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Based on the sociotechnical systems theory, we examined the human–technology interactions in the context of future works conditioned by machine learning (ML) and artificial intelligence (AI). Skills needed to support career sustainability and the future of the workforce, particularly for the middle-skilled workforce in the contemporary United States America (USA) context, were also studied.

We conducted a scenario analysis to demonstrate the potential roles that human resource professionals may perform to fill the skill gaps given their expertise in the shaping and skilling processes.

Assessing the success of the integration of AI and ML into the middle-skilled workforce requires a multi-faceted approach that considers performance metrics, cost-effectiveness, job satisfaction, environmental impact and innovation. Employees with AI skills can be more competitive in the workforce and forward to high-skilled positions.

Empirical research and related studies focusing on evaluations of reskilling and upskilling processes and outcomes would support career sustainability and the future development of middle-skilled workers.

Through a proactive strategic career development plan with AI integration, middle-skilled workers may enhance their career sustainability and be prepared for future higher-skilled work.

The economic downturn caused by technology-induced unemployment may be addressed by unleashing middle-skilled workforce potentials for future work created by AI and robotics and sustaining economic competitiveness.

This article offers important implications for human resource development theory-minded researchers and scholarly practitioners.

By integrating diverse data sources, we aim to provide a nuanced understanding of the children’s experiences, perspectives and social interactions.

This article describes the development and application of a novel mixed-method approach to researching children’s lifeworlds. The study employs a combination of qualitative interviews, observational techniques and quantitative measures to comprehensively explore the multifaceted aspects of children’s lifeworlds.

Our findings contribute to the growing body of knowledge in childhood studies and inform the design of more responsive and contextually relevant interventions for the well-being of children in various settings.

No research limitations or implications were evident in this research.

This article has demonstrated an innovative approach to investigate children’s lifeworlds through integrating qualitative interviews, observation methods and qualitative measures. Through this comprehensive approach, it provided the means to delve into the intricate dimensions of children’s lifeworlds.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

This paper aims to explore and conceptualize the emotional labor of racial minorities and women in the gig economy.

The paper draws on current research on gig workers' engagement in emotional labor and accounts of unfair practices in the gig economy. It calls out the presence of bias in algorithmic systems used within the gig economy as a means of control and gig worker management. The negative impact of such bias on a specific gig worker demographic is theorized.

Through a review of research on the nature of work in the gig economy, the paper suggests an unspoken mandate exists for gig workers to engage in emotional labor practices. Specifically, the nature of gig work in terms of algorithmic control, coupled with gig work dependence, often creates a need for gig workers to engage in emotional labor. This need is heightened for racial and ethnic minorities and women gig workers.

As gig platforms increasingly rely on algorithms for management and gig workers face biases, this paper offers valuable insights that contribute to a comprehensive understanding of the gig economy's impact on worker well-being. The paper discusses the need for more profound research into the nature of work in the gig economy and the life experiences of gig workers.

This paper has significant implications for organizations and gig workers. Understanding the relationships proposed in this paper can inform organizational strategies to enhance the well-being of gig workers and improve their overall work experiences, potentially leading to increased satisfaction and reduced turnover. Additionally, the paper recommends strategies gig workers can utilize to achieve positive outcomes.

The evolving work landscape, driven by the gig economy, necessitates a thorough understanding of new work dynamics. This paper sheds light on the often-overlooked diversity within the gig workforce, mainly focusing on the unique experiences of women and racial and ethnic minorities.