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The academic and public debate on social inequality has recently been fuelled by large disparities in income and wealth, profound changes in the labour market, and other emerging cleavages in post-industrial societies. This article contributes to the discussion by arguing that class divisions are theoretically based on four types of capital: people's economic means, their social capital, their cultural resources, and the combination of their health and attractiveness ('person capital'). From this premise, the social structure of the Netherlands is examined. A dedicated survey was linked to microdata from the national population register, tax authorities and benefit agencies. Using latent class analysis, we assess contingencies in the distribution of the different resources, and identify a structure consisting of six capital groups. The established upper echelon (15.5% of the adult population) has the most capital, followed by the privileged younger people (12.7%), the employed middle echelon (26.9%) and the comfortable retirees (16.6%). Total capital is lowest among the insecure workers (13.5%) and the precariat (14.8%). Each social class has a distinctive mix of the four types of capital, highlighting the need to look beyond economic differences in order to comprehend structural inequality. The results of this study also indicate that resource disparities between classes coincide with other forms of social hierarchy and contrasts by age. Moreover, the contemporary class structure is associated with divergent views and experiences among the Dutch. Classes with little capital tend to rate politics, society, and their own social position more negatively. In addition, they value self-enhancement and hedonism less than today's upper classes and report lower levels of well-being.

This study examines differences in benefit receipt using an intersectional approach. Intersectionality theory emphasizes the importance of the interplay of multiple social dimensions. Taking this as a starting point, the paper investigates how different combinations of three demographic variables plus education buffer or amplify benefit receipt and thereby create relatively advantaged and disadvantaged groups. Administrative data were used, sourced from Dutch registers that provide accurate and detailed information on benefit receipt for the entire Dutch population, including small and hard-to-reach segments. Multilevel Analyses of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) are performed to assess which intersectional groups are relatively advantaged or disadvantaged with respect to benefit receipt. Intersectional group differences are more pronounced for social assistance than for unemployment insurance. Complex combinations of education, gender, age and migration background are required to better understand differences in benefit receipt, especially for unemployment insurance.