Plutarch's chemistry of stones and metals: conceptions and explanations. With an appendix on the TheSu XML annotation scheme

This dissertation presents a systematic and analytic overview of most of the information related to stones, minerals, and stone masonry which is found in the corpus of Plutarch of Chaeronea, combined with most of the information on metals and metalworking which is connected to the former. This survey is intended as a first step in the reconstruction of the full landscape of ‘chemical’ ideas occurring in Plutarch’s writings; accordingly, the exposition of the relevant passages, the assessment of their possible interpretations, the discussion on their implications, and their contextualization in the ancient traditions have been conducted with a special interest in the ‘mineralogical’ and ‘metallurgic’ themes developed in the frame of natural philosophy and meteorology. Although in this perspective physical etiology could have come to acquire central prominence, non-etiological information on Plutarch’s ideas on the nature and behaviour of stones and metals has been treated as equally relevant to reach a fuller understanding of how Plutarch conceptualized and visualized them in general, in- and outside the frame of philosophical explanation. Such extensive outline of Plutarch’s ideas on stones and metals is a prerequisite for an accurate inquiry into his use of the two in analogies, metaphors, and symbols: to predispose this kind of research was another aim of the present survey, and this aim has contributed to shape it; moreover, a special attention has been paid to the analysis of analogical and figurative speaking due to the nature itself of a large part of Plutarch’s references to stones and metals, which are either metaphorical, presented in close association with metaphors, or framed in analogies. Much of the information used for the present overview has been extracted —always with supporting argumentation— from the implications of such metaphors and analogies.

Weak reasoning argumentative theory. A dialogical approach for the discovery of philosophy in high schools

In the literature on philosophical practices, despite the crucial role that argumentation plays in these activities, no specific argumentative theories have ever been proposed to assist the figure of the facilitator in conducting philosophical dialogue and to enhance student’s critical thinking skills. The dissertation starts from a cognitive perspective that challenges the classic Cartesian notion of rationality by focusing on limits and biases of human reasoning. An argumentative model (WRAT – Weak Reasoning Argumentative Theory) is then outlined in order to respond to the needs of philosophical dialogue. After justifying the claim that this learning activity, among other inductive methodologies, is the most suitable for critical thinking education, I inquired into the specific goal of ‘arguing’ within this context by means of the tools provided by Speech Act Theory: the speaker’s intention is to construct new knowledge by questioning her own and other’s beliefs. The model proposed has been theorized on this assumption, starting from which the goals, and, in turn, the related norms, have been pinpointed. In order to include all the epistemic attitudes required to accomplish the complex task of arguing in philosophical dialogue, I needed to integrate two opposed cognitive accounts, Dual Process Theory and Evolutionary Approach, that, although they provide incompatible descriptions of reasoning, can be integrated to provide a normative account of argumentation. The model, apart from offering a theoretical contribution to argumentation studies, is designed to be applied to the Italian educational system, in particular to classes in technical and professional high schools belonging to the newly created network Inventio. This initiative is one of the outcomes of the research project by the same name, which also includes an original Syllabus, research seminars, a monitoring action and publications focused on introducing philosophy, in the form of workshop activities, into technical and professional schools.

Tree regularized neural networks for key point analysis

This thesis contributes to the ArgMining 2021 shared task on Key Point Analysis. Key Point Analysis entails extracting and calculating the prevalence of a concise list of the most prominent talking points, from an input corpus. These talking points are usually referred to as key points. Key point analysis is divided into two subtasks: Key Point Matching, which involves assigning a matching score to each key point/argument pair, and Key Point Generation, which consists of the generation of key points. The task of Key Point Matching was approached using different models: a pretrained Sentence Transformers model and a tree-constrained Graph Neural Network were tested. The best model was the fine-tuned Sentence Transformers, which achieved a mean Average Precision score of 0.75, ranking 12 compared to other participating teams. The model was then used for the subtask of Key Point Generation using the extractive method in the selection of key point candidates and the model developed for the previous subtask to evaluate them.