu problématique, les communautés étant vulnérables aux événements extrêmes. En effet, le développement économique et urbain rapide et mal maîtrisé augmente l'exposition aux phénomènes extrêmes. La Direction du Développement et de la Coopération suisse (DDC) s'implique activement dans la réduction des risques naturels au Maroc. La cartographie des dangers et son intégration dans l'aménagement du territoire représentent une méthode efficace afin de réduire la vulnérabilité spatiale. Ainsi, la DDC a mandaté ce projet d'adaptation de la méthode suisse de cartographie des dangers à un cas d'étude marocain (la ville de Beni Mellal, région de Tadla-Azilal, Maroc). La méthode suisse a été adaptée aux contraintes spécifiques du terrain (environnement semi-aride, morphologie de piémont) et au contexte de transfert de connaissances (caractéristiques socio-économiques et pratiques). Une carte des phénomènes d'inondations a été produite. Elle contient les témoins morphologiques et les éléments anthropiques pertinents pour le développement et l'aggravation des inondations. La modélisation de la relation pluie-débit pour des événements de référence, et le routage des hydrogrammes de crue ainsi obtenus ont permis d'estimer quantitativement l'aléa inondation. Des données obtenues sur le terrain (estimations de débit, extension de crues connues) ont permis de vérifier les résultats des modèles. Des cartes d'intensité et de probabilité ont été obtenues. Enfin, une carte indicative du danger d'inondation a été produite sur la base de la matrice suisse du danger qui croise l'intensité et la probabilité d'occurrence d'un événement pour obtenir des degrés de danger assignables au territoire étudié. En vue de l'implémentation des cartes de danger dans les documents de l'aménagement du territoire, nous nous intéressons au fonctionnement actuel de la gestion institutionnelle du risque à Beni Mellal, en étudiant le degré d'intégration de la gestion et la manière dont les connaissances sur les risques influencent le processus de gestion. L'analyse montre que la gestion est marquée par une logique de gestion hiérarchique et la priorité des mesures de protection par rapport aux mesures passives d'aménagement du territoire. Les connaissances sur le risque restent sectorielles, souvent déconnectées. L'innovation dans le domaine de la gestion du risque résulte de collaborations horizontales entre les acteurs ou avec des sources de connaissances externes (par exemple les universités). Des recommandations méthodologiques et institutionnelles issues de cette étude ont été adressées aux gestionnaires en vue de l'implémentation des cartes de danger. Plus que des outils de réduction du risque, les cartes de danger aident à transmettre des connaissances vers le public et contribuent ainsi à établir une culture du risque. - Severe rainfall events are thought to be occurring more frequently in semi-arid areas. In Morocco, flood hazard has become an important topic, notably as rapid economic development and high urbanization rates have increased the exposure of people and assets in hazard-prone areas. The Swiss Agency for Development and Cooperation (SADC) is active in natural hazard mitigation in Morocco. As hazard mapping for urban planning is thought to be a sound tool for vulnerability reduction, the SADC has financed a project aimed at adapting the Swiss approach for hazard assessment and mapping to the case of Morocco. In a knowledge transfer context, the Swiss method was adapted to the semi-arid environment, the specific piedmont morphology and to socio-economic constraints particular to the study site. Following the Swiss guidelines, a hydro-geomorphological map was established, containing all geomorphic elements related to known past floods. Next, rainfall / runoff modeling for reference events and hydraulic routing of the obtained hydrographs were carried out in order to assess hazard quantitatively. Field-collected discharge estimations and flood extent for known floods were used to verify the model results. Flood hazard intensity and probability maps were obtained. Finally, an indicative danger map as defined within the Swiss hazard assessment terminology was calculated using the Swiss hazard matrix that convolves flood intensity with its recurrence probability in order to assign flood danger degrees to the concerned territory. Danger maps become effective, as risk mitigation tools, when implemented in urban planning. We focus on how local authorities are involved in the risk management process and how knowledge about risk impacts the management. An institutional vulnerability "map" was established based on individual interviews held with the main institutional actors in flood management. Results show that flood hazard management is defined by uneven actions and relationships, it is based on top-down decision-making patterns, and focus is maintained on active mitigation measures. The institutional actors embody sectorial, often disconnected risk knowledge pools, whose relationships are dictated by the institutional hierarchy. Results show that innovation in the risk management process emerges when actors collaborate despite the established hierarchy or when they open to outer knowledge pools (e.g. the academia). Several methodological and institutional recommendations were addressed to risk management stakeholders in view of potential map implementation to planning. Hazard assessment and mapping is essential to an integrated risk management approach: more than a mitigation tool, danger maps represent tools that allow communicating on hazards and establishing a risk culture.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

Health at work and risk factors related to ergonomics: some results from the Swiss sample of the 4th European working conditions survey

Introduction The European Foundation for the improvement of living and working conditions conducts a survey every 5 years since 1990. The foundation also offers the possibility to non-EU countries to be included in the survey: in 2005, Switzerland took part for the first time in the fourth edition of this survey. The Institute for Work and Health (IST) has been associated to the Swiss project conducted under the leadership of the SECO and the Fachhochschule Nordwestschweiz. The survey covers different aspects of work like job characteristics and employment conditions, health and safety, work organization, learning and development opportunities, and the balance between working and non-working life (Parent-Thirion, Fernandez Macias, Hurley, & Vermeylen, 2007). More particularly, one question assesses the worker's self-perception of the effects of work on health. We identified (for the Swiss sample) several factors affecting the risk to report health problems caused by work. The Swiss sample includes 1040 respondents. Selection of participants was based on a random multi-stage sampling and was carried out by M.I.S Trend S.A. (Lausanne). Participation rate was 59%. The database was weighted by household size, gender, age, region of domicile, occupational group, and economic sector. Specially trained interviewers carried out the interviews at the respondents home. The survey was carriedout between the 19th of September 2005 and the 30th of November 2005. As detailed in (Graf et al., 2007), 31% of the Swiss respondents identify work as the cause of health problems they experience. Most frequently reported health problems include back pain (18%), stress (17%), muscle pain (13%), and overall fatigue (11%). Ergonomic aspects associated with higher risk of reporting health problems caused by work include frequent awkward postures (odds ratio [OR] 4.7, 95% confidence interval [CI] 3.1 to 5.4), tasks involving lifting heavy loads (OR 2.7, 95% CI 2.0 to 3.6) or lifting people (OR 2.2, 95% CI 1.4 to 3.5), standing or walking (OR 1.4, 95% CI 1.1 to 1.9), as well as repetitive movements (OR 1.7, 95% CI 1.3 to 2.3). These results highlight the need to continue and intensify the prevention of work related health problems in occupations characterized by risk factors related to ergonomics.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

The conditions for the reproduction of the SAGUAPAC water cooperative in the city of Santa Cruz de la Sierra, Bolivia : discourse analysis

The SAGUAPAC cooperative in the city of Santa Cruz de la Sierra (Eastern Bolivia) is regularly presented as an example of cooperative successes regarding water supply and sanitation. Its efficiency, both economic and technical, is widely considered as the main reason for its attractiveness. However, without denying its importance, we show, through a discourse analysis from and about SAGUAPAC in local media, that moral and non-instrumental factors are crucial in the reproduction of the cooperative. These factors create attachment and affection toward the cooperative, through a storytelling using a four-dimensional rhetoric (mythification, identification, emotionalisation and personification). This storytelling technique, internalized in the local media discourse and materializing the so-called new spirit of capitalism, exploits the affects and instrumentalisation of local myths and legends, as well as the 'camba' ethnic identity. In that, it tends to retain SAGUAPAC members and to canvass new ones, by providing them with recognition in their quality of local community members. However, the mobilisation of social norms and power hierarchies might end up reinforcing the social exclusion of Andean non-camba immigrants, inspite of an a priori inclusive and democratic organisation.

Stochasticity in economic losses increases the value of reputation in indirect reciprocity.

Recent theory predicts harsh and stochastic conditions to generally promote the evolution of cooperation. Here, we test experimentally whether stochasticity in economic losses also affects the value of reputation in indirect reciprocity, a type of cooperation that is very typical for humans. We used a repeated helping game with observers. One subject (the "Unlucky") lost some money, another one (the "Passer-by") could reduce this loss by accepting a cost to herself, thereby building up a reputation that could be used by others in later interactions. The losses were either stable or stochastic, but the average loss over time and the average efficiency gains of helping were kept constant in both treatments. We found that players with a reputation of being generous were generally more likely to receive help by others, such that investing into a good reputation generated long-term benefits that compensated for the immediate costs of helping. Helping frequencies were similar in both treatments, but players with a reputation to be selfish lost more resources under stochastic conditions. Hence, returns on investment were steeper when losses varied than when they did not. We conclude that this type of stochasticity increases the value of reputation in indirect reciprocity.