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The aim of this chapter is to investigate the immigrant women entrepreneurship phenomenon in Italy by focusing on the Polish experience. Stemming from the most current data on immigration in Italy and on immigrant women entrepreneurs and women-led firms, by analysing the regions in which these firms are grounded and the economic sectors in which they are mostly involved, this chapter presents the research programme the two authors of this book have been involved in over the last year and the first preliminary results. Specifically, the two authors engaged to compare the experiences, difficulties and opportunities of immigrant women entrepreneurs of different ethnicities/communities located in Italy. The final goal is to analyse if and how the socio-cultural background of these women counts, if and how it affects their way of doing business and what is the influence of the socio-cultural Italian context. The first group of immigrant women entrepreneurs that the authors decided to analyse are the Polish. Accordingly, this chapter presents data on Polish women entrepreneurs based in Italy and the results of an interview with an expert on this community.

This chapter provides preliminary evidence to show that financial accounting students would use generative artificial intelligence (AI) tools to improve their learning if given the opportunity to do so by their instructors. Most students who completed the exercises we used in the study did so diligently and modified their answers after using a generative AI tool in a manner that suggests beneficial effects. It appears that the more prior knowledge a student had about the subject matter, the more beneficial was the experience. Pitfalls still exist, however. For example, students without knowledge of the subject matter struggled with crafting queries and judging the efficacy of their answers. Moreover, although a minority, some students tended to duplicate their original answers without utilizing the responses generated by the generative AI tool. Additionally, certain students merely copied the answers generated by the AI tool without providing any additional critique or analysis. Implications for teaching and learning and opportunities for future research are discussed.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

This chapter offers a critique of the affirmative forms of thought that attempt to ground the ontology of social being through subjective-idealist terms. Some recent examples came in the form of notion of truth grounded in subjects' experience and in rationality of language and discourse. The first part of the chapter demonstrates the perilous implications of such an approach for social theory tasked with ontology and for the conception of truth necessary for its task. The second part scrutinizes the paradigm of society that stems from this subjective-idealist notion of truth and social ontology that adopts discourse, language, and literary metaphors to comprehend social being. As an alternative, the final part of the chapter offers a preliminary sketch of the relation of ontology, normativity, and mediation, as well as the notion of critique necessary for social theory tasked with ontology.

This chapter has aimed to indicate some new important emerging policy problems, which have characterised the Covid crisis in the European economy during 2020 and then the bounce-back in 2021. The chapter has illustrated an economic theoretical framework focussed on innovation and structural changes, according to a Schumpeterian and evolutionary or neo-institutional approach, which seems more appropriate than the traditional neoclassical and macroeconomic models, as the basis for a ‘new industrial strategy’ in the European Union. The mainstream economic models are static and point-like, as they do not consider the role of time and of space, such as the existence of asymmetric information and external economies and also the interdependence between the companies and the other ‘stakeholders’ in the process of economic development. On the contrary, the theoretical framework of this chapter considers the factors that act on the structural changes according to four different and interdependent dimensions: the final demand, the intermediate productions and also the supply of labour and the endowment of natural resources. Finally, some preliminary indications on the organisation of a new industrial strategy at the European scale are discussed, different from the focus on just the digital and green technologies, as indicated by the NGEU program by the European Commission.

Miscarriage is the most common adverse pregnancy outcome, with an estimated one in four pregnancies ending in loss. Despite its prevalence, and significant effects, early pregnancy loss is commonly unacknowledged by organizations, and the intersect of miscarriage experiences while navigating work remains sparsely researched. Available literature, and preliminary research from my Ph.D., reveal stark findings, notably that women commonly conceal miscarriage at work, and when they do disclose, they often experience inconsistent support, or none at all. Minimization, and even discriminatory practice, are commonly witnessed (including inappropriate absence reporting, formal warnings, jeopardization of promotional opportunities, and redundancy). Effective support is often due to empathetic line managers, who sometimes have first-hand experience. Partners are commonly assigned to the “supporter role”, resulting in insufficient leave and support. The absence of formal initiatives, including policy and training, exacerbate the issue. Workplaces that fail to address miscarriage likely face reduced engagement and productivity, and increased absenteeism, presenteeism, and staff turnover. Key recommendations are presented, emphasizing the need for organizations to (i) implement a pregnancy loss policy; (ii) train managers, HR, and colleagues; (iii) provide specialist support; and (iv) tackle pro-natal cultures. Avenues for future research are explored, notably the need to adopt an intersectional lens, and to obtain management/HR and partner perspectives.

This chapter first analyzes how the data-cleaning process affects the share of missing values in the extracted European and North American datasets. It then moves on to examine how three different approaches to treat the issue of missing values, Complete Case, Multiple Imputation Chained Equations (MICE), and K-Nearest Neighbor (KNN) imputations affect the number of firms and their average lifespan in the datasets compared to the original sample and assessed across different SIC industry divisions. This is extended to consider implied effects on the distribution of a key performance indicator, return on assets (ROA), calculating skewness and kurtosis measures for each of the treatment methods and across industry contexts. This consistently shows highly negatively skewed distributions with high positive excess kurtosis across all the industries where the KNN imputation treatment creates results with distribution characteristics that are closest to the original untreated data. We further analyze the persistency of the (extreme) left-skewed tails measured in terms of the share of outliers and extreme outliers, which shows consistent and rather high percentages of outliers around 15% of the full sample and extreme outliers around 7.5% indicating pervasive skewness in the data. Of the three alternative approaches to deal with missing values, the KNN imputation treatment is found to be the method that generates final datasets that most closely resemble the original data even though the Complete Case approach remains the norm in mainstream studies. One consequence of this is that most empirical studies are likely to underestimate the prevalence of extreme negative performance outcomes.

Purpose: This study aims to employ bibliometric analysis to condense multiple studies into a single publication that not only gives insights into the growth and advancement of the research area but also establishes a future research agenda. This study provides a summary of advances in academic research on money laundering. The research includes bibliometric analysis and visualisation of bibliographic data using the Scopus database. The results of the study show that there has been a significant increase in the number of publications in the field of money laundering research, with topics focussed on specific areas. This study will also benchmark existing and preliminary themes, designs, and methodological choices for future money laundering research.

Methodology: With the help of the ‘visualisation of similarities’ (VOS) viewer open-source software, bibliometric analysis was performed using Scopus data. Citation analysis, topic mapping, country collaboration, co-citation analysis, and keyword co-occurrence analysis are some of the approaches used in bibliometric analysis.

Findings: Based on a bibliometric analysis of 1,391 research papers retrieved from the Scopus database over the past three decades (1990–2021), the study identified the most prominent authors, studies, journals, affiliations, and countries in the field of money laundering, as well as the most co-cited authors and journals. The writers also highlight future study issues in the field of money laundering.

Practical implications: The study’s findings might provide academics and practitioners with information on the present state of money laundering research and trend subjects. It can also be used as a guideline for identifying possible research gaps in the existing literature.

Activism in the sport world is often connected to iconic images like the raised fists of John Carlos and Tommie Smith in a Black Power salute at the 1968 Mexico City Olympics or the figure of Cathy Freeman, wrapped in the Aboriginal flag, taking her victory lap at the 1994 Commonwealth Games and the 2020 Sydney Olympics. Activism, be it individual or through collective action, is a contemporary reality in sport. These actions reverberate out, sometimes joining with or magnifying other significant social and political currents to create waves that shift society. They may take the form of supporting mental health conversations, developing sporting infrastructure and support to expand opportunities for the next generation, concerted efforts at changing governance representation, or challenging sexist policy in sports, for example. This chapter draws from a talanoa on activism in Pacific sport, bringing these various activities together in order to surface the activism taking place, and better understand and reframe how we think about sport activism in Pacific communities. On the one hand, we recognize that particular cultural values like humility, respect, and orientations to servant leadership naturally encourage activism in the form of everyday advocacy and grassroots interventions. On the other, we discuss whether these values also prevent more outspoken and disruptive forms of activism which are often required to challenge systems of injustice and enact structural change. In this preliminary look at Pacific activism in sport, we surface some insights and raise questions for future research.