Die vorgelegte Dissertation trägt den Titel Regularization Methods for Statistical Modelling in Small Area Estimation. In ihr wird die Verwendung regularisierter Regressionstechniken zur geographisch oder kontextuell hochauflösenden Schätzung aggregatspezifischer Kennzahlen auf Basis kleiner Stichproben studiert. Letzteres wird in der Fachliteratur häufig unter dem Begriff Small Area Estimation betrachtet. Der Kern der Arbeit besteht darin die Effekte von regularisierter Parameterschätzung in Regressionsmodellen, welche gängiger Weise für Small Area Estimation verwendet werden, zu analysieren. Dabei erfolgt die Analyse primär auf theoretischer Ebene, indem die statistischen Eigenschaften dieser Schätzverfahren mathematisch charakterisiert und bewiesen werden. Darüber hinaus werden die Ergebnisse durch numerische Simulationen veranschaulicht, und vor dem Hintergrund empirischer Anwendungen kritisch verortet. Die Dissertation ist in drei Bereiche gegliedert. Jeder Bereich behandelt ein individuelles methodisches Problem im Kontext von Small Area Estimation, welches durch die Verwendung regularisierter Schätzverfahren gelöst werden kann. Im Folgenden wird jedes Problem kurz vorgestellt und im Zuge dessen der Nutzen von Regularisierung erläutert. Das erste Problem ist Small Area Estimation in der Gegenwart unbeobachteter Messfehler. In Regressionsmodellen werden typischerweise endogene Variablen auf Basis statistisch verwandter exogener Variablen beschrieben. Für eine solche Beschreibung wird ein funktionaler Zusammenhang zwischen den Variablen postuliert, welcher durch ein Set von Modellparametern charakterisiert ist. Dieses Set muss auf Basis von beobachteten Realisationen der jeweiligen Variablen geschätzt werden. Sind die Beobachtungen jedoch durch Messfehler verfälscht, dann liefert der Schätzprozess verzerrte Ergebnisse. Wird anschließend Small Area Estimation betrieben, so sind die geschätzten Kennzahlen nicht verlässlich. In der Fachliteratur existieren hierfür methodische Anpassungen, welche in der Regel aber restriktive Annahmen hinsichtlich der Messfehlerverteilung benötigen. Im Rahmen der Dissertation wird bewiesen, dass Regularisierung in diesem Kontext einer gegen Messfehler robusten Schätzung entspricht - und zwar ungeachtet der Messfehlerverteilung. Diese Äquivalenz wird anschließend verwendet, um robuste Varianten bekannter Small Area Modelle herzuleiten. Für jedes Modell wird ein Algorithmus zur robusten Parameterschätzung konstruiert. Darüber hinaus wird ein neuer Ansatz entwickelt, welcher die Unsicherheit von Small Area Schätzwerten in der Gegenwart unbeobachteter Messfehler quantifiziert. Es wird zusätzlich gezeigt, dass diese Form der robusten Schätzung die wünschenswerte Eigenschaft der statistischen Konsistenz aufweist. Das zweite Problem ist Small Area Estimation anhand von Datensätzen, welche Hilfsvariablen mit unterschiedlicher Auflösung enthalten. Regressionsmodelle für Small Area Estimation werden normalerweise entweder für personenbezogene Beobachtungen (Unit-Level), oder für aggregatsbezogene Beobachtungen (Area-Level) spezifiziert. Doch vor dem Hintergrund der stetig wachsenden Datenverfügbarkeit gibt es immer häufiger Situationen, in welchen Daten auf beiden Ebenen vorliegen. Dies beinhaltet ein großes Potenzial für Small Area Estimation, da somit neue Multi-Level Modelle mit großem Erklärungsgehalt konstruiert werden können. Allerdings ist die Verbindung der Ebenen aus methodischer Sicht kompliziert. Zentrale Schritte des Inferenzschlusses, wie etwa Variablenselektion und Parameterschätzung, müssen auf beiden Levels gleichzeitig durchgeführt werden. Hierfür existieren in der Fachliteratur kaum allgemein anwendbare Methoden. In der Dissertation wird gezeigt, dass die Verwendung ebenenspezifischer Regularisierungsterme in der Modellierung diese Probleme löst. Es wird ein neuer Algorithmus für stochastischen Gradientenabstieg zur Parameterschätzung entwickelt, welcher die Informationen von allen Ebenen effizient unter adaptiver Regularisierung nutzt. Darüber hinaus werden parametrische Verfahren zur Abschätzung der Unsicherheit für Schätzwerte vorgestellt, welche durch dieses Verfahren erzeugt wurden. Daran anknüpfend wird bewiesen, dass der entwickelte Ansatz bei adäquatem Regularisierungsterm sowohl in der Schätzung als auch in der Variablenselektion konsistent ist. Das dritte Problem ist Small Area Estimation von Anteilswerten unter starken verteilungsbezogenen Abhängigkeiten innerhalb der Kovariaten. Solche Abhängigkeiten liegen vor, wenn eine exogene Variable durch eine lineare Transformation einer anderen exogenen Variablen darstellbar ist (Multikollinearität). In der Fachliteratur werden hierunter aber auch Situationen verstanden, in welchen mehrere Kovariate stark korreliert sind (Quasi-Multikollinearität). Wird auf einer solchen Datenbasis ein Regressionsmodell spezifiziert, dann können die individuellen Beiträge der exogenen Variablen zur funktionalen Beschreibung der endogenen Variablen nicht identifiziert werden. Die Parameterschätzung ist demnach mit großer Unsicherheit verbunden und resultierende Small Area Schätzwerte sind ungenau. Der Effekt ist besonders stark, wenn die zu modellierende Größe nicht-linear ist, wie etwa ein Anteilswert. Dies rührt daher, dass die zugrundeliegende Likelihood-Funktion nicht mehr geschlossen darstellbar ist und approximiert werden muss. Im Rahmen der Dissertation wird gezeigt, dass die Verwendung einer L2-Regularisierung den Schätzprozess in diesem Kontext signifikant stabilisiert. Am Beispiel von zwei nicht-linearen Small Area Modellen wird ein neuer Algorithmus entwickelt, welche den bereits bekannten Quasi-Likelihood Ansatz (basierend auf der Laplace-Approximation) durch Regularisierung erweitert und verbessert. Zusätzlich werden parametrische Verfahren zur Unsicherheitsmessung für auf diese Weise erhaltene Schätzwerte beschrieben. Vor dem Hintergrund der theoretischen und numerischen Ergebnisse wird in der Dissertation demonstriert, dass Regularisierungsmethoden eine wertvolle Ergänzung der Fachliteratur für Small Area Estimation darstellen. Die hier entwickelten Verfahren sind robust und vielseitig einsetzbar, was sie zu hilfreichen Werkzeugen der empirischen Datenanalyse macht.

Dieser Artikel erschien in der Zeitschrift "Deutschunterricht" 1995. Er porträtiert den syrischen Schriftsteller, der sich unter dem Pseudonym Rafik Schami einen Namen gemacht hat.

1907 erschien das Violoncello erstmals in der Filmgeschichte. Als Hauptinstrument in einem kurzen Slapstick der französischen Firma Pathé. - Der Beitrag erschien in der Festschrift für den Barockcellisten Gerhart Darmstadt.

This working paper examines the concept of metabolism and its potential as a critical analytical lens to study the contemporary city from a political perspective. The paper illustrates how the metabolism concept has been used historically, both as a metaphor to describe the technological, social, political and economic dimensions of human-environment relations, and as a concrete analytical tool to quantify and better understand how flows of matter and energy shape the territorial and spatial configurations of cityscapes. Drawing on the example of the urban water metabolism of the Greater Accra Metropolitan Area (GAMA), it is argued that contemporary approaches to metabolic analysis should be extended in two ways to increase the integrative potential of the urban water metabolism concept. On the one hand, the paper demonstrates that a political ecology approach is particularly well-suited to illuminate the contested production of urban environments and move beyond a narrow technical, managerial and state- centric focus in research on urban metabolic relations. On the other hand, the paper advocates for an approach to metabolic analysis that views the urban environment not simply as a relatively static exteriority that is produced by dynamic flows of matter, energy and information, but rather as a dynamic, nested and co-evolutionary network of complex biosocial and material relations, which in itself shapes how various metabolisms interact across scales. The paper then concludes by briefly discussing how a combination of metabolic analysis and political ecology research can inform urban water governance. In sum, the paper emphasizes the need for metabolic analysis to remain open to a plurality of different knowledge forms and perspectives, and to remain attentive to the inherently political nature of material and technological phenomena in order to allow for mutually beneficial exchanges between various scholarly communities.

The main socio-ecological pressures in five wetlands in the Greater Accra Region were first identified and then summarized by reviewing the relevant literature. As a second step, fieldwork in the region was carried out in 2016 to further examine the pressures identified in the literature. Most research on the wetlands in Ghana was published around the year 2000. Yet, similar socio-ecological pressures persist today. Based on both, fieldwork observations and the literature review, these pressures were ranked using the IUCN pressures system analysis framework. It is suggested that further research needs to proceed with uncovering how trade-offs between ecosystem and quality of life can be defined.

This report presents the results of a stakeholder mapping exercise carried out in the WaterPower project. The mapping was conducted for the following main research areas of the project: water supply, land use planning and management, wetland management and climate change adaptation/disaster risk reduction. The report gives an overview of the stakeholders that play a role in these respective areas and identifies those who have concomitant responsibilities in different sectors. It represents the first step towards further involvement of stakeholders in the WaterPower project.

Urban flooding cannot be avoided entirely and in all areas, particularly in coastal cities. Therefore adaptation to the growing risk is necessary. Geographical Information Systems (GIS) based knowledge on risk informs location-based approach to adaptation to climate risk. It allows managing city- wide coordination of adaptation measures, reducing adverse impacts of local strategies on neighbouring areas to the minimum. Quantitative assessments dominate GIS applications in flood risk management, for instance to demonstrate the distribution of people and assets in a flood prone area. Qualitative, participatory approaches to GIS are on the rise but have not been applied in the context of flooding yet. The overarching research question of this working paper is: what can GIS, and what can it not say about relationships / social relations in adaptation to urban flood risk? The use of GIS in risk mapping has exposed environmental injustices. Applications of GIS further allow model- ling future flood risk in function of demographic and land use changes, and combining it with decision support systems (DSS). While such GIS applications provide invaluable information for urban planners steering adaptation they however fall short on revealing the social relations that shape individual and household adaptation decisions. The relevance of networked social relations in adaptation to flood risk has been demonstrated in case studies, and extensively in the literature on organizational learning and adaptation to change. The purpose of this literature review is to identify the type of social relations that shape adaptive capacities towards urban flood risk which can- not be identified in a conventional GIS application.

The rate and range of ongoing changes in social and ecological systems and particularly the global environmental degradation illustrates the need of holistic and sustainable approaches for the governance of natural resources to ensure their well-functioning for future generations (Rockström et al. 2009). The narrative of common pool resources system such as SES of small-scale fisheries, reports world-wide of stock collapse, environmental degradation and overexploitation (Cinner et al. 2013). In order to understand the complexity of system interactions in those resource systems, the consideration of local scale specific phenomena is of great relevance (Ostrom 2007b). The focus of this thesis consequently is the social-ecological system of a small scale fishery in a heavily urbanised coastal wetland on the fringes of Ghana ́s capital Accra. With the theoretical foundation of the social-ecological system (SES) theory (Folke et al. 2004; Berkes et al. 2003; G. S. Cumming 2011) and the social-ecological system framework (SESF) by Ostrom (2007a) and McGinnis & Ostrom (2014) as analytical tool, the study ex- amines the role of the fishers as focal actor group and the governance system based on traditional ecological knowledge (TEK) (Berkes et al. 2003). While the common narrative of system collapse is partly confirmed for the focal system, also contradicting findings about the diversity of the actor group, their sustainable and responsible exploitation of the deltas resources have been found, that rather illustrate the fishers as potential cooperation partners for the development of sustainable governance strategies (see Hollup 2000) than simply as bur- den to the system. However, the results also show that in order to achieve sustainable outcomes in the focal SES, so far unsuccessful top-down governance efforts have to work cooperatively with the fishers to challenge the multiple threats to the system from external perturbation and internal changes, in the long run.

This literature review was conducted to identify important wetlands in the Greater Accra Region and to illustrate dominant research trends, prevailing perspectives and corresponding research gaps. Six wetlands systems were identified as most significant lagoon systems, namely the Densu Delta, Sakumo, Muni-Pomadze, Keta, Korle and Songor Lagoons. Research foci for each of the respective wetlands were extrapolated and summarized in a category system. The frequency of different categories illustrates that natural science’s perspectives dominate, as most of Accra’s lagoons have been studied with regard to their ecological, physical and chemical properties. The development of research interest over time and focus on ecological baseline conditions are related to the designation of Ramsar Sites and orientation of national policies towards environmental protection. A research gap was identified, as studies link their findings to human activities but neglect the connection between governance variables and environmental developments. It is suggested to expand the natural science’s perspective on Accra’s wetlands to account for social and political aspects in order to develop a holistic and more sustainable management strategy.

This working paper outlines analytical pathways that could contribute to deepening the understanding of water inequalities in cities of the Global South. It brings together the status quo of research on water inequalities in Accra, the capital of Ghana, and studies on Environmental Justice. In doing so, it argues for the need to analytically distinguish between the terms ‘(in)equality’ and ‘(in)justice’. Studying everyday water practices and per- spectives on water (in)justice of different stakeholders would be a suitable entry point for an in-depth ethnographic study that analytically separates water inequalities and water injustices but considers their interlinkages. The working paper is based on a literature review conducted in 2015 in the scope of the WaterPower project.

In der kleinen ostfriesischen Kirchengemeinde W. hat sich im Jahr 1969 ein plötzlicher Todesfall ereignet. Fremdverschulden wird ausgeschlossen. Jemand, der die Hintergründe des Todesfalls aufklären will, stößt allenthalben auf – bisweilen gar aggressives – Schweigen. Eine Geschichte über individuelle und kollektive Schuld, lutherische Kirchenmusik und den Wert, den wir der Kultur und der Tradition beimessen. Ausgezeichnet mit dem Borsla-Preis 2019.

Global food security poses large challenges to a fast changing human society and has been a key topic for scientists, agriculturist, and policy makers in the 21st century. The United Nation predicts a total world population of 9.15 billion in 2050 and defines the provision of food security as the second major point in the UN Sustainable Development Goals. As the capacities of both, land and water resources, are finite and locally heavily overused, reducing agriculture’s environmental impact while meeting an increasing demand for food of a constantly growing population is one of the greatest challenges of our century. Therefore, a multifaceted solution is required, including approaches using geospatial data to optimize agricultural food production. The availability of precise and up-to-date information on vegetation parameters is mandatory to fulfill the requirements of agricultural applications. Direct field measurements of such vegetation parameters are expensive and time-consuming. On the contrary, remote sensing offers a variety of techniques for a cost-effective and non-destructive retrieval of vegetation parameters. Although not widely used, hyperspectral thermal infrared (TIR) remote sensing has demonstrated being a valuable addition to existing remote sensing techniques for the retrieval of vegetation parameters. This thesis examined the potential of TIR imaging spectroscopy as an important contribution to the growing need of food security. The main scientific question dealt with the extraction of vegetation parameters from imaging TIR spectroscopy. To this end, two studies impressively demonstrated the ability of extracting vegetation related parameters from leaf emissivity spectra: (i) the discrimination of eight plant species based on their emissivity spectra and (ii) the detection of drought stress in potato plants using temperature measures and emissivity spectra. The datasets used in these studies were collected using the Telops Hyper-Cam LW, a novel imaging spectrometer. Since this FTIR spectrometer presents some particularities, special attention was paid on the development of dedicated experimental data acquisition setups and on data processing chains. The latter include data preprocessing and the development of algorithms for extracting precise surface temperatures, reproducible emissivity spectra and, in the end, vegetation parameters. The spectrometer’s versatility allows the collection of airborne imaging spectroscopy datasets. Since the general availability of airborne TIR spectrometers is limited, the preprocessing and data extraction methods are underexplored compared to reflective remote sensing. This counts especially for atmospheric correction (AC) and temperature and emissivity separation (TES) algorithms. Therefore, we implemented a powerful simulation environment for the development of preprocessing algorithms for airborne hyperspectral TIR image data. This simulation tool is designed in a modular way and includes the image data acquisition and processing chain from surface temperature and emissivity to the final at-sensor radiance data. It includes a series of available algorithms for TES, AC as well as combined AC and TES approaches. Using this simulator, one of the most promising algorithms for the preprocessing of airborne TIR data – ARTEMISS – was significantly optimized. The retrieval error of the atmospheric water vapor during the atmospheric characterization was reduced. As a result, this improvement in atmospheric characterization accuracy enhanced the subsequent retrieval of surface temperatures and surface emissivities intensely. Although, the potential of hyperspectral TIR applications in ecology, agriculture, and biodiversity has been impressively demonstrated, a serious contribution to a global provision of food security requires the retrieval of vegetation related parameters with global coverage, high spatial resolution and at high revisit frequencies. Emerging from the findings in this thesis, the spectral configuration of a spaceborne TIR spectrometer concept was developed. The sensors spectral configuration aims at the retrieval of precise land surface temperatures and land surface emissivity spectra. Complemented with additional characteristics, i.e. short revisit times and a high spatial resolution, this sensor potentially allows the retrieval of valuable vegetation parameters needed for agricultural optimizations. The technical feasibility of such a sensor concept underlines the potential contribution to the multifaceted solution required for achieving the challenging goal of guaranteeing global food security in a world of increasing population. In conclusion, thermal remote sensing and more precisely hyperspectral thermal remote sensing has been presented as a valuable technique for a variety of applications contributing to the final goal of a global food security.

In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.

This dissertation deals with consistent estimates in household surveys. Household surveys are often drawn via cluster sampling, with households sampled at the first stage and persons selected at the second stage. The collected data provide information for estimation at both the person and the household level. However, consistent estimates are desirable in the sense that the estimated household-level totals should coincide with the estimated totals obtained at the person-level. Current practice in statistical offices is to use integrated weighting. In this approach consistent estimates are guaranteed by equal weights for all persons within a household and the household itself. However, due to the forced equality of weights, the individual patterns of persons are lost and the heterogeneity within households is not taken into account. In order to avoid the negative consequences of integrated weighting, we propose alternative weighting methods in the first part of this dissertation that ensure both consistent estimates and individual person weights within a household. The underlying idea is to limit the consistency conditions to variables that emerge in both the personal and household data sets. These common variables are included in the person- and household-level estimator as additional auxiliary variables. This achieves consistency more directly and only for the relevant variables, rather than indirectly by forcing equal weights on all persons within a household. Further decisive advantages of the proposed alternative weighting methods are that original individual rather than the constructed aggregated auxiliaries are utilized and that the variable selection process is more flexible because different auxiliary variables can be incorporated in the person-level estimator than in the household-level estimator. In the second part of this dissertation, the variances of a person-level GREG estimator and an integrated estimator are compared in order to quantify the effects of the consistency requirements in the integrated weighting approach. One of the challenges is that the estimators to be compared are of different dimensions. The proposed solution is to decompose the variance of the integrated estimator into the variance of a reduced GREG estimator, whose underlying model is of the same dimensions as the person-level GREG estimator, and add a constructed term that captures the effects disregarded by the reduced model. Subsequently, further fields of application for the derived decomposition are proposed such as the variable selection process in the field of econometrics or survey statistics.

Der vorliegende Sammelband geht auf die UniGR-Fachtagung Edu.GR - Europa leben lernen / Edu.GR - Apprendre à vivre l’Europe zurück, die am 20. September 2018 an der Universität Trier stattfand. Die Beiträge befassen sich aus unterschiedlichen Perspektiven – so aus Sicht der Bildungswissenschaften, der Fachdidaktiken, der Sozialwissenschaften und der Bildungspraxis – mit der Frage der Gestaltung Europas am Beispiel der Großregion. Vorgestellt und diskutiert werden neben Konzepten transnationaler Bildung auch empirische Analysen des Denkens und Handelns der Beteiligten in grenzregionalen (Aus-)Bildungskontexten sowie ausgewählte Beispiele transnationaler Bildungspraxis.

Thema dieser Dissertation ist das deutsche Selbstbildnis im 17. Jahrhundert. Ziel der Arbeit war es, das deutsche Selbstbildnis als eigene Gattung zu etablieren. Hierzu wurden die Selbstbildnisse deutscher Maler des 17. Jahrhunderts ausgewählt, gilt doch diese Zeit noch immer als ‚totes Jahrhundert‘. Grundlage der Untersuchung war eine Sammlung von 148 Objekten, die einer grundlegenden Analyse unterzogen wurden. Das früheste Selbstbildnis in dieser Sammlung stammt von 1600, das späteste wurde um 1700 angefertigt. Künstler aus dem gesamten Alten Reich, ob aus Schlesien und Böhmen, Nord-oder Süddeutschland oder aus den österreichischen wie schweizerischen Landen sind hier vertreten. Die Selbstbildnisse stammen von Malern in der gesamten breite ihrer Karriere. So sind gleichermaßen Selbstbildnisse von Gesellen wie Meistern, von Hofmalern bis hin zu Freimeistern vertreten. Besonders wichtig war es, nicht nur Selbstbildnisse im Gemälde oder Kupferstich in die Untersuchung aufzunehmen, sondern auch Stammbucheinträge. Die ausführliche Betrachtung und Gegenüberstellung der deutschen Selbstbildnisse mit denen ihrer europäischen Kollegen hat gezeigt, dass auch deutsche Maler den gängigen Darstellungstypen wie etwa dem virtuoso folgten. Aber die deutschen Maler imitierten nicht nur, sondern experimentierten und gingen mit ihren Vorbildern spielerisch um. Daneben folgten sie natürlich auch den Trends der Selbstinszenierung. Sie drückten in ihren Selbstbildnissen ihren Wunsch nach sozialer und gesellschaftlicher Emanzipation des gesamten Berufsstandes aus. So war das deutsche Selbstbildnis eigenständiger Ausdruck des Aufbruches deutscher Künstler in eine neue Zeit.

Die Trierer Quellen- und Studienhefte zur historisch-politischen Bildung veröffentlichen Ergebnisse aktueller Forschungsprojekte und Materialien für den historisch-politischen Unterricht aus der Arbeit des Arbeitsbereichs Didaktik der Gesellschaftswissenschaften.

This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.

L’apprentissage par le projet - plus que toute autre forme d’enseignement - permet aux élèves de participer de manière autonome à l’organisation des cours. Les apprenant(e)s ne s’exercent pas seulement dans l’action autonome et responsable, mais jouent, eux aussi, un rôle actif dans la société.

Considérer les processus d’évaluation à l’école comme une possibilité pour soutenir les élèves dans l’évaluation réaliste et le développement de leurs processus et leur comportement d’apprentissage : l’évaluation participative des performances offre différentes possibilités pratiques pour favoriser la motivation d’apprendre, l’autoréflexion et la compréhension démocratique.

Les carnets paraissent deux fois par an et offrent aux dirigeant(e)s des écoles ainsi qu’au personnel des fondements théoriques et du matériel pratique pour la mise en oeuvre d’un développement scolaire démocratique. Chaque publication traite d’une méthode de l’éducation à la démocratie ou d’une question stratégique du développement scolaire. Les carnets en langue allemande sont mis à la disposition des écoles luxembourgeoises en version imprimée. Tout le matériel ainsi que la version en langue française sont disponibles en ligne.

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L‘école est un lieu de socialisation des enfants et des jeunes. Les heures de cours de l‘enseignement des différentes matières sont un espace d‘expérimentation de cette socialisation. Elles marquent par leur durée dans la journée aussi bien le rôle fondamental de l‘école que l‘action et la perception à la fois des enseignant(e)s et des apprenant(e)s. Il apparaît donc d’autant plus important d’intégrer ces cours dans l’organisation d’une culture scolaire démocratique.

Evapotranspiration is often estimated by numerical simulation. However, to produce accurate simulations, these models usually require on-site measurements for parameterization or calibration. We have to make sure that the model realistically reproduces both, the temporal patterns of soil moisture and evapotranspiration. In this study, we combine three sources of information: (i) measurements of sap velocities; (ii) soil moisture; and (iii) expert knowledge on local runoff generation and water balance to define constraints for a “behavioral” forest stand water balance model. Aiming for a behavioral model, we adjusted soil moisture at saturation, bulk resistance parameters and the parameters of the water retention curve (WRC). We found that the shape of the WRC influences substantially the behavior of the simulation model. Here, only one model realization could be referred to as “behavioral”. All other realizations failed for a least one of our evaluation criteria: Not only transpiration and soil moisture are simulated consistently with our observations, but also total water balance and runoff generation processes. The introduction of a multi-criteria evaluation scheme for the detection of unrealistic outputs made it possible to identify a well performing parameter set. Our findings indicate that measurement of different fluxes and state variables instead of just one and expert knowledge concerning runoff generation facilitate the parameterization of a hydrological model.

In this thesis, we aim to study the sampling allocation problem of survey statistics under uncertainty. We know that the stratum specific variances are generally not known precisely and we have no information about the distribution of uncertainty. The cost of interviewing each person in a stratum is also a highly uncertain parameter as sometimes people are unavailable for the interview. We propose robust allocations to deal with the uncertainty in both stratum specific variances and costs. However, in real life situations, we can face such cases when only one of the variances or costs is uncertain. So we propose three different robust formulations representing these different cases. To the best of our knowledge robust allocation in the sampling allocation problem has not been considered so far in any research. The first robust formulation for linear problems was proposed by Soyster (1973). Bertsimas and Sim (2004) proposed a less conservative robust formulation for linear problems. We study these formulations and extend them for the nonlinear sampling allocation problem. It is very unlikely to happen that all of the stratum specific variances and costs are uncertain. So the robust formulations are in such a way that we can select how many strata are uncertain which we refer to as the level of uncertainty. We prove that an upper bound on the probability of violation of the nonlinear constraints can be calculated before solving the robust optimization problem. We consider various kinds of datasets and compute robust allocations. We perform multiple experiments to check the quality of the robust allocations and compare them with the existing allocation techniques.