Archivio istituzionale della ricerca - Università degli Studi di Venezia Ca' Foscari
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Documentalidad, virtualidad y memorias del dolor en "La imaginación pública" de Cristina Rivera Garza
No full textIn recent years, theoretical debate around the so-called ‘documentary turn’ has intensified within Latin American literature. In this context, the reappropriation of archives and the political implications of their literary use have become increasingly important. This analysis focuses on the aesthetic and political role of the interplay between virtual documents, such as Wikipedia, and poetry in constructing memories of pain and gender-based violence in Mexico, as depicted in Cristina Rivera Garza’s poetry collection La imaginación pública. The critic shows how the virtual archive effectively embodies intimate experiences through a social language that both amplifies and condenses the text with lyrical undertones
Tutela della biodiversità e specie alloctone invasive
No full textLa sostenibilità è coinvolta sotto il profilo della tutela della biodiversita
Armenia: un paese tra tragedia e speranza
No full textQuesto testo presenta brevemente il contesto storico-culturale dell'Armeni
Prefazione
No full textPrefazione a studio dedicato alla viceneda compositiva dell' "Ambleto" di Giovanni Testor
La storiografia cinese contemporanea : tendenze e prospettive
No full textThis collection of articles examines recent developments in Chinese language historiography, focusing on four key areas: the historiography of the Chinese Communist Party, particularly Mao Zedong's early revolutionary activities; interpretation of the Cultural Revolution; the adoption of Global history in the People's Republic of China; and transformations of historiography produced in Taiwan and about Taiwan
L’ATTUALITÀ DEL CONTRATTO DI RETE COME STRUMENTO DI AGGREGAZIONE TRA (MICRO)IMPRESE
No full textIl contributo torna, a distanza di più di quindici anni dalla suo regolamentazione, sul contratto di rete tra imprese, alla luce dell'interesse costante che la prassi imprenditoriale dimostra per questo strumento di collaborazione tra imprese, valutando anche eventuali potenzialità future dello stesso
Climate risk disclosure and greenwashing: Evidence from Chinese A-share listed companies
Get PDFClimate change is a significant global challenge that affects corporate financial performance, business objectives, and societal sustainability. This study examines the relationship between climate risk disclosure (CRD) and greenwashing among A-share listed companies in China, with a comparison between large and small firms. Using data from the LSEG and CSMAR databases covering the period 2016–2022, we investigate the potential of CRD to mitigate greenwashing. Furthermore, we analyze the moderating role of gender quotas in this relationship. Our findings indicate that CRD can reduce greenwashing and that gender quotas exert a nonlinear moderating effect. This research provides theoretical insights into the direct link between climate risk and greenwashing and offers practical implications for policymakers and regulators seeking to promote sustainable business practices and enhance corporate competitiveness through gender diversity
Engement nella classe d'italiano L2 e Ls.
No full textIl saggio presenta una riflessione sulla didattica centrata sull'engagement ovvero sull'esperienza significativa in termini di apprendimento situato e collaborativo
FanFAIR: sensitive data sets semi-automatic fairness assessment
Get PDFBackground: Research has shown how data sets convey social bias in Artificial Intelligence systems, especially those based on machine learning. A biased data set is not representative of reality and might contribute to perpetuate societal biases within the model. To tackle this problem, it is important to understand how to avoid biases, errors, and unethical practices while creating the data sets. In order to provide guidance for the use of data sets in contexts of critical decision-making, such as health decisions, we identified six fundamental data set features (balance, numerosity, unevenness, compliance, quality, incompleteness) that could affect model fairness. These features were the foundation for the FanFAIR framework. Results: We extended the FanFAIR framework for the semi-automated evaluation of fairness in data sets, by combining statistical information on data with qualitative features. In particular, we present an improved version of FanFAIR which introduces novel outlier detection capabilities working in multivariate fashion, using two state-of-the-art methods: the Empirical Cumulative-distribution Outlier Detection (ECOD) and Isolation Forest. We also introduce a novel metric for data set balance, based on an entropy measure. Conclusion: We addressed the issue of how much (un)fairness can be included in a data set used for machine learning research, focusing on classification issues. We developed a rule-based approach based on fuzzy logic that combines these characteristics into a single score and enables a semi-automatic evaluation of a data set in algorithmic fairness research. Our tool produces a detailed visual report about the fairness of the data set. We show the effectiveness of FanFAIR by applying the method on two open data sets