John Cabot University ScholarShip

Indices to measure the extent and penetration of information in an economy are static measures. Information, however, is a dynamic, expanding resource. Information is produced when data from digital computers articulate with human-generated systems where they are transformed into information. Economic information is effective when it fuels technological innovations contributing to total factor productivity (TFP) growth. This paper develops a theoretical model to measure effective economic information (EEI) as a dynamic process. Using systemic design thinking, design systems in data value chains are embedded within their TFP-information absorption ecosystem. The system’s characteristics of human capital, economic, institutional, and regulatory factors determine the quality and amount of EEI produced. The EEI measurement model uses differential equations allowing for the dynamic expansion of information to include information-knowledge spillovers. Empirical tests for EEI on TFP for EU countries show that EEI is the key driver for TFP growth, while IT investment alone is only a necessary condition. EEI-type measures direct policy attention towards improving TFP-information absorption ecosystems and supporting the adaption of design processes that are more suitable for their TFP-information absorption ecosystems. Both are necessary to connect IT investment to TFP growth.

Objectives. Despite sexual minority (SM), i.e. individuals who identify as lesbian women, gay men, bisexual, or pansexual, individuals presenting worse mental health outcomes when compared to heterosexual individuals, they face more difculties in accessing afrmative and quality health services. This study is a mixed-method non-randomized single-arm trial targeting SM individuals assessing the feasibility and exploratory fndings from an afrmative mindfulness, acceptance, and compassion-based group intervention (Free2Be). Method. Eighteen participants who self-identifed as SM, with a mean age of 30.80 years old, underwent a face-to-face group intervention with 13 weekly sessions (Free2Be). Feasibility was assessed in three domains (acceptability, practicality, and preliminary efectiveness) with self-report questionnaires and hetero-report interviews, during and after the intervention, and using a mixed-methods approach. Using a pre–post and participant-by-participant design, changes were assessed in self-reported internalized stigma, psychopathology indicators, and mindfulness, acceptance, and compassion processes. Results. The Free2Be was acceptable and feasible in all three domains. Participants who completed the intervention (≥80% of attendance) revealed signifcant or reliable decreases in stress and social anxiety symptoms, self-criticism, and fear of compassion for the self. Conclusions. The study provides evidence of the feasibility of the intervention. This afrmative mindfulness, acceptance, and compassion-based group intervention seems to be feasible and acceptable for SM individuals. These promising fndings warrant further investigation within a pilot study.

This survey reviews emerging but fast-growing literature on impacts of artificial intelligence (AI) on entrepreneurship, providing a resource for researchers in entrepreneurship and neighboring disciplines. We begin with a review of definitions of AI and show that ambiguity and broadness of definitions adopted in empirical studies may result in obscured evidence on impacts of AI on en-trepreneurship. Against this background, we present and discuss existing theory and evidence on how AI technologies affect entrepreneurial opportunities and decision-making under uncertainty, the adoption of AI technologies by startups, entry barriers, and the performance of entrepreneurial businesses. We add an original empirical analysis of survey data from the German Socio-economic Panel revealing that entrepreneurs, particularly those with employees, are aware of and use AI technologies significantly more frequently than paid employees. Next, we discuss how AI may affect entrepreneurship indirectly through impacting local and sectoral labor markets. The reviewed evidence suggests that AI technologies that are designed to automate jobs are likely to result in a higher level of necessity entrepreneurship in a region, whereas AI technologies that transform jobs without necessarily displacing human workers increase the level of opportunity entrepreneurship. More generally, AI impacts regional entrepreneurship ecosystems (EE) in multiple ways by altering the importance of existing EE elements and processes, creating new ones, and potentially reducing the role of geography for entrepreneurship. Lastly, we address the question of how regulation of AI may affect the entrepreneurship landscape by focusing on the case of the European Union that has pioneered data protection and AI legislation. We conclude our survey by discussing implications for entrepreneurship research and policy.

The advent of generative Artificial Intelligence (genAI) and large language models (LLMs) will require a sea change in how and what we teach students of all levels. Research strongly suggests that most university students are regularly using it in our courses, so it is incumbent on us to establish norms and best practices in our classes regarding AI use, ethics, and literacy. This strengthening guide provides modular lesson plans for an advanced university-level English Composition course that focuses on the teaching of critical reading and writing as well as information literacy. This guide provides: • practical lessons that address genAI and LLMs and its interaction with Liberal Arts approaches to teaching and learning; • genAI tools to use and suggestions about when to use them in class; and • assignments and assessment rubrics. We argue that the appropriate response to advancements in these technologies lies in the foregrounding of the liberal arts approach and the direct use and exploration of these new tools to enhance that perspective. This requires a shift in teaching that moves from product to process and focuses on critical reading and writing in shorter collaborative bursts that build toward a final written project rather than production of full-length assigned papers to be completed by students at home on their own. This guide was written by an interdisciplinary team of instructors and reference and instruction library professionals at John Cabot University in Rome, Italy. The project was completed in partnership with Parami University through the Open Society University Network and supported in part by a grant from the Open Society Foundations.

A map is a partition of the sphere into interior-disjoint regions homeomorphic to closed disks. Some regions are labeled as nations, while the remaining ones are labeled as holes. A map in which at most k nations touch at the same point is a k-map, while it is hole-free if it contains no holes. A graph is a map graph if there is a bijection between its vertices and the nations of a map, such that two nations touch if and only the corresponding vertices are connected by an edge. We present a fixed-parameter tractable algorithm for recognizing map graphs parameterized by treewidth. Its time complexity is linear in the size of the graph. It reports a certificate in the form of a so-called witness, if the input is a yes-instance. Our algorithmic framework is general enough to test, for any k, if the input graph admits a k-map or a hole-free k-map.

Civic associations are expected to foster civic, pro-social behavior, but this optimistic view is increasingly contested. We argue that populist radical right parties can strategically target and infiltrate associations to diffuse anti-establishment rhetoric and anti-democratic attitudes. We illustrate this phenomenon by examining the relationship between civic associations and compliance with government rules during Germany's first Covid-19 lockdown with a difference-in-differences design. Results show that areas with denser sport, nature, and culture clubs recorded higher mobility under lockdown. We document the infiltration mechanism and the spreading of anti-democratic attitudes within associations, using survey and election data and qualitative evidence including interviews. In doing so, we shed light on a negative effect of social networks and an understudied strategy of challenger populist parties.

The chapter describes the implementation and revision of an instruction training plan developed to assist early-career librarians and librarians with no previous instruction experience with developing the basic skills for teaching information literacy in an academic environment. The case study enters an already existing scholarly conversation, wanting to provide a real-life example of an instruction training program meant to support an on-the-job approach to train new instruction librarians. The instruction training plan developed at John Cabot University was informally developed throughout the years to teach librarians with no previous instruction experience the basics of library instruction with a strong active learning component, due to the fact that most of the training had to happen on the job. Learning the theory and applying it in practice became a need and the major strength of this program, and the need to hire, and therefore train, new instruction librarians, became the opportunity to update and formalize the training plan. The instruction training plan builds its foundations on the ACRL documents and guidelines related to instructional practices, including the Framework for Information Literacy for Higher Education and Roles and Strengths of Teaching Librarians. The training plan focuses on the essential aspects of backward design, developing assessable learning outcomes, creating instructional activities that foster authentic learning, and applying appropriate assessment techniques.

This study explores the influence of customer investors' perceptions on their willingness to invest in sustainable crowdfunding campaigns. Specifically, it examines whether emphasizing a product's direct impact on consumers (B2C) or its broader industrial impact (B2B) affects investment decisions. Using a between-subjects experiment with 304 participants, the research investigates how environmental sustainability activism moderates investment behavior. The study found that higher levels of environmental activism decrease support for B2C campaigns compared to B2B campaigns. These results suggest that sustainability-focused backers prefer projects due to perceived greater systemic impact.

This article revisits the well-known monument of Eurysaces in the context of the Roman funerary landscape. By focusing on its structure and original context, our research demonstrates that the monument, far from being a unicum, instead conformed to contemporary commemorative practices and was in many ways typical. Analysis of comparable monuments and funerary areas, as well as characterization of the concrete used, indicates that the monument of Eurysaces was originally an aedicula tomb with a superstructure, now missing. This reconstruction allows for a more convincing and traditional positioning of the relief images known as “Eurysaces and his wife” at the crowning level of this structure. While our research focuses on the monument of Eurysaces, an important and unexpected result has been the likely identification of several full-length portrait reliefs whose distinctive features suggest that they belong to a previously unrecognized corpus in Rome: aedicular statues. This designation explains the characteristics differentiating them from freestanding statues and helps fill the lacuna of evidence for Rome’s once robust group of funerary structures and ornamentation. The identification of these aedicular statues, in turn, reiterates the fact that aedicula tombs were once popular in the city’s funerary landscape, as they were across the Roman empire.

In this paper we investigate the effect of working-from home (WFH) on job satisfaction. We use longitudinal data from Italy to estimate a difference-in-differences model, in which the treatment group includes individuals who transitioned to remote work in 2020 due to the COVID-19 pandemic and continued to work from home in 2021. We perform the analysis, which extends to various aspects of self-reported job satisfaction, by gender and personality traits as per the Big-Five framework, encompassing Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Our findings reveal that WFH exhibits a positive influence on job satisfaction, albeit exclusively among women, and with some heterogeneity, depending on personal characteristics. Specifically, this effect seems more noticeable in women characterized by elevated Openness to Experience, whereas those with heightened conscientiousness or neuroticism levels tend to experience less satisfaction when working remotely.

Background Schizotypal personality disorder is characterized by a pervasive pattern of maladaptive behavior that has been associated with the liability for schizophrenia. Little is known about effective psychosocial interventions. This pilot non-inferiority randomized controlled trial aimed to compare a novel form of psychotherapy tailored for this disorder and a combination of cognitive therapy and psychopharmacological treatment. The former treatment – namely, Evolutionary Systems Therapy for Schizotypy—integrated evolutionary, metacognitively oriented, and compassion focused approaches. Methods Thirty-three participants were assessed for eligibility, twenty-four randomized on a 1:1 ratio, nineteen included in the final analysis. The treatments lasted 6 months (24 sessions). The primary outcome was change across nine measurements in personality pathology, the secondary outcomes were remission from diagnosis and pre-post changes in general symptomatology and metacognition. Results Primary outcome suggested a non-inferiority of the experimental treatment in respect to control condition. Secondary outcomes reported mixed results. There was no significant difference in terms of remission, but experimental treatment showed a larger reduction of general symptomatology (η2 = 0.558) and a larger increase in metacognition (η2 = 0.734). Conclusions This pilot study reported promising results about the effectiveness of the proposed novel approach. A confirmatory trial on large sample size is needed to provide evidence about relative effectiveness of the two treatment conditions.