5,547 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

    Get PDF

    Undergraduate Catalog of Studies, 2023-2024

    Get PDF

    Gabriel Harvey and the History of Reading: Essays by Lisa Jardine and others

    Get PDF
    Few articles in the humanities have had the impact of Lisa Jardine and Anthony Grafton’s seminal ‘Studied for Action’ (1990), a study of the reading practices of Elizabethan polymath and prolific annotator Gabriel Harvey. Their excavation of the setting, methods and ambitions of Harvey’s encounters with his books ignited the History of Reading, an interdisciplinary field which quickly became one of the most exciting corners of the scholarly cosmos. A generation inspired by the model of Harvey fanned out across the world’s libraries and archives, seeking to reveal the many creative, unexpected and curious ways that individuals throughout history responded to texts, and how these interpretations in turn illuminate past worlds. Three decades on, Harvey’s example and Jardine’s work remain central to cutting-edge scholarship in the History of Reading. By uniting ‘Studied for Action’ with published and unpublished studies on Harvey by Jardine, Grafton and the scholars they have influenced, this collection provides a unique lens on the place of marginalia in textual, intellectual and cultural history. The chapters capture subsequent work on Harvey and map the fields opened by Jardine and Grafton’s original article, collectively offering a posthumous tribute to Lisa Jardine and an authoritative overview of the History of Reading

    Teachers’ Professional Competence for Bilingual (Economic) Education

    Get PDF
    Bilingual education holds great potential to simultaneously nurture bilingualism, biliteracy as well as subject-specific and intercultural competences – all crucial skills for the 21st century. However, the widespread implementation of bilingual education faces challenges such as the lack of learning materials and considerable training needs of active bilingual education teachers. Although teachers’ challenges and pedagogical practices within different content-based bilingual education types like immersion, dual-language education or content and language integrated learning are similar, an overarching and comprehensive overview of bilingual education teachers’ required competences is still missing. To address this research gap and ultimately increase the quality of teacher training, the present dissertation closely examines the required competences of bilingual education teachers for secondary education both in general and in the context of the promising bilingual subject of economics. This investigation incorporates a systematic literature review, a mixed-methods study to accumulate practitioners’ insights into professionalism and a linguistic analysis of learning materials. The systematic review encompassed 79 international reports on bilingual education teachers’ competences, which were categorically grouped and narratively synthesised. A competence model specific to bilingual education teachers was developed based on the converging competences found in the competence frameworks and the reports on individual competences. Important competences included several aspects of language proficiency such as subject-specific or academic language proficiency and additional requirements like critical consciousness, cooperation skills, pedagogical/psychological knowledge of methodology or material design and pedagogical content knowledge. The second study used a mixed-methods design with 32 participants (trainee teachers and teacher educators involved in a bilingual education qualification program) filling in a questionnaire and 11 follow-up interviews with participants teaching political studies or geography bilingually. It compared beliefs about generalist and bilingual education teachers’ professional competences and revealed that bilingual education teachers’ competence requirements were more pronounced. These included expanded language proficiency, international content knowledge and pedagogical content knowledge of merging language, content, learning and culture. Higher motivation and enhanced pedagogical/psychological knowledge of material design, methodology and assessment were also deemed important by practitioners. Notable differences between trainee teachers and teacher educators emerged particularly regarding the importance of reflection and the required level of language proficiency. In the third study, the linguistic complexity of 1529 English main body texts in 30 bilingual economics learning materials was analysed. The results showed a lack of systematic complexity progression across grade levels that can potentially hinder students’ continuous language development. Together with substantial fluctuations in lexical richness and the overall scarcity of ready-made materials, these results highlighted the need for bilingual education teachers to create or adapt their own learning materials. To this effect, language proficiency, pedagogical/psychological knowledge of material design and learning processes, (pedagogical) content knowledge and intrinsic motivation were identified as essential for high-quality material production. The present dissertation furthermore discusses and triangulates the results of the three studies to come up with a competence model specifically targeted at bilingual economic education teachers. Overall, it sheds light on teachers’ competences, challenges and opportunities in the field of bilingual (economic) education. Therefore, this comprehensive dissertation contributes to the enhancement of teacher training for bilingual (economic) education. Additionally, the two competence models developed in this dissertation can be used as reflective tools by interested generalist (economic) education teachers. Finally, this dissertation creates a solid foundation for future research, which overall benefits policy, schools, teachers, students and researchers alike

    Linking language and emotion: how emotion is understood in language comprehension, production and prediction using psycholinguistic methods

    Get PDF
    Emotions are an integral part of why and how we use language in everyday life. We communicate our concerns, express our woes, and share our joy through the use of non-verbal and verbal language. Yet there is a limited understanding of when and how emotional language is processed differently to neutral language, or of how emotional information facilitates or inhibits language processing. Indeed, various efforts have been made to bring back emotions into the discipline of psycholinguistics in the last decade. This can be seen in many interdisciplinary models focusing on the role played by emotion in each aspect of linguistic experience. In this thesis, I answer this call and pursue questions that remain unanswered in psycholinguistics regarding its interaction with emotion. The general trend that I am using to bring emotion into psycholinguistic research is straightforward. Where applicable and relevant, I use well-established tasks or paradigms to investigate the effects of emotional content in language processing. Hence, I focused on three main areas of language processing: comprehension, production and prediction. The first experimental chapter includes a series of experiments utilising the Modality Switching Paradigm to investigate whether sentences describing emotional states are processed differently from sentences describing cognitive states. No switching effects were found consistently in my 3 experiments. My results suggest that these distinct classes of interoceptive concepts, such as ‘thinking’ or ‘being happy’, are not processed differently from each other, suggesting that people do not switch attention between different interoceptive systems when comprehending emotional or cognitive sentences. I discuss the implications for grounded cognition theory in the embodiment literature. In my second experimental chapter, I used the Cumulative Semantic Interference Paradigm to investigate these two questions: (1) whether emotion concepts interfere with one another when repeatedly retrieved (emotion label objects), and (2) whether similar interference occurs for concrete objects that share similar valence association (emotion-laden objects). This could indicate that people use information such as valence and arousal to group objects in semantic memory. I found that interference occurs when people retrieve direct emotion labels repeatedly (e.g., “happy” and “sad”) but not when they retrieve the names of concrete objects that have similar emotion connotations (e.g., “puppy” and “rainbow”). I discuss my findings in terms of the different types of information that support representation of abstract vs. concrete concepts. In my final experimental chapter, I used the Visual World Paradigm to investigate whether the emotional state of an agent is used to inform predictions during sentence processing. I found that people do use the description of emotional state of an agent (e.g., “The boy is happy”) to predict the cause of that affective state during sentence processing (e.g., “because he was given an ice-cream”). A key result here is that people were more likely to fixate on the emotionally congruent objects (e.g., ice-cream) compared to incongruent objects (e.g., broccoli). This suggests that people rapidly and automatically inform predictions about upcoming sentence information based on the emotional state of the agent. I discuss our findings as a novel contribution to the Visual World literature. I conducted a diverse set of experiments using a range of established psycholinguistic methods to investigate the roles of emotional information in language processing. I found clear results in the eye-tracking study but inconsistent effects in both switching and interference studies. I interpret these mixed findings in the following way: emotional content does not always have effects in language processing and that effect are most likely in tasks that explicitly require participants to simulate emotion states in some way. Regardless, not only was I successful in finding some novel results by extending previous tasks, but I was also able to show that this is an avenue that can be explored more to advance the affective psycholinguistic field

    Multidisciplinary perspectives on Artificial Intelligence and the law

    Get PDF
    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Essays on Corporate Disclosure of Value Creation

    Get PDF
    Information on a firm’s business model helps investors understand an entity’s resource requirements, priorities for action, and prospects (FASB, 2001, pp. 14-15; IASB, 2010, p. 12). Disclosures of strategy and business model (SBM) are therefore considered a central element of effective annual report commentary (Guillaume, 2018; IIRC, 2011). By applying natural language processing techniques, I explore what SBM disclosures look like when management are pressed to say something, analyse determinants of cross-sectional variation in SBM reporting properties, and assess whether and how managers respond to regulatory interventions seeking to promote SBM annual report commentary. This dissertation contains three main chapters. Chapter 2 presents a systematic review of the academic literature on non-financial reporting and the emerging literature on SBM reporting. Here, I also introduce my institutional setting. Chapter 3 and Chapter 4 form the empirical sections of this thesis. In Chapter 3, I construct the first large sample corpus of SBM annual report commentary and provide the first systematic analysis of the properties of such disclosures. My topic modelling analysis rejects the hypothesis that such disclosure is merely padding; instead finding themes align with popular strategy frameworks and management tailor the mix of SBM topics to reflect their unique approach to value creation. However, SBM commentary is less specific, less precise about time horizon (short- and long-term), and less balanced (more positive) in tone relative to general management commentary. My findings suggest symbolic compliance and legitimisation characterize the typical annual report discussion of SBM. Further analysis identifies proprietary cost considerations and obfuscation incentives as key determinants of symbolic reporting. In Chapter 4, I seek evidence on how managers respond to regulatory mandates by adapting the properties of disclosure and investigate whether the form of the mandate matters. Using a differences-in-differences research design, my results suggest a modest incremental response by treatment firms to the introduction of a comply or explain provision to provide disclosure on strategy and business model. In contrast, I find a substantial response to enacting the same requirements in law. My analysis provides clear and consistent evidence that treatment firms incrementally increase the volume of SBM disclosure, improve coverage across a broad range of topics as well as providing commentary with greater focus on the long term. My results point to substantial changes in SBM reporting properties following regulatory mandates, but the form of the mandate does matter. Overall, this dissertation contributes to the accounting literature by examining how firms discuss a central topic to economic decision making in annual reports and how firms respond to different forms of disclosure mandate. Furthermore, the results of my analysis are likely to be of value for regulators and policymakers currently reviewing or considering mandating disclosure requirements. By examining how companies adapt their reporting to different types of regulations, this study provides an empirical basis for recalibrating SBM disclosure mandates, thereby enhancing the information set of capital market participants and promoting stakeholder engagement in a landscape increasingly shaped by non-financial information

    Rules, frequency, and predictability in morphological generalization: behavioral and computational evidence from the German plural system

    Get PDF
    Morphological generalization, or the task of mapping an unknown word (such as a novel noun Raun) to an inflected form (such as the plural Rauns), has historically proven a contested topic within computational linguistics and cognitive science, e.g. within the past tense debate (Rumelhart and McClelland, 1986; Pinker and Prince, 1988; Seidenberg and Plaut, 2014). Marcus et al. (1995) identified German plural inflection as a key challenge domain to evaluate two competing accounts of morphological generalization: a rule generation view focused on linguistic features of input words, and a type frequency view focused on the distribution of output inflected forms, thought to reflect more domain-general cognitive processes. More recent behavioral and computational research developments support a new view based on predictability, which integrates both input and output distributions. My research uses these methodological innovations to revisit a core dispute of the past tense debate: how do German speakers generalize plural inflection, and can computational learners generalize similarly? This dissertation evaluates the rule generation, type frequency, and predictability accounts of morphological generalization in a series of behavioral and computational experiments with the stimuli developed by Marcus et al.. I assess predictions for three aspects of German plural generalization: distribution of infrequent plural classes, influence of grammatical gender, and within-item variability. Overall, I find that speaker behavior is best characterized as frequency-matching to a phonologically-conditioned lexical distribution. This result does not support the rule generation view, and qualifies the predictability view: speakers use some, but not all available information to reduce uncertainty in morphological generalization. Neural and symbolic model predictions are typically overconfident relative to speakers; simple Bayesian models show somewhat higher speaker-like variability and accuracy. All computational models are outperformed by a static phonologically-conditioned lexical baseline, suggesting these models have not learned the selective feature preferences that inform speaker generalization

    Linguistically inspired roadmap for building biologically reliable protein language models

    Full text link
    Deep neural-network-based language models (LMs) are increasingly applied to large-scale protein sequence data to predict protein function. However, being largely black-box models and thus challenging to interpret, current protein LM approaches do not contribute to a fundamental understanding of sequence-function mappings, hindering rule-based biotherapeutic drug development. We argue that guidance drawn from linguistics, a field specialized in analytical rule extraction from natural language data, can aid with building more interpretable protein LMs that are more likely to learn relevant domain-specific rules. Differences between protein sequence data and linguistic sequence data require the integration of more domain-specific knowledge in protein LMs compared to natural language LMs. Here, we provide a linguistics-based roadmap for protein LM pipeline choices with regard to training data, tokenization, token embedding, sequence embedding, and model interpretation. Incorporating linguistic ideas into protein LMs enables the development of next-generation interpretable machine-learning models with the potential of uncovering the biological mechanisms underlying sequence-function relationships.Comment: 27 pages, 4 figure

    La traduzione specializzata all’opera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.

    Get PDF
    Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The “Language Toolkit – Le lingue straniere al servizio dell’internazionalizzazione dell’impresa” project, promoted by the Department of Interpreting and Translation (ForlĂŹ Campus) in collaboration with the Romagna Chamber of Commerce (ForlĂŹ-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices
    • 

    corecore