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This chapter challenges middle-class bias in work-life literature by examining work-life balance dynamics through a social class perspective. It reveals class-based disparities in physical, temporal, and psychological outcomes, including the role of economic capital in work-life balance and the challenges encountered by the socially mobile in achieving psychological balance. It emphasizes the need to acknowledge social class implications for work-life balance and urges organizations to address class-based inconsistencies and inequalities in their practices.

This chapter examines the shifting significance of data ownership and athlete rights as they pertain to the growth and expansion of the global sports gambling industry. It provides a nuanced overview of the ‘datafication’ of society, tracing how the omnipresent embrace of digital technologies has expediated new forms of organisational, political and corporate surveillance from which concerns over privacy, rights to ownership and the misuse of personal data arise. The chapter moves on to discuss how the extraction and trade of data has revolutionised how elite sport is performed, manufactured, broadcast and consumed, shedding critical light on the role of the gambling industry in the exchange of human data as a market commodity. These insights inform a series of socio-legal and ethical questions about the relationships between athlete data and the sports gambling industry for the purpose of signposting emerging issues and opportunities for critical sociological research and intervention.

In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches – media literacy, the German “(politische) Bildung” and Freirean “critical pedagogy” – and empirical analyses of online educational resources about datafication.

The study interconnects theoretical analyses with an empirical mixed methods investigation that includes expert interviews with creators of online educational resources about datafication and a qualitative survey with educators interested in teaching about data technologies.

The research identified novel findings on the goals of resource creators and educators, such as a focus on empowering and emancipatory approaches, fostering systemic understanding of datafication and encouraging collective action. Such perspectives are rare in existing critical data literacy conceptualisations but show resemblance to traditional education scholarship. This highlights how much can be learnt from practitioners and from these more established educational approaches. Based on these findings, a framework for critical datafication literacy is suggested that aims for systemic understanding of datafication, encouraging critical thinking and enabling learners to make enlightened choices and take different forms of action.

The study is unique in its interconnection of theoretical and empirical research, and it advances previous research by suggesting a grounded framework for critical datafication literacy.

Mothers play important roles in their families' lives. When they are high performance athletes, they need specific supports that will enable them to excel in their roles as mother athletes. The feminist qualitative research in this chapter is based on data from two studies drawn from semi-structured interviews with elite female distance runners: 14 in 2013–2014 and 11 in 2021. We address two questions: (1) what are the considerations that elite female distance runners make around planning their pregnancy(ies) and family lives? and (2) how have experiences shifted between athlete interviews in 2013–2014 and a new cohort of athletes in 2021? In order to address these questions, we drew on three complementary theoretical approaches: liberal feminism, radical feminism, and strategic essentialism. Further, we then used thematic analysis and generated three broader themes about elite female distance runners that aligned with both cohorts of athletes. First, athletes are forced to plan/strategize their pregnancies around finances, competitions, contracts, and spousal supports due to the lack of support from athletic governing bodies or corporate sponsors. Second, female athletes who choose to have children experience stress and uncertainty in their athletic careers that their male counterparts do not. Third, elite female athletes are demanding that further change occur to address these inequalities, and participants offered a number of potential solutions to improve supports for these athletes. Although solid progress has been noted in the timeframes of our two cohorts, further commitment from athletic governing bodies and corporate sponsors is needed to work toward gender equity in athletics.

The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as artificial intelligence. This paper analyses how DigComp 2.2 defines data literacy and how the framework looks at this from a societal lens.

This study critically examines DigComp 2.2, using the data literacy competence model developed by the Knowledge Centre for Digital and Media Literacy Flanders-Belgium. The examples of knowledge, skills and attitudes focussing on data literacy (n = 84) are coded and mapped onto the data literacy competence model, which differentiates between using data and understanding data.

Data literacy is well-covered in the framework, but there is a stronger emphasis on understanding data rather than using data, for example, collecting data is only coded once. Thematically, DigComp 2.2 primarily focusses on security and privacy (31 codes), with less attention given to the societal impact of data, such as environmental impact or data fairness.

Given the datafication of society, data literacy has become increasingly important. DigComp is widely used across different disciplines and now integrates data literacy as a required competence for citizens. It is, thus, relevant to analyse its views on data literacy and emerging technologies, as it will have a strong impact on education in Europe.

This paper aims to explore how critical digital and data literacies are facilitated by testing different methods in the classroom, with the ambition to find a pedagogical framework for prompting sustained critical literacies.

This contribution draws on a 10-year set of critical pedagogy experiments conducted in Denmark, USA and Italy, and engaging more than 1,500 young adults. Multi-method pedagogical design trains students to conduct self-oriented guided autoethnography, situational analysis, allegorical mapping, and critical infrastructure analysis.

The techniques of guided autoethnography for facilitating sustained data literacy rely on inviting multiple iterations of self-analysis through sequential prompts, whereby students move through stages of observation, critical thinking, critical theory-informed critique around the lived experience of hegemonic data and artificial intelligence (AI) infrastructures.

Critical digital/data literacy researchers should continue to test models for building sustained critique that not only facilitate changes in behavior over time but also facilitate citizen social science, whereby participants use these autoethnographic techniques with friends and families to build locally relevant critique of the hegemonic power of data/AI infrastructures.

The proposed literacy model adopts a critical theory stance and shows the value of using multiple modes of intervention at micro and macro levels to prompt self-analysis and meta-level reflexivity for learners. This framework places critical theory at the center of the pedagogy to spark more radical stances, which is contended to be an essential step in moving students from attitudinal change to behavioral change.

Research and experience show that evidence-based practice (EBP), i.e. using the best available knowledge in daily professional work, is difficult to achieve in social services. The purpose of this study is to understand the development of organizational EBP learning processes in daily work through workplace education for staff and managers of supported homes for people with cognitive disabilities. The authors examine how the EBP model and new knowledge are understood and made actionable in the workplace, applying theories of organizational learning.

The authors used empirical material collected from an EBP workplace education pilot in Sweden, as well as documents on national EBP implementation in Swedish social services. Before the pilot, a focus group interview was conducted with regional senior managers. Participating managers and staff were individually interviewed two to three years after the pilot.

The study illustrates how knowledge-based action emerged from education where EBP was interpreted, understood, reflected on, and tested, supported by codified EBP tools in the work context. The participants, when supervised, and when observing and questioning their own behaviors in practice, contributed to double-loop learning (DLL) processes. Codification of EBP knowledge into useful tools and socialization processes during education and workplace meetings was crucial in developing individual and group DLL and knowledge-based actions.

The bottom-up approach to EBP development and the adaptive contextual learning at the workplace gave new insights into organizational learning in social service workplaces.

The study principally aims to investigate the relationship among work–life balance (WLB), job satisfaction (JS) and employee commitment (EC) among the railway staff by integrating the social exchange theory (SET). The study also explores JS as a mediator in the context of the new normal.

A mixed-method sequential explanatory design was utilized for this study. The research instrument was administered to 533 railway employees, using purposive sampling to ensure reliability and validity. Structural equation modeling (SEM) was employed to analyze the quantitative data and measure mediation effects. Additionally, 15 interviews were conducted with employees from three job positioning groups (A, B and C) to gain further insights into commitment-related concerns.

The study found that WLB and JS positively influenced EC, with JS acting as a mediator between WLB and EC. Furthermore, factors such as fostering friendships among colleagues, effectively managing work–life integration and recognizing the importance of job roles were identified as crucial in enhancing the relationship between WLB and EC.

The study includes SET to examine the social exchange process while considering WLB benefits as a reward from the employer and EC as the outcome of this reward. This study contributes by examining the effects of COVID-19 on the railway industry and EC. The mixed-methods sequential explanatory design gave a comprehensive understanding of the relationships between WLB, JS and EC. The study’s implications highlight the importance of implementing supportive policies, such as flexible work schedules and a supportive organizational culture, to enhance employee commitment and reduce attrition rates. The study emphasizes the significance of prioritizing employee well-being to achieve organizational goals and enhance organizational commitment.

Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making.

This paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment.

Four main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions.

Three notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.