Parthenope University of Naples
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L’ideologia dell’Albergo dei Poveri di Napoli: fra carità e sviluppo produttivo
No full textLa fondazione del Real Albergo dei Poveri di Napoli, avvenuta nel 1751 per volontà di Carlo III e di sua moglie Maria Amalia di Sassonia, era fortemente rappresentativa della sua funzione di istituzione pubblica, grazie ad una architettura imponente che celebrava la magnificenza dei sovrani. Esso riproduceva il luogo, fisico e mentale, di una complessa integrazione di funzioni reali e simboliche: alla politica di renfermement, si accostava quella dichiaratamente filantropica di ricovero e accoglienza e quella di rieducazione attraverso la pratica del lavoro. La diversificazione dell’edificio e la sua struttura esprimevano le varie parti del programma di reclusione, in particolare attraverso moduli organizzativi di segregazione ispirati ad una logica produttivistica degli spazi dedicati alle arti e ai mestieri. La mistica del lavoro, che si realizzava con la possibilità per gli ospiti di trasformarsi in forza-lavoro, svolgendo attività produttive, mestieri, arti, attraverso l’utilizzo di strumenti di lavoro, laboratori ed officine, rappresentava pertanto un elemento di evidente distacco dagli antichi modelli di carità privata. In tale prospettiva di natura economicistica, si aprivano così nuove possibilità di integrazione con una realtà industriale in formazione, che vedeva il coinvolgimento della mano pubblica nell’incrementare lo sviluppo economico e il tessuto manifatturiero locale.The foundation of the Real Albergo dei Poveri (Royal Hospice for the Poor) in Naples, established in 1751 by Charles III and his wife Maria Amalia of Saxony, was highly representative of its function as a public institution, thanks to its imposing architecture that celebrated the magnificence of the sovereigns. It reproduced the physical and mental space of a complex integration of real and symbolic functions: the policy of renfermement was combined with the openly philanthropic policy of shelter and hospitality and that of re-education through work. The diversification of the building and its structure expressed the various parts of the imprisonment programme, in particular through organisational modules of segregation inspired by a productive logic of spaces dedicated to arts and crafts. The mystique of work, which was realised through the possibility for guests to transform themselves into a workforce, carrying out productive activities, crafts and arts through the use of work tools, laboratories and workshops, therefore represented a clear departure from the old models of private charity. From this economic perspective, new possibilities for integration with a developing industrial reality opened up, involving the public sector in boosting economic development and the local manufacturing fabric
Italian farmers’ preferences for adopting agriculture 4.0 technologies: A choice experiment analysis
No full textDigital (“Agriculture 4.0”) technologies can improve both sustainability and productivity; however, their uptake in Italy remains uneven, partly due to fragmented farm structures and limited digital readiness. Grounded in the Theory of Reasoned Goal Pursuit (TRGP) and underpinned by Random Utility Theory, the study employs a nationwide discrete choice experiment (n = 452, May–June 2024) and a mixed logit model in willingness to pay (WTP) space to quantify Italian farmers’ preferences and WTP for five key attributes: work hours saved, energy saved, water saved, sales increase, and adoption cost. The results show that farmers place the highest WTP on labour and water savings, followed by the prospect of higher sales, whereas energy-saving attributes exert the weakest influence. High adoption costs are a major deterrent, especially for small and medium-sized farms. Interaction effects reveal that farm size, working hours, income, resource use and attitudes towards innovation significantly moderate preferences. The findings highlight the need for differentiated policy packages – combining financial incentives, tailored training, and effective communication – to foster wider and more equitable adoption of Agriculture 4.0 technologies in Italy
Digitalizzazione e intelligenza artificiale: leve strategiche necessarie ma non sufficienti per la semplificazione del Fisco?
No full textIl contributo analizza gli effetti che la digitalizzazione e l’intelligenza artificiale producono
sull’evoluzione del rapporto tra Amministrazione finanziaria e contribuenti, evidenziando
come tali tecnologie incidano tanto sul versante della semplificazione del Fisco
quanto su quello della prevenzione e contrasto all’evasione. L’analisi prende avvio dal
nuovo servizio di consultazione semplificata e si propone di far e emergere le criticità connesse
all’impiego di algoritmi predittivi nella formulazione delle risposte ai quesiti interpretativi. Parallelamente, il contributo analizza
il crescente impiego dell’intelligenza artificiale nell’analisi del rischio fiscale, mettendone
in luce le potenzialità nel rafforzare l’azione di contrasto all’evasione e nel generare, anche
indirettamente, effetti di semplificazione fiscale: la riduzione del tax gap favorisce, infatti,
la stabilità del quadro normativo, riduce il ricorso ad interventi legislativi frammentati e
contribuisce a rafforzare la certezza del diritto. Tali sviluppi richiedono, tuttavia, il pieno
rispetto dei diritti fondamentali del contribuente, quale presidio essenziale del “giusto”
procedimento di accertamento tributario. La trasparenza degli algoritmi, la prevenzione di
effetti discriminatori e l’esercizio di un controllo effettivo da parte del funzionario rappresentano
condizioni necessarie per evitare che la “travolgente forza pratica” degli algoritmi
predittivi finisca per assumere un ruolo dominante nel processo decisionale, nonostante
la c.d. “riserva di umanità” introdotta dalla recente disciplina nazionale sull’intelligenza
artificiale. Solo in presenza di tali garanzie, l’intelligenza artificiale potrà effettivamente
contribuire alla semplificazione del rapporto tra Amministrazione finanziaria e contribuenti,
senza pregiudicare il necessario bilanciamento, ispirato al principio di proporzionalità,
tra efficienza dell’azione amministrativa e tutela dei diritti fondamentali
Profili socio-emotivi degli studenti italiani: differenze di genere, territorio e background familiare
No full textGenAI-Assisted Knowledge Generation: A Case Study on Human-Machine Collaboration Through the SECI Model
No full text- This paper analyses the impact of Generative Artificial Intelligence (GenAI) on the traditional phases of knowledge creation theorized Nonaka’s SECI model. To the purpose, an exploratory single-case study was conducted using semi-structured interviews, direct observation and document analysis within a company operating in the cybersecurity sector and software development. The case company was selected based on its strong innovation orientation, technological culture, and moderate organizational complexity, which are three factors influencing technology adoption in business environments. Interviews were conducted with employees and managers from the R&D and Operations departments, and data were triangulated with secondary sources. Qualitative data were analysed through content analysis methodology, generating an inductive coding tree. The study reveals that GenAI significantly impacts knowledge creation across existing SECI phases. Specifically, while it supports externalization, combination and internalization by facilitating knowledge transformation processes, its impact on socialization presents both opportunities and risks, particularly in the replacement of human interactions. Moreover, results reveal differentiated effects of GenAI across the SECI phases. GenAI enhances externalization, combination, and internalization by supporting the generation of formal templates, code synthesis, report creation and personalized feedback, while its effect on socialization is more ambiguous, raising concerns about critical thinking and the erosion of informal peer learning. These findings suggest that GenAI holds transformative force within knowledge dynamics, offering a unique opportunity to reconsider how human and machine-generated knowledge co-evolve. The paper's novelty and significance reside not only in the analysis of GenAI impact on well-established KM model but also in its capacity to offer organisations interesting insights on effectively integrating it into their workflows
Exploring public discourse on green hydrogen via YouTube comments: A comparative sentiment analysis using VADER and ChatGPT
No full textUnified Sports for Inclusive Education: Assessing Basketball’s Role in Supporting Students with Special Educational Needs—A Pilot Study
No full textThis pilot study evaluates the effectiveness of basketball, implemented according to Uni-
versal Design for Learning (UDL) principles and educational best practices, as an inclu-
sive tool for students with Special Educational Needs in lower secondary school. The re-
search involved 24 adolescents aged 11–14 with Special Educational Needs, who partici-
pated in a structured 30-session basketball program designed to enhance motor, rela-
tional, and individual skills. The program incorporated evidence-based methodologies
such as differentiated instruction, peer modeling, and cooperative activities. Motor tests
and psychometric questionnaires were administered pre- and post-intervention to assess
three key developmental dimensions. Results demonstrated significant improvements
across all three dimensions: relational competencies and individual factors showed equal
progress (+20.8% each), while motor skills showed slightly more modest but still substan-
tial gains (+16.6%). These findings confirm that a structured pedagogical approach can
transform sport into a powerful vehicle for inclusion. The article highlights how the inte-
gration of physical activity, inclusive teaching methodologies, and unified sports repre-
sents an effective strategy to address the complexity of Special Educational Needs
Reimagining Deaf Childhood Education: Integrating Cultural Identity and Technological Innovations for Holistic Learning
No full textEvaluation of SOEC segmented performance through experimental localized fuel electrode multisampling technique
No full textIn this study, a commercial solid oxide electrolysis cell (SOEC) was tested under different operating conditions to evaluate electrochemical performance and thermochemical gradients at the fuel electrode. An innovative test bench with eleven sampling points distributed across the electrode surface enabled in-operando measurements of gas composition and temperature, uncovering performance gradients not detectable by conventional inlet–outlet analysis.Experiments were carried out on a fuel-electrode-supported cell (81 cm2active area), varying inlet flow rate and composition. A simplified electrochemical–thermal model, developed from experimental data and fundamental electrochemical and thermodynamic principles, was validated and used to predict local voltage, current density, and temperature distributions.The results indicate high electrochemical activity near the inlet, with local current densities up to 0.45 A/cm2and thermal gradients of about 4.5 °C across the cell surface.Overall, the study provides new insights into the spatial heterogeneity of SOEC operating parameters and underscores the relevance of localized diagnostics. Such approaches improve the understanding of electrochemical and thermal behavior, supporting strategies to enhance SOEC efficiency and durability