Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

Export Supply Chain Organization and Food Safety and Quality Standards: a case study of the Moroccan Fruit and Vegetable Sector

Agri-food supply chains extend beyond national boundaries, partially facilitated by a policy environment that encourages more liberal international trade. Rising concentration within the downstream sector has driven a shift towards “buyer-driven” global value chains (GVCs) extending internationally with global sourcing and the emergence of multinational key economic players that compete with increase emphasis on product quality attributes. Agri-food systems are thus increasingly governed by a range of inter-related public and private standards, both of which are becoming a priori mandatory, especially in supply chains for high-value and quality-differentiated agri-food products and tend to strongly affect upstream agricultural practices, firms’ internal organization and strategic behaviour and to shape the food chain organization. Notably, increasing attention has been given to the impact of SPS measures on agri-food trade and notably on developing countries’ export performance. Food and agricultural trade is the vital link in the mutual dependency of the global trade system and developing countries. Hence, developing countries derive a substantial portion of their income from food and agricultural trade. In Morocco, fruit and vegetable (especially fresh) are the primary agricultural export. Because of the labor intensity, this sector (especially citrus and tomato) is particularly important in terms of income and employment generation, especially for the female laborers hired in the farms and packing houses. Hence, the emergence of agricultural and agrifood product safety issues and the subsequent tightening of market requirements have challenged mutual gains due to the lack of technical and financial capacities of most developing countries.

Essays in Industrial Organization and Information Technology

Chapter 1 studies how consumers’ switching costs affect the pricing and profits of firms competing in two-sided markets such as Apple and Google in the smartphone market. When two-sided markets are dynamic – rather than merely static – I show that switching costs lower the first-period price if network externalities are strong, which is in contrast to what has been found in one-sided markets. By contrast, switching costs soften price competition in the initial period if network externalities are weak and consumers are more patient than the platforms. Moreover, an increase in switching costs on one side decreases the first-period price on the other side. Chapter 2 examines firms’ incentives to invest in local and flexible resources when demand is uncertain and correlated. I find that market power of the monopolist providing flexible resources distorts investment incentives, while competition mitigates them. The extent of improvement depends critically on demand correlation and the cost of capacity: under social optimum and monopoly, if the flexible resource is cheap, the relationship between investment and correlation is positive, and if it is costly, the relationship becomes negative; under duopoly, the relationship is positive. The analysis also sheds light on some policy discussions in markets such as cloud computing. Chapter 3 develops a theory of sequential investments in cybersecurity. The regulator can use safety standards and liability rules to increase security. I show that the joint use of an optimal standard and a full liability rule leads to underinvestment ex ante and overinvestment ex post. Instead, switching to a partial liability rule can correct the inefficiencies. This suggests that to improve security, the regulator should encourage not only firms, but also consumers to invest in security.

Performing inclusion and exclusion in the peer group. Children's social organization and peer socializing practices in the classroom

This PhD thesis investigates children’s peer practices in two primary schools in Italy, focusing on the ordinary and the Italian L2 classroom. The study is informed by the paradigm of language socialization and considers peer interactions as a ‘double opportunity space’, allowing both children’s co-construction of their social organization and children’s sociolinguistic development. These two foci of attention are explored on the basis of children’s social interaction and of the verbal, embodied, and material resources that children agentively deploy during their mundane activities in the peer group. The study is based on a video ethnography that lasted nine months. Approximately 30 hours of classroom interactions were video-recorded, transcribed, and analyzed with an approach that combines the micro-analytic instruments of Conversation Analysis and the use of ethnographic information. Three main social phenomena were selected for analysis: (a) children’s enactment of the role of the teacher, (b) children’s reproduction of must-formatted rules, and (c) children’s argumentative strategies during peer conflict. The analysis highlights the centrality of the institutional frame for children’s peer interactions in the classroom. Moreover, the study illustrates that children socialize their classmates to the linguistic, social, and moral expectations of the context in and through various practices. Notably, these practices are also germane to the local negotiation of children’s social organization and hierarchy. Therefore, the thesis underlines that children’s peer interactions are both a resource for children’s sociolinguistic development and a potentially problematic locus where social exclusion is constructed and brought to bear. These insights are relevant for teachers’ professional practice. Children’s peer interactions are a resource that can be integrated in everyday didactics. Nevertheless, the role of the teacher in supervising and steering children’s peer practices appears crucial: an acritical view of children’s autonomous work, often implied in teaching methods such as peer tutoring, needs to be problematized.

Populism as a battlefield Populist actors and their representation on social and legacy media during the european parliament elections 2019 in Finland, Italy and the Netherlands

The objective of the present research is to describe and explain populist actors and populism as a concept and their representation on social and legacy media during the 2019 EU elections in Finland, Italy and The Netherlands. This research tackles the topic of European populism in the context of political communication and its relation to both the legacy and digital media within the hybrid media system. Departing from the consideration that populism and populist rhetoric are challenging concepts to define, I suggest that they should be addressed and analyzed through the usage of a combination of methods and theoretical perspectives, namely Communication Studies, Corpus Linguistics, Political theory, Rhetoric and Corpus-Assisted Discourse Studies. This thesis considers data of different provenance. On the one hand, for the Legacy media part, newspapers articles were collected in the three countries under study from the 1st until the 31st of May 2019. Each country’s legacy system is represented by three different quality papers and the articles were collected according to a selection of keywords (European Union Elections and Populism in each of the three languages). On the other hand, the Digital media data takes into consideration Twitter tweets collected during the same timeframe based on particular country-specific hashtags and tweets by identified populist actors. In order to meet the objective of this study, three research questions are posed and the analysis leading to the results are exhaustively presented and further discussed. The results of this research provide valuable and novel insights on how populism as a theme and a concept is being portrayed in the context of the European elections both in legacy and digital media and political communication in general.

Victorian letter writing and its representation in literature and painting: the case study of love letters

One of the main features of nineteenth-century fiction is the quasi-total disappearance of the epistolary novel that had had its heydays in the previous century. For this reason, some scholars have declared the “death” of the letter in literature after the transitional romantic period. However, Victorian novels overflow with letters that are embedded, quoted in part or described and commented on by narrators or characters. Even when its content is not revealed to the reader, the letter becomes a signifier loaded with meanings, also and particularly so, when it is burnt, torn, hidden, found or buried. The Postal Reform of 1839-40 caused the number of letters sent every year in Britain to grow from 75 to 410 million in only 14 years, and the mediatic campaign that supported it drew the attention of the population to the material aspects concerning this means of communication. Newspapers became more affordable too and they promoted a taste for sensationalism that often involved the “spectacularization” of private correspondence. Starting from an excursus on the history of the letter aimed at identifying the key aspects of the genre, this work deals with some real love correspondences from people belonging to different classes in the period from 1840 to the 1870s, to then analyse their fictional and pictorial counterparts. The general picture that emerges from this analysis is that of a Victorian society where letters were able to break down the boundaries between high and low forms of cultural expressions and where, more than ever, letters were present in people’s everyday lives as well as in the art and literature they enjoyed.

Beyond pollinator reward: steps forward and knowledge gaps on the role of floral nectar in plant-animal interactions.

The work done within the framework of my PhD project has been carried out between November 2019 and January 2023 at the Department of Biological, Geological and Environmental Sciences of the University of Bologna, under the supervision of Prof. Marta Galloni and PhD Gherardo Bogo. A period of three months was spent at the Natural History Museum of Rijeka, under the supervision of Prof. Boštjan Surina. The main aim of the thesis was to investigate further the so-called pollinator manipulation hypothesis, which states that when a floral visitor gets in contact with a specific nectar chemistry, the latter affects its behavior of visit on flowers, with potential repercussions on the plant reproductive fitness. To the purpose, the topic was tackled by means of three main approaches: field studies, laboratory assessments, and bibliographic reviews. This research project contributes to two main aspects. First, when insects encounter nectar-like concentrations of a plethora of secondary metabolites in their food-environment, various aspects of their behavior relevant to flower visitation can be affected. In addition, the results I gained confirm that the combination of field studies and laboratory assessments allows to get more realistic pictures of a given phenomenon than the single approaches. Second, reviewing the existent literature in the field of nectar ecology has highlighted how crucial is to establish the origin of nectar biogenic amines to either confirm or reject the multiple speculations made on the role of nectar microbes in shaping plant-animal interactions.

The social construction of cooperation: exchange, identification and collective intentions within the organization

My aim is to develop a theory of cooperation within the organization and empirically test it. Drawing upon social exchange theory, social identity theory, the idea of collective intentions, and social constructivism, the main assumption of my work implies that both cooperation and the organization itself are continually shaped and restructured by actions, judgments, and symbolic interpretations of the parties involved. Therefore, I propose that the decision to cooperate, expressed say as an intention to cooperate, reflects and depends on a three step social process shaped by the interpretations of the actors involved. The first step entails an instrumental evaluation of cooperation in terms of social exchange. In the second step, this “social calculus” is translated into cognitive, emotional and evaluative reactions directed toward the organization. Finally, once the identification process is completed and membership awareness is established, I propose that individuals will start to think largely in terms of “We” instead of “I”. Self-goals are redefined at the collective level, and the outcomes for self, others, and the organization become practically interchangeable. I decided to apply my theory to an important cooperative problem in management research: knowledge exchange within organizations. Hence, I conducted a quantitative survey among the members of the virtual community, “www.borse.it” (n=108). Within this community, members freely decide to exchange their knowledge about the stock market among themselves. Because of the confirmatory requirements and the structural complexity of the theory proposed (i.e., the proposal that instrumental evaluations will induce social identity and this in turn will causes collective intentions), I use Structural Equation Modeling to test all hypotheses in this dissertation. The empirical survey-based study found support for the theory of cooperation proposed in this dissertation. The findings suggest that an appropriate conceptualization of the decision to exchange knowledge is one where collective intentions depend proximally on social identity (i.e., cognitive identification, affective commitment, and evaluative engagement) with the organization, and this identity depends on instrumental evaluations of cooperators (i.e., perceived value of the knowledge received, assessment of past reciprocity, expected reciprocity, and expected social outcomes of the exchange). Furthermore, I find that social identity fully mediates the effects of instrumental motives on collective intentions.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.

Radar based improvements and diagnosis of the convective capabilities of the cosmo-2 model

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

Children’s socialization, involved parenting, and the construction of the family-school partnership in everyday family interactions: a study on parent-assisted homework as a morally dense educational arena

This study investigates an activity that takes place at the intersection between family and school and plays a key role in the building of the family-school partnership largely promoted by education policies: parent-assisted homework. Even though this topic is not new in pedagogical research, what is innovative about this study is the focus on naturally occurring parent-child conversations during homework. Adopting a phenomenological approach to the study of educational events and relying on conversation analysis, the present study analyzes 62 video-recorded sessions of parent-assisted homework collected in 19 Italian families with children aged 6-10 years old (i.e., attending primary school). The analysis of parent-child interactions reveals that parent-assisted homework is not only a site for formal learning but also and primarily a morally dense educational arena. Through the ‘small talks’ that accompany the completion of homework exercises, parents and children evoke and co-construct moral ideologies concerning topics as diverse as learning, school rules and standards, ‘good, involved parenting’, the family-school partnership, children’s autonomy, virtue, time management, and the organization of knowledge and authority in interaction. By taking part in everyday homework interactions, children are educated to culture-specific ethical systems and socialized into morally competent members of their communities, while parents implement the family-school partnership and comply with the model of “involved parent” proposed by pedagogical research and policies. Providing empirical evidence for the moral and educational relevance of ordinary family talk, this study contributes to pedagogical research on family life and promotes parents’ reflexivity about their mundane interactive activities.

Towards Unstructured Knowledge Integration in Natural Language Processing

In the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep learning. In particular, purely data-driven approaches have opened to a wide variety of successful applications due to the large availability of data. Nonetheless, the integration of prior knowledge is still required to compensate for specific issues like lack of generalization from limited data, fairness, robustness, and biases. In this thesis, we analyze the methodology of integrating knowledge into deep learning models in the field of Natural Language Processing (NLP). We start by remarking on the importance of knowledge integration. We highlight the possible shortcomings of these approaches and investigate the implications of integrating unstructured textual knowledge. We introduce Unstructured Knowledge Integration (UKI) as the process of integrating unstructured knowledge into machine learning models. We discuss UKI in the field of NLP, where knowledge is represented in a natural language format. We identify UKI as a complex process comprised of multiple sub-processes, different knowledge types, and knowledge integration properties to guarantee. We remark on the challenges of integrating unstructured textual knowledge and bridge connections with well-known research areas in NLP. We provide a unified vision of structured knowledge extraction (KE) and UKI by identifying KE as a sub-process of UKI. We investigate some challenging scenarios where structured knowledge is not a feasible prior assumption and formulate each task from the point of view of UKI. We adopt simple yet effective neural architectures and discuss the challenges of such an approach. Finally, we identify KE as a form of symbolic representation. From this perspective, we remark on the need of defining sophisticated UKI processes to verify the validity of knowledge integration. To this end, we foresee frameworks capable of combining symbolic and sub-symbolic representations for learning as a solution.