Keywords

Neighbourhoods as Meso-level Contexts of Vulnerability

Over the last few years, the LIVES program has developed a theoretical framework that defines vulnerability as ‘as a process of resource or reserve loss or insufficiency in one or more life domains’ (Spini & Widmer, in this volume). When exposed to an individual or social stressor, vulnerable persons do not have the reserves to cope with the stressor and are unable to (rapidly) recover from stress (Cullati et al., 2018). The central concepts in the LIVES approach to vulnerability—exposure to stressors and endowment with resources and reserves—are not purely individual concepts but depend on contextual factors. Usually, these contextual factors are studied at the macro-level; for example, a country’s culture, economic situation or welfare policies have been found to shape the dynamics of vulnerability in daily life (e.g., see Cheung & Chan, 2007). While such macro-level contextual factors undoubtedly exert a critical influence on the risk of becoming vulnerable, we are all embedded within multiple layers of social relations below the country level. As Elder et al. suggest, individuals are not just national citizens but also residents of particular neighbourhoods and members of particular groups and communities. The local context is an important determinant of social inequality. For instance, living in a neighbourhood with concentrated poverty increases crime and reduces educational attainment, well-being and employment chances. We believe it is important not to neglect these so-called meso-level contexts or local contexts (Ranci, 2009).

According to Spini and Widmer (in this volume), a focus on the meso-level makes us aware that ‘vulnerability is not just individual but also impacts close connections, who amplify, share or suppress the effects of stressors and who bring or share needed resources’. In this contribution, we show how meso-level integration is necessary for the understanding of vulnerability processes. Specifically, we argue that the dynamic between resources and stressors is shaped by the local contexts within which individuals are embedded: in personal networks (that provide support or information), in social groups (that purvey collective identities and meaning), or in neighbourhoods (that structure daily routines and shape the experience of social structures). The moderating function of the meso-level seems particularly important to us as it can not only activate or reinforce processes of vulnerabilisation but also weaken, transform, or nullify the effects of stressors (Vacchiano & Spini, 2021).

In the next three sections, we discuss the added value of the integration of the meso-level for the study of vulnerability. We first show how meso-level labour market contexts can substantially alter the size of the penalties associated with low levels of educational attainment or a more disadvantaged background for young people seeking employment for the first time. Second, we examine the role of local networks and neighbourhood deprivation for unemployment duration. Third, we investigate how people residing in zones with higher levels of income inequality perceive others as being more competitive and how such perceptions can affect their health.

Local Economic Structures and Vulnerability in the School-to-Work Transition

Moments of transition, from one stage of the life course to another, are moments of heightened exposure to stressors. The transition from school or university to the world of work—where young people leave behind the fixed and familiar certainties of teachers, timetables and classes and seek employment—is one such moment (Schoon & Silbereisen, 2009). For some, the process of finding stable employment is a relatively swift and trouble-free affair. Others, however, face long periods of unemployment, inactivity or employment in insecure positions. These experiences have immediate consequences in terms of lost income and delayed independence and are also associated with a host of negative outcomes in middle age, including include higher unemployment, lower wages, worse outcomes in terms of mental and physical health and higher risk of premature death.

The multifaceted, enduring and costly nature of these so-called ‘scarring effects’ is such that there is a clear need to understand who is most vulnerable to ‘bad beginnings’ in the labour market. Sociological frameworks typically view vulnerability through a micro-macro lens that overlooks meso-level influences. The ‘transition regimes’ framework (Smyth et al., 2001), for instance, holds that vulnerability reflects the interaction between the micro-level resources and attributes of labour market entrants and macro-level institutional arrangements, which are assumed to be uniform at the country level (Raffe, 2014). This view offers invaluable insight into the sources of lingering cross-national differences in vulnerability among young people. However, there are also indications that it produces a misleading picture of the individual-level drivers of vulnerability and resilience.

Contrary to the implicit assumptions of much research on the school-to-work transition, uneven processes of economic growth and industrial restructuring have given rise to substantial variation in the number and range of occupational opportunities in any given location. Analysis that reflects the reality of this profound meso-level variation has shown that the local employment opportunity structure can substantially moderate—and, indeed, sometimes even nullify—the size of the youth labour market penalties associated with the core micro-level vulnerabilities of low educational attainment and a more disadvantaged family background.

For example, while individual educational attainment is widely recognised to be ‘the single most important determinant of occupational success in industrialized societies’, our analysis of British Household Panel and German Socio-Economic Panel data showed that the strength of the education-destination gradient varied substantially within the United Kingdom and Germany (Morris, 2021). In strong local economies such as Cambridge and Hamburg, young people obtain employment with relative ease irrespective of their highest level of educational attainment. However, gaps—between the less qualified and between the most and least qualified—appear and grow as local economic performance worsens. On average, it takes young people with low qualifications between one and three months longer to find employment of any sort if they are located in a place of low rather than high labour demand, and the job search time gaps between most and least qualified in weak local economies are substantial (Fig. 9.1).

Fig. 9.1
Two line graphs of time in months versus local unemployment rate in the United Kingdom and Germany. 3 lines, low quals, medium quals, and high quals increase, with low quals having the highest peak data.

Predicted median time in months to first job in the UK and Germany after leaving full-time education and training

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A similar story emerges when considering the intergenerational transmission of (dis)advantage at labour market entry. Net of educational attainment, young people have an equal probability of finding employment and securing a good first job in strong local labour markets within the UK and Germany, irrespective of their social origins. However, those in weak labour markets such as Hull and Gelsenkirchen are 12-15 percentage points less likely to find employment within a two-year period, and those who do so obtain first jobs that are 5-8 ISEI pointsFootnote 1 lower in occupational status if their parents are care workers rather than secondary school teachers. Young people who are not bumped out of the labour market are bumped down into first jobs that likely offer fewer opportunities for progression over the later life course.

These findings highlight the relevance of the meso-level economic structures within which young people are embedded for understanding who is most at risk of bad beginnings in the labour market. Individual resources are undoubtedly the most important component of both vulnerability and resilience, but meso-level opportunity structures can both amplify and mitigate the risks associated with low educational attainment or a more disadvantaged family background.

Neighbourhood Deprivation and Unemployment: The Role of Social Interactions in the Neighbourhood

Several studies have demonstrated that living in a poor neighbourhood increases the risk of and duration of unemployment (Buck, 2001), independent of one’s individual labour market and socioeconomic characteristics (Buck, 2001; Miltenburg & Van de Werfhorst, 2017). In the same vein, relocating residents from more- to less-deprived neighbourhoods improved their employment outcomes in the long run (Mendenhall et al., 2006). While research has convincingly demonstrated that neighbourhood disadvantage affects employment, the mechanisms through which this operates have been less explored. Inhabitants of disadvantaged neighbourhoods may face more unemployment for three main reasons: spatial mismatch, neighbourhood discrimination, and social interactions (Galster, 2012; Sampson et al., 2002). Jobs may be less available in deprived neighbourhoods, and transport connections to places with better employment chances may be bad (spatial mismatch). Job seekers from disadvantaged neighbourhoods may face discrimination from employers on the basis of the stigma associated with their neighbourhood (neighbourhood discrimination), they may lack connections to people who can provide them with information about job opportunities or other help in the job search process, or they may put less effort into the job search due to neighbourhood peer influences (social interaction mechanism).

Whereas there is a good account of these mechanisms of neighbourhood disadvantage, it is more difficult to disentangle them in empirical research, and most studies are limited to demonstrating that neighbourhoods matter without explicitly examining the mechanisms influencing their significance. In particular, the social interaction mechanism is simply often assumed to be important without being explicitly measured. Neighbourhood deprivation and neighbours as part of personal networks are rarely examined simultaneously in empirical population-level research (Desmond & An, 2015; Fernandez & Su, 2004). One reason may be that the literature on neighbourhood effects and the literature on network effects have developed largely separately. The neighbourhood effects literature has shown that residential neighbourhoods affect their inhabitants’ life chances and choices, but it has rarely included good measures of social networks and interactions (Galster, 2012; Sampson et al., 2002). The social networks literature, by contrast, has examined the properties of social networks and how these affect socioeconomic outcomes, usually without a focus on the geographical location of personal networks (Granovetter, 1995; Portes, 1998). More recent contributions, for instance, from Brändle (2018) or Ganjour et al. (2020), have examined the geographical and structural aspects of personal networks and have shown that these networks are, indeed, often local.

We conducted an integrated study of personal networks and neighbourhoods with population-level data from the UK Household Longitudinal Study, also known as Understanding Society (Vandecasteele & Fasang, 2020). The data include a measure of the proportion of friends who live in the same neighbourhood as well as small-scale information on specific dimensions of neighbourhood deprivation. Figure 9.2 shows the probability of ending an unemployment spell by neighbourhood employment deprivation as well as the share of friends in the local area. The results showed that neighbourhood employment disadvantage prolonged unemployment, but only for individuals who reported that all of their friends live in the same deprived neighbourhood (darker line). By contrast, the predicted probabilities in Fig. 9.2 show that living in an advantaged neighbourhood with all of one’s friends in the neighbourhood improved the chance to exit unemployment.

Fig. 9.2
A line graph with error bars represents the unemployment exit versus percent unemployment-deprived in the neighborhood. 2 lines, less than half, and all exhibit decreasing trends, but the less than half data set has a less steep drop compared to all.

Predicted probabilities of exiting unemployment between 2011 and 2012 by neighbourhood deprivation and proportion of friends in the neighbourhood (Vandecasteele & Fasang, 2020)

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Consequently, it is not only residing in a disadvantaged neighbourhood but also having social connections there that prevents individuals from re-entering employment. In contrast, neighbourhood location is not associated with unemployment exit if one’s friends do not live in the same neighbourhood. Our study is the first to find evidence with population-wide panel data that neighbourhood effects on employment outcomes depend on the location of personal networks. These results thus show support for the importance of the social interaction mechanism of neighbourhood disadvantage. It could be argued that resource-sharing and norm-setting in neighbourhoods exacerbate vulnerabilisation processes in deprived local settings. Hence, at least for employment chances, local connections to other deprived people may add to the cumulative disadvantage experienced by economically vulnerable population groups.

The Effects of Local Income Inequality on Psychological Health

Over the last two decades, many countries have seen dramatic increases in income inequality (e.g., see Saez, 2019). Given the scope of this phenomenon, many scholars have wondered whether income inequality acts as a contextual stressor and impairs psychological health (for recent reviews, see Buttrick & Oishi, 2017). However, this body of research has produced mixed results: In particular, the effects of income inequality on psychological health outcomes seem to be largely inconsistent (for a meta-analysis, see Ngamaba et al., 2017).

We believe that one of the reasons for these inconsistencies is that most extant studies have operationalised income inequality at broad levels of aggregation (e.g., national income inequality). However, we know that individuals systematically misestimate the magnitude of macro-level income inequality (e.g., within their countries), whereas they perform much better when estimating the magnitude of meso-level income inequality (e.g., within their ZIP code or municipality; see Johnston, & Newman, 2016: 175-177).

We conducted three series of studies using meso-level income inequality as a predictor, with the aim of resolving some inconsistencies in the literature on income inequality and psychological health. Our theoretical starting point was as follows: In economically unequal (vs. equal) local contexts, the poor and the rich are mechanically further away from one another on the pay scale, which makes standards of income comparison more salient (e.g., the rich are more noticeable in the residential context and become recurrent targets of economic comparison; for empirical evidence, see Payne et al., 2017). As such, meso-level inequality could prompt concerns about one’s relative position in the economic hierarchy and induce the perception that everyone around oneself is competitive.

A first series of studies tested the association of meso-level inequality with perceived competitiveness in the United States (Sommet et al., 2019). We asked 2,500+ U.S. residents to report the level of perceived competitiveness in their area on a scale comprising items such as ‘In my town/city, it seems that people are competing with each other’; then, we gathered the Gini coefficient of the ZIP code where each participant lived.Footnote 2 The Gini coefficient was found to be a consistent and robust predictor of perceived competitiveness: The higher the meso-level inequality, the higher the perceived competitiveness.

In a second series of studies, we went one step further and examined the downstream consequences of the inequality-competitiveness link on psychological health (Sommet et al., 2020). Drawing on the LIVES framework (see Spini and Widmer in this volume), we reasoned that the perceived competitiveness induced by income inequality should act as a social stressor and evoke both (i) avoidance-based psychological processes (focused on the risk of falling behind the competition) and (ii) approach-based psychological processes (focused on the possibility of getting ahead of the competition). To test this idea, we conducted a two-year longitudinal study with 1,700+ U.S. residents (median age = 48) recruited through a national volunteer research registry named ResearchMatch (see Harris et al., 2012). The Wave 1 (2016) to Wave 2 (2017) response rate was approximately 75%. We showed that an increase in the Gini coefficient of the participants’ areas was associated with an increase in perceived competitiveness over time. More importantly, we showed that this increase led to opposing effects on psychological health: Meso-level income inequality had both a negative indirect effect on psychological health via avoidance-based psychological processes (focused on avoiding failure) and a positive indirect effect on psychological health via approach-based psychological processes (focused on attaining achievement).

In a third and final series of studies, we sought to examine the conditions under which meso-level income inequality impairs rather than improves psychological health (Sommet et al., 2018). This time, we reasoned that the contextual stressor of perceived competitiveness induced by income inequality should be particularly threatening for individuals with low monetary reserves (i.e., facing financial scarcity: having insufficient monetary resources to cover monthly expenses; Mullainathan & Shafir, 2014). To test this idea, we pooled the responses from the Swiss Household Panel, a nationally representative panel survey that followed approximately 15,000 participants from 1,700+ municipalities over 15 years of assessment. We showed that an increase in meso-level income inequality (i.e., the Gini coefficient of the municipality of residence) over the life course led to an increase in psychological health problems only for people facing financial scarcity (approximately 10% of the Swiss population; see Fig. 9.3).

Fig. 9.3
A line graph of psychological health problems versus Meso level income inequality in the Gini coefficient of the municipality residence. The scarcity line increases steeply, while the equilibrium and abundance lines decrease gradually.

Effects of meso-level income inequality over the life course on psychological health as a function of monetary reserves

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Conclusion

Our findings, whether on the school-to-work transition, unemployment or psychological health, have one common denominator: They show that meso-level structures such as local contexts or neighbourhoods are of crucial importance to understand vulnerability as a dynamic of stressors and resources. It is in the local context that social stress is experienced, but it is also at this meso-level that people have access to resources that allow them to mitigate or nullify the impact of macro-level structures or individual characteristics.

In our study on the school-to-work transition, we showed that meso-level structural opportunities and resources crucially influenced how young people are able to handle such stressful biographical transitions—these resources can mitigate or in some cases even nullify individual disadvantages, such as low qualifications. Unemployment is one of the major social stressors of modern societies. In a second study, we showed how the effectiveness of resources connected to personal networks—information about job opportunities or help for the job search—depended substantially on their spatial distribution. In a deprived neighbourhood, those who reported all their friends as also living in the neighbourhood faced prolonged unemployment. Only for those living in a privileged neighbourhood did a high share of the personal network living nearby become a resource allowing them to exit unemployment. High local income inequality increased the perception that everyone around oneself is competitive. This perceived competitiveness can be conceptualised as a social stressor, especially for people living in unequal contexts. Our third case shows that an increase in meso-level income inequality led to an increase in psychological health problems, but only for people facing financial scarcity.

In terms of social policy, this finding means that the local level is particularly suited for interventions to buffer the main macro-sociological risks of vulnerability. It is the level at which people can be empowered to acquire and accumulate resources that protect them from vulnerability in the long term. For instance, policies supporting young people when entering the labour market should be adapted to regional specificities and reinforced in regions with a weak labour market. Regional and local policies, especially in regard to residential policies, should aim at blending populations across economic fault lines. Such an approach will help mitigate situations of vulnerability and reinforce the buffering effects that local contexts may have on social stressors.