Search results

The COVID-19 pandemic has affected women in unique gender-specific ways, particularly their traditional status as home managers. This study aims to draw on the role theory to examine the impact of the COVID-19 pandemic on women's work–family balance during the lockdown.

The current COVID-19 pandemic, which has altered the ways in which we live and work, requires specific methodological tools to be understood. The authors, therefore, opted for an interpretive–constructivist and constructivist–phenomenologist approach. The dataset, thus, comprises of semi-structured interviews with 26 working women in the UK.

The findings illustrate how the COVID-19 lockdown has intensified British women's domestic workload and has, thus, caused unbridled role conflict, which has further been exacerbated by structural and interactional roles undertaken by women, especially during the lockdown. Remote working has contributed to women's role congestion and role conflict and poses severe challenges to role differentiation. Furthermore, we found that the lockdown has facilitated the rediscovery of family values and closeness, which is connected to the decline in juvenile delinquency and low crime rate that has resulted from the lockdown.

Through the lens of the role theory, this study concludes that the cohabitation of work and family duties within the domestic space undermines the ability to achieve work–family balance and role differentiation due to the occurrence of inter-role conflicts. This study enriches our understanding of the effect of remote working on female employees' work–family balance during the unprecedented COVID-19 pandemic lockdown.

Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.

The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.

The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).

As in other systematic literature review studies, the results are limited by the content of the selected papers.

The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.

This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

In transnational families worldwide, different family members have varying degrees of mobility, as well as different physical and emotional experiences with relatives and places throughout their lives. For this reason, in recent decades, increasing attention has been placed upon the experiences of migrants' descendants growing up across borders.

Based on data from a multi-sited ethnography and a survey, this chapter explores the experiences of children growing up in Chinese transnational families split between Zhejiang province and their parents' immigration countries, located mainly in Europe. First, it introduces the migration context and methods, presenting the profiles and basic information of the 77 Chinese migrants' descendants who participated in a ‘Roots-seeking Journey’ summer camp held in their family area of origin in China, in 2018. Second, it explores their heterogeneous early childhood paths and conditions, paying particular attention to mobility, care strategies, intergenerational relations and transnational ties. Finally, this chapter introduces the concept of fluid childhoods, and reflects on the key role of care-related mobility and communication technologies in shaping their early life paths and experiences as well as further transnational engagement.