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The purpose of this paper is to investigate and theoretically explain how line managers and lower-status experts work together in public health-care organizations. Hence, this study explores how lower-status experts influence line managers' decision-making and task prioritizing in order to guide staff experts' cooperation and performance improvements.

The authors used a qualitative method for data collection and analysis of the experts' and line managers' explanations about their cooperation. A theoretical approach of experts' identity positioning, in terms of differences and similarities, was used in analyzing the interaction between managers and experts.

This study shows that similarities and differences in positioning acts exist simultaneously. Similarity is constructed by way of strategic and professional alignment with the line managers' core tasks. Differences stem from the distinction between knowledge-grounded skills and professional attributes such as language, analytical tools, and jargon. Lower-status experts need to leave their entrenched positions and match the professional status of line managers in both knowledge aspirations and appearance to reach a respected approach of experts' identity positioning.

Unlike many previous studies, this study demonstrates that similarities and differences in positioning acts exist simultaneously.

The purpose of this study is to examine the relationship between job characteristics that foster learning (experience with and demand for continuous learning at work, skills variety and autonomy) as potential predictors of self-reported outcomes, such as future learning ability and employee disengagement at work for a cohort of employees with no or very limited job change experience. Further consideration was given to employees’ experiences at work (meaningfulness and recognition at work) as potential mediators in this relationship between job characteristics and employee outcomes.

A cross-sectional design was applied. Participants (N = 284) were recruited from Northern Germany and asked to complete a paper-and-pencil survey. The results were subsequently analyzed using path models to examine direct and indirect effects associated with mediation.

Path model analysis indicated that job characteristics promoting learning at work are positive predictors of self-reported future learning ability and negative predictors of disengagement. Both meaningfulness and recognition predict future learning ability as well. However, these variables only operated as significant mediators in the relationship between job characteristics and employee disengagement (but not self-reported future learning ability).

The study outlines the importance of job characteristics and employee experience to understand employees’ beliefs about their learning ability and engagement at work. The findings highlight the importance of meaningfulness and recognition for employees, as well as the role of learning-supportive job characteristics.

The ongoing “digitalization of work” is one of the major phenomena shaping contemporary organizations. The aim of this study is to explore linguistic constructs of white-collar workers (WCWs) related to their use of digital tools.

The framework of ideological dilemmas (Billig et al., 1988) is mobilized to investigate the conflicting demands WCW interviewees construct when describing the ongoing digitalization of their office work.

This study shows how “digitalization of work” is enforcing an organizational ideological dilemma of structure and flexibility for WCWs. In the digital workplace, this dilemma is linguistically expressed as the individual should be, or should want to be, both flexible and structured in her work.

The use of language exposes conflicting ideals in the use of digital tools that might increase work–life stress. Implications for managers include acknowledging the dilemmas WCWs face in digitalized organizations and supporting them before they embark upon a digitalization journey.

The study shows that the negotiation between competing organizational discourses is constructed irrespective of hierarchical positions; the organizations digital maturity; private or public sector; or country. The study confirms contradictory ideological claims as “natural” and unquestionable in digitalized officework.

The purpose of the current study is to investigate occupational stereotypes among a professional sample of recruiters and other employees on the two fundamental dimensions of warmth and competence.

The authors conducted a survey to collect professionals´ (mostly recruiters´) ratings of preselected occupations. Participants were asked to rate warmth and competence attributes. Factor and cluster analysis were employed to investigate the two-dimensional structure of the warmth/competence space and how and whether occupations cluster as predicted by the stereotype content model (SCM).

Almost all occupations showed a clear two-factorial structure, corresponding to the warmth/competence dimensions. A five-cluster solution was deemed appropriate as depicting how occupations disperse on these dimensions. Implications for stereotyping research, the design of hiring discrimination experiments, and HRM are discussed.

In contrast to previous related research, in which participants select the included occupations themselves, the authors included prespecified common occupations, which should be important for representativeness. In addition, previous research has been conducted in the United States, while the authors conduct this study in a European context (Sweden). Finally, instead of studying students or participants with unspecified work experience, the authors focus on professionals (mostly recruiters).

A growing body of literature shows how intragenerational occupational mobility affects economic dynamics and social stratification. In this article the authors aim to carry out a structured review of this literature, outlining a systemic overview for more comprehensive research and public policies.

The authors use methods from structured literature reviews and network science to reveal the segmented research landscape of occupational mobility literature. The authors made an in-depth analysis of the most important papers to summarize the main contributions of the literature and identify research gaps.

The authors reveal a segmented research landscape around three communities: (1) human capital theory, (2) social stratification theory and (3) migration studies. Human capital research uses microfounded mathematical modeling to understand the relationship between skills and mobility. Nevertheless, it cannot explain social segregation and generally does not focus on the importance of local labor demand. Social stratification research can explain the social and institutional barriers to occupational mobility. Migration research studies the relationship between migration, labor demand and social mobility.

This paper is the first literature review that uses network analysis to perform a systematic review of the intragenerational occupational mobility literature. Moreover, this review identifies opportunities for mutual learning and research gaps in the research landscape.

The purpose of this paper is to characterise the position of highly educated African migrants in the Finnish labour market and to examine the impact of the COVID-19 pandemic on that position.

The paper is based on the biographical work stories of 17 highly educated African migrant workers in four occupation areas in Finland: healthcare, cleaning, restaurant and transport. The sample was partly purposively and partly theoretically determined. The authors used content driven thematic analysis technique, combined with by the biographical narrative concept of turning points.

Using the case of highly educated African migrants in the Finnish labour market, the authors show how student migration policies reinforce a pattern of division of labour and occupations that allocate migrant workers to typical low skilled low status occupations in the secondary sector regardless of level of education, qualification and work experience. They also show how the unique labour and skill demands of the COVID-19 pandemic incidentally made these typical migrant occupations essential, resulting in increased employment and work security for this group of migrant workers.

This research and the authors’ findings are limited in scope owing to sample size and methodology. To improve applicability of findings, future studies could expand the scope of enquiry using e.g. quantitative surveys and include other stakeholders in the study group.

The paper adds to the knowledge on how migration policies contribute to labour market dualisation and occupational segmentation in Finland, illustrated by the case of highly educated African migrant workers.

The article investigates whether and to what extent outsiderness is gendered in Western Europe, both in terms of its spread and degree. It thus explores which male and female post-Fordist social classes are more exposed to the risk of this phenomenon. It also scrutinizes whether such a gendered characterization has varied over time and across clusters of Western European countries.

Relying on a comparative analysis of the data provided by the European Social Survey (ESS) dataset and comparing two points in time – the early/mid-2000s and the late 2010s – the work provides both a dichotomous and continuous variable of outsiderness, which measure its spread and degree in the female and male workforces of a pooled set of growth models.

The empirical analysis shows that outsiderness is profoundly gendered in Western Europe and thus a feminized social phenomenon. However, the comparative investigation highlights that outsiderness has been genderized in diverse ways across the four growth models. Different patterns of gendered outsiderness can be identified.

The article provides a comparative and diachronic analysis of outsiderness from a gender lens, putting into a mutual dialogue different literature on labour market, and shows that outsiderness represents a key analytical dimension for assessing gender inequalities.

This study adopts the popular culture lens to investigate the collective understanding behind the human resources (HR) occupations.

The empirical study analyzes 129 characters from 87 movies, television (TV) series, books and comics. The measurement model was tested using structural equation modeling and cluster analysis identified five HR representations in the popular culture.

Popular culture reflects five HR representations: The Executor, the Hero, the Buddy, the Bore, and the Good-time person. Results suggest that public opinion pays scarce attention to the so-called HR “strategic position” while underlining the need for a more socially responsible HR approach.

The authors' study serves as a means for integrating past research on HR role and reputation, occupational image, self-identity and popular media. While most scholars have addressed popular culture as a single case and paid almost no attention to the HR domain, this article complements the literature by offering a fruitful way to distil HR summative popular culture representations, thus advocating for both a theoretical and a methodological contribution.

In this study, the authors examine whether social capital embedded in individuals' social networks is connected to employees' long-term income development in Finland.

Analyses are based on 25–35-year-old employees from the Finnish Living Conditions Survey of 1994 combined with register data on earned incomes from 1995 to 2016. The authors used questions addressing the frequency of meeting parents or siblings, spending free time with co-workers and participation in associational, civic or other societal activities as measures of the extent of network capital. Ordered logistic model was used to examine whether the size and composition of social networks differ by gender and socio-economic status. Linear growth curve models were employed to estimate the effect of social capital on long-term income development.

Results indicate minor differences in network composition according to gender, but large differences between socio-economic groups. The authors found that income development was faster for those who participated in civic activities occasionally or who met their relatives or co-workers on a monthly basis, that is, for the “middle group”.

Results are generalizable only to Finnish or Nordic welfare state context. The authors’ measures of social capital come from cross-sectional survey. Thus, the authors are not able to address the stability or accumulation of social capital during life course. This restriction will probably cause the authors’ analysis to underestimate the true effect of social capital on earned incomes.

Moderate-level investments to network capital seem to be the most beneficial with regard to the long-term income development.

The study results give support to the idea that social capital can be transformed into economic capital. The results also imply that in economic terms it is important to balance diverse forms of social capital. At the policy level, a special emphasis should be directed to employees with low-socio-economic position. These people are especially vulnerable as their low level of income is combined with network composition that hinders their further income development.

The combined survey and register data give unique insight on how the social capital embedded in individuals' social networks is connected with long-term income development.

Data science promises new opportunities for organizational decision-making. Data scientists arguably play an important role in this regard and one can even observe a certain “buzz” around this nascent occupation. This paper enquires into how data scientists construct their occupational identity and the challenges they experience when enacting it.

Based on semi-structured interviews with data scientists working in different industries, the authors explore how these actors draw on their educational background, work experiences and perception of the contemporary digitalization discourse to craft their occupational identities.

The authors identify three main components of data scientists’ occupational identity: a scientific mindset, an interest in sophisticated forms of data work and a problem-solving attitude. The authors demonstrate how enacting this identity is sometimes challenged through what data scientists perceive as either too low or too high expectations that managers form towards them. To address those expectations, they engage in outward-facing identity work by carrying out educational work within the organization and (paradoxically) stressing both prestigious and non-prestigious parts of their work to “tame” the ambiguity and hype they perceive in managers’ expectations. In addition, they act upon themselves to better appreciate managers’ perspectives and expectations.

This study contributes to research on data scientists as well as the accounting literature that often refers to data scientists as new competitors for accountants. It cautions scholars and practitioners alike to be careful when discussing the possibilities and limitations of data science concerning advancements in accounting and control.