Over the past half-century, structural developments in production systems and labour markets have brought about substantial shifts in the occupational structure. Individuals’ positions within these societal transformations are widely understood to shape their expectations of the future and their political preferences. While the focus in much recent research in this regard has been on occupations’ susceptibility to automation, this study places the level of skill requirements at the centre of the analysis. Using data from the European Social Survey, we find robust support for this perspective. Individuals in occupations with higher skill requirements tend to anticipate fewer personal economic difficulties and hold more positive views about the direction of societal development, while also being less supportive of government redistribution and less inclined to vote for the radical right. In contrast, the theoretically expected relationships between automation-risk measures and these outcomes generally disappear once skill level requirements are controlled for. Our theoretical arguments and empirical findings suggest that the role of automation risk may be overstated in understanding how occupational positions shape social and political outcomes, and that the level of skill requirements carries greater explanatory weight in shaping individuals’ expectations about the future and their political preferences in knowledge societies.

Recent studies on occupational structure and individual mobility suggest that the number of categories in the occupational structure vastly exceeds the limited number of classes in commonly applied schemes (Cheng and Park, 2020; Lin and Hung, 2022; Toubøl and Larsen, 2017; Villarreal, 2020). This discrepancy underscores the inadequacy of coarse class schemes in capturing the complexities of occupational structures. We argue that a continuous, multi-dimensional representation offers a nuanced and efficient tool for understanding research questions across diverse topics such as gendered occupational choices, political views and values, intergenerational transmission of occupational attributes, and the nature and trajectory of structural labor change.Our contribution is to adopt a methodology that allows for the continuous differentiation of occupations across multiple dimensions, rather than confining them to discrete clusters. This approach aligns with the longstanding sociological tradition of representing occupational structures using continuous scales (Duncan, 1961; Cain and Treiman, 1981; Ganzeboom et al., 1992; Chan and Goldthorpe, 2004; Goldthorpe and Hope, 1974; Hadden et al., 2004; Lambert and Griffiths, 2018; Le Grand and Tåhlin, 2013; Prandy and Lambert, 2003; Treiman, 1977).While much of this research focuses on unraveling a primary vertical dimension of occupational structure, linked to class, status, prestige, and educational requirements, others highlight also the horizontal nature of occupational structure by considering gender as a second dimension (England, 1992; Magnusson and Tåhlin, 2023; Shu et al., 1996; McLaughlin, 1978; Wood and Eagly, 2012a). These two dimensions have also been put forward as intertwined in the sense that the dimension of gender also includes a vertical order where men's jobs are seen as more status-worthy (e.g. Charles and Grusky, 2005; Steinberg, 1990). Thus, our expectation is that the occupational structure from an individual mobility viewpoint is governed by at least two dimensions: socio-economic status and a division by gender.The trajectory of literature on occupational structure has evolved from the broad class models like the Erikson's and Goldthorpe's (1992; cf. Wright, 1997) to Weeden's and Grusky's (2005) micro class approach, and more recently, to the analysis of specific occupational traits enabled by the Occupational Information Network (O∗Net) (e.g. Levanon and Grusky, 2016). However, the main weakness of many recent contributions on the topic, particularly those reliant on O∗Net, lies in their preconceived categorization of work content and skills as either masculine or feminine, and their conflation of these traits with a vertical grading of occupations. In contrast, our approach returns to the foundational principles of social stratification research by employing an inductive methodology that distinguishes the core of occupational structure, emphasizing mobility over theoretical preconceptions. We hence rely on the Weberian concept of ‘social class’ for our conceptualization of occupational structure, as encompassing those economic situations between which individual (and generational) mobility is easy and typical (Weber, 1978, p. 57).We ask: What is the number of dimensions that can accurately and parsimoniously represent the occupational structure? Do the main dimensions in the analysis reflect occupational segregation in terms of status and gender? We leverage a comprehensive, nationally encompassing database capturing the majority of occupational changes in the Swedish labor market between 2001 and 2013 to answer these questions. We construct a distance matrix for 95 occupations, which is reduced using Multi-Dimensional Scaling (MDS) techniques (Borg and Groenen, 2005). Subsequently, we rigorously test whether externally derived variables representing occupational status and gender can effectively substitute for the empirically derived dimensions, using constrained MDS.Our findings challenge traditional models by revealing a three-dimensional, continuously rectangular occupational structure. This structure is primarily organized along three distinct dimensions. The first is a vertical dimension, strongly associated with socio-economic status, which we interpret as representing the level of "Educational Certification" required to enter an occupation.The second dimension captures a distinction along a "Nature vs. Urbanity" spectrum. Here, "Nature" refers to occupations involved in extracting resources (e.g., food, materials, crafts, energy) or a scientific understanding of natural phenomena (e.g., physics, biology). By contrast, "Urbanity" encompasses roles more closely tied to administrative, service-oriented, or industrial settings.The third dimension distinguishes between "Caring vs. Technical" roles. Caring roles involve providing emotional support, consideration, and guidance, while technical roles are centered on machinery, production, and engineering. Although this dimension is correlated with the proportion of females in these occupations, our analysis demonstrates that gender segregation in a physical sense of the term is not a crucial feature of the occupational structure.

There is a conception that contemporary work lives become ever more complex. Pioneering research has indicated that work lives have indeed become more complex, yet at a modestly increasing pace. This paper uses Swedish registry data across an exceptionally long time period, including cohorts born from 1931 to 1983. The following conclusions are drawn using state-of-the-art methods of measuring sequence complexity. For early-careers, an increasing complexity trend is evident between the 1950s and 1960s birth cohorts, yet complexity fluctuates around a stable trend for the 1970s birth cohorts and onward. For mid-careers, which are considerably more stable on average, complexity has decreased among women born between the 1930s and the early-1950s. However, the opposite trend holds true for men, resulting in a gender convergence in work complexity. We observe a subsequent standstill of the mid-career complexity trend across both genders, followed by a modest decline for the last observed cohorts. Analyses point to educational expansion as an important driver of the initial increase of early-career complexity. Taken together, this study affirms an initial shift to more work life complexity in the twentieth century, yet we find no unidirectional trend toward more complexity over the last decades.

Research suggests that structural change drives occupational mobility in high-income countries over time, but two partially competing theories explain how such change occurs. One suggests that younger cohorts replace older ones through higher education, and the second suggests that individuals adapt to structural change by switching from declining to new or growing occupations during their careers. A proposed occupational scheme aligns with the two dimensions of structural change - skill upgrading on the vertical axis of occupational differentiation, increasing demand for data comprehension (i.e. high skill) and primary tasks concerning either people or things on the horizontal axis. Applied to career trajectories in the Swedish labour market, sequence analyses of the scheme suggest stability in attainment of career mobility types over time between consecutive birth cohorts, and considerable evidence for within-career manoeuvring. Analyses address heterogeneity along parental class and gender.

This study advances the analysis of cognitive skill use at work by considering another crucial factor: the motivation-to-learn (MtL). Previous research has indicated that MtL forms cognitive skills in the school setting. However, the role of MtL in the work setting is much less understood. The present study analyses the association between MtL and cognitive skill use in three major European labour markets: Germany, the Netherlands, and the United Kingdom, using the Programme for the International Assessment of Adult Competencies (PIAAC). Findings from a regression analysis of cognitive skill use on MtL and various control variables show that the independent contribution of MtL is about as important as the combined contribution of literacy/numeracy proficiency, although a decomposition analysis reveals further insights about how MtL, literacy/numeracy proficiency, and education intersect each other in the determination of cognitive skill use. The found association is remarkably stable across different samples and model specifications. Some heterogeneities are however revealed, such as a larger relative importance of MtL among the low-educated in the Netherlands. The findings are interpreted in light of contemporary theory on institutional regimes, concentrating on cross-country differences in on-the-job training prevalence.

Work learning is the skills and the knowledge that is generated from work practices and in exchange of information at work. While there are good reasons to fear that frequent job changers do not learn thoroughly at work, it is also conceivable that the experience of many types of jobs instead yields greater learning. Despite this issue’s significance for on-going discussions in research and policy, thorough analyses of it are surprisingly sparse. In this study, we test whether job mobility is positively or negatively associated with subsequent work learning using data from two Swedish representative datasets (LNU and PIAAC). In order to substantiate both claims, we utilize a wide array of research on human capital, job matching, labor market segmentation and learning motivation. We analyze a broad set of indicators of work learning and show that job mobility in general is associated with greater total subsequent learning than is job stability. 

Across European countries, immigrants are disadvantaged in labor market attainment relative to natives: foreign-born individuals are less likely to be employed and more likely to be unemployed. Previous research indicates that immigrants’ employment chances are better when the share of low-skill jobs in the labor market is large. Upgrading of the job structure, which has taken place in many countries over recent decades, might therefore have hurt immigrants’ employment prospects. However, an exclusive focus on skill demand neglects another important development in the skill structure of advanced economies: educational expansion. The rapid rise in skill supply has tended to outpace the decline in the low-skill job share with increasing over-education as a consequence, potentially leading to crowding-out of immigrant workers from employment. Based on data from the European Union Labour Force Surveys (EU-LFS) 2004-2016, we perform analyses that jointly consider the demand and supply sides of labor markets. Our results indicate that the size of the low-skill job sector is positively related to immigrants’ employment if and only if those employed in the low-skill sector have low qualifications. In economies with high rates of over-education, where many well-educated natives occupy low-skill jobs, the labor market prospects of immigrants deteriorate.