Affordances and Language: How the Level of Object Familiarity modulates the Manipulation and Categorization of Objects across Development

According to much evidence, observing objects activates two types of information: structural properties, i.e., the visual information about the structural features of objects, and function knowledge, i.e., the conceptual information about their skilful use. Many studies so far have focused on the role played by these two kinds of information during object recognition and on their neural underpinnings. However, to the best of our knowledge no study so far has focused on the different activation of this information (structural vs. function) during object manipulation and conceptualization, depending on the age of participants and on the level of object familiarity (familiar vs. non-familiar). Therefore, the main aim of this dissertation was to investigate how actions and concepts related to familiar and non-familiar objects may vary across development. To pursue this aim, four studies were carried out. A first study led to the creation of the Familiar and Non-Familiar Stimuli Database, a set of everyday objects classified by Italian pre-schoolers, schoolers, and adults, useful to verify how object knowledge is modulated by age and frequency of use. A parallel study demonstrated that factors such as sociocultural dynamics may affect the perception of objects. Specifically, data for familiarity, naming, function, using and frequency of use of the objects used to create the Familiar And Non-Familiar Stimuli Database were collected with Dutch and Croatian children and adults. The last two studies on object interaction and language provide further evidence in support of the literature on affordances and on the link between affordances and the cognitive process of language from a developmental point of view, supporting the perspective of a situated cognition and emphasizing the crucial role of human experience.

"Ancestry, gender and language - The role of culture in economic development"

This thesis is a combination of research questions in development economics and economics of culture, with an emphasis on the role of ancestry, gender and language policies in shaping inequality of opportunities and socio-economic outcomes across different segments of a society. The first chapter shows both theoretically and empirically that heterogeneity in risk attitudes can be traced to the ethnic origins and ancestral way of living. In particular, I construct a measure of historical nomadism at the ethnicity level and link it to contemporary individual-level data on various proxies of risk attitudes. I exploit exogenous variation in biodiversity to build a novel instrument for nomadism: distance to domestication points. I find that descendants of ethnic groups that historically practiced nomadism (i) are more willing to take risks, (ii) value security less, and (iii) have riskier health behavior. The second chapter evaluates the nature of a trade-off between the advantages of female labor participation and the positive effects of female education. This work exploits a triple difference identification strategy relying on exogenous spike in cotton price and spatial variation in suitability for cotton, and split sample analyses based on the exogenous allocation of land contracts. Results show that gender differences in parental investments in patriarchal societies can be reinforced by the type of agricultural activity, while positive economic shocks may further exacerbate this bias, additionally crowding out higher possibilities to invest in female education. The third chapter brings novel evidence of the role of the language policy in building national sentiments, affecting educational and occupational choices. Here I focus on the case of Uzbekistan and estimate the effects of exposure to the Latin alphabet on informational literacy, education and career choices. I show that alphabet change affects people's informational literacy and the formation of certain educational and labour market trends.

Cognition in context: Evidence on affordances and verbal language

This thesis investigated affordances and verbal language to demonstrate the flexibility of embodied simulation processes. Starting from the assumption that both object/action understanding and language comprehension are tied to the context in which they take place, six studies clarified the factors that modulate simulation. The studies in chapter 4 and 5 investigated affordance activation in complex scenes, revealing the strong influence of the visual context, which included either objects and actions, on compatibility effects. The study in chapter 6 compared the simulation triggered by visual objects and objects names, showing differences depending on the kind of materials processed. The study in chapter 7 tested the predictions of the WAT theory, confirming that the different contexts in which words are acquired lead to the difference typically observed in the literature between concrete and abstract words. The study in chapter 8 on the grounding of abstract concepts tested the mapping of temporal contents on the spatial frame of reference of the mental timeline, showing that metaphoric congruency effects are not automatic, but flexibly mediated by the context determined by the goals of different tasks. The study in chapter 9 investigated the role of iconicity in verbal language, showing sound-to-shape correspondences when every-day object figures, result that validated the reality of sound-symbolism in ecological contexts. On the whole, this evidence favors embodied views of cognition, and supports the hypothesis of a high flexibility of simulation processes. The reported conceptual effects confirm that the context plays a crucial role in affordances emergence, metaphoric mappings activation and language grounding. In conclusion, this thesis highlights that in an embodied perspective cognition is necessarily situated and anchored to a specific context, as it is sustained by the existence of a specific body immersed in a specific environment.

Hybrid Artificial Intelligence to Extract Patterns and Rules from Argumentative and Legal Texts

This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach “hybrid”, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both “top-down” structured knowledge and “bottom-up” data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 — i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.

Developing a large scale FrameNet for Italian - The IFrameNet experience

In this thesis we present the development and the current status of the IFrameNet project, aimed at the construction of a large-scale lexical semantic resource for the Italian language based on Frame Semantics theories. We will begin by contextualizing our work in the wider context of Frame Semantics and of the FrameNet project, which, since 1997, has attempted to apply these theories to lexicography. We will then analyse and discuss the applicability of the structure of the American resource to Italian and more specifically we will focus on the domain of fear, worry, and anxiety. We will finally propose some modifications aimed at improving this domain of the resource in relation to its coherence, its ability to accurately represent the linguistic reality and in particular in order to make it possible to apply it to Italian.

Sustainability and environmental impact of the Italian ceramic tile industry

The increasing consumption rates among citizens and the uncontrolled exploitation of natural resources have made environmental pollution and management of waste the main problems facing humanity in its upcoming future. Together with generation of energy and transport, industrial production certainly plays a key role in the genesis of these problems. It is for this reason that the concepts of environmental, social and economic sustainability have emerged over the years as the cornerstones for future development. In light of this, the most forward-looking industries have begun to study their impact on environment and society in order to improve their performances and, at the same time, to anticipate the increasingly rigorous environmental regulations. In this work, various performance indicators related to the Italian ceramic tile sector will be presented and discussed. In particular, the emission factor of characteristic pollutants will be reported on a period of up to fifteen years while data regarding waste management, concentration of pollutants and emission legal limits for the last decade will be here disclosed as a result of a vast analysis on recorded data. The collected information describes the present level of performance of the ceramic tile manufacturing industries in Italy and shows how recycling is now a consolidated reality and how some pollutants, such as particulate matter, fluorine and lead are actually disappearing from production processes and how others, such as volatile organic compounds, are increasing instead. Moreover, the adoption of alternative raw materials for the production of ceramic tiles is discussed and the implementation of the recycling of various waste is addressed at experimental or industrial scale. Finally, the development of a new ceramic engobe with high content of waste glass (20%) is presented as an experimental example of reutilization of resources in the ceramic tile industry.