Conference Agenda

Existing research on the class divide in political attitudes has largely focused on individual class positions, with limited attention given to the role of class-based personal networks. To address this gap, this paper examines the relationship between individual class positions, the class composition of personal networks, and political attitudes toward both socioeconomic and sociocultural issues. I propose two main hypotheses regarding the role of personal networks in shaping political attitudes. First, personal networks may influence political attitudes independently of an individual’s class position. Second, the influence of personal networks on political attitudes may vary depending on an individual’s class position. This study utilizes quantitative data from three waves (2016–2023) of the Chilean Longitudinal Social Survey (ELSOC), a representative panel survey of the urban Chilean population. Explanatory analyses using multivariate regression models reveal that variations in political attitudes are significantly shaped by network composition. Specifically, individuals with heterogeneous networks tend to display more progressive and egalitarian views, while network segregation leads to notable attitudinal differences, particularly across different classes. These findings highlight the critical role of personal networks in understanding how class influences political attitudes.

Over time, the notion of social exclusion has evolved to encompass vulnerability in the sense of exposure to economic insecurity and risk. This is particularly relevant amidst the progressive erosion of the secure, stable career patterns that used to be based on permanent salaried employment, especially in Europe. The recent rise of digital platform work has intensified precarity and poverty risks, reconfiguring inequalities in ways that remain only partially understood.

The proposed presentation operationalises the concept of individual economic vulnerability seen as heightened risk of multidimensional deprivation. We build a composite indicator that incorporates economic-financial and familial factors, along with human capital (education and skills) and social capital (resources embedded within personal networks), both essential for labour market success. Social capital is particularly important as a buffer against precarity, though its distribution may be uneven and contingent on contextual factors.

We harness original data from a survey of online platform workers in France (n = 908, 2018) and Spain (n = 447, 2020-22), using a position generator to measure social capital. Results show that most workers display signs of exposure to economic risk, with distinct sub-groups combining multiple sources of vulnerability. Notably, groups already marginalized by their gender, age, or migration history exhibit the lowest social capital and highest vulnerability. We conclude that non-standard, technology-enabled job arrangements reproduce inherited patterns of inequality and deprivation.

We present new data collected from over forty rural communities around the world to analyse the relationship between material wealth, inequality in wealth, and a variety of social support networks that connect “sharing units” (households) together. These data were gathered as part of the “ENDOW” project (for Economic Networks and the Dynamics Of Wealth inequality, a large US NSF-funded collaboration). The ENDOW communities show immense diversity in their institutional, cultural, and economic arrangements, ranging from farming villages in India to fishing settlements in Ecuador to pastoral groups in Namibia. Anthropologists working with each community have gathered extensive demographic, economic, and social support network data that form the basis of our analyses.

Looking within communities, we find consistent positive associations between sharing unit wealth and both access to support (out-degree) and provisioning of support (in-degree) within the community, and more mixed associations with access to support beyond the community. We also find a form of wealth homophily in that sharing units that have a greater fraction of their connections to wealthy sharing units are significantly wealthier themselves (economic connectedness, Chetty et al 2022). Across communities, we examine how network features predict which sites have greater material wealth inequality. We find that communities that have less economic connectedness (links across wealth levels) have significantly greater wealth inequality. In contrast, we do not find a correlation between the variance in sharing units’ access to or provisioning of support and its material wealth inequality. We discuss the implications of these findings and plans for further explorations.

Social capital theories highlight the importance of social relationships for health outcomes and life opportunities. However, research often relies on aggregate measures, neglecting how specific tie and network characteristics facilitate resource flow, such as social support. Moreover, discussions on the bonding and bridging function of ties primarily focus on how actors bridge different social groups, disregarding place and space. Especially for young adults in deprived areas, outreaching bridging ties can be crucial, as local ties may only offer limited informational or instrumental support. In this study, we analyse how social capital, manifested in ties that are embedded in residential areas and personal networks, is associated with the flow of resources—specifically, the provision of different types of social support to young adults in Switzerland. Using cross-classified multilevel models, we analyse data from the Swiss Federal Survey of Young Adults (CHX-YASS; n = 79,000). Our findings show that some network measures of social capital remain associated with received support after accounting for tie and individual-level covariates. At the individual level, social support depends on demand for receivers and available resources for providers, though this varies across support types. Spatial bridging social capital is associated with more advice and encouragement but not with more emotional support. This study contributes to the literature on social capital and social support by illuminating both social and spatial functions of social capital. The combined consideration of network and residential characteristics enriches our understanding of the interplay of contextual factors in the provision of social support.

Introduction and Aim:

Volunteering is a form of social capital that fosters trust and reciprocity within communities. However, measures of volunteerism often assume uniform experiences across racial groups, overlooking unique perspectives, particularly those of Black individuals. This study aims to quantitatively test for differential item functioning by race (DIF) in survey questions assessing volunteerism and qualitatively investigate reasons for finding DIF.

Methods:

We analyzed publicly available longitudinal data (1995–2016) from the Midlife in the United States Study (MIDUS) (n=6,695). Structural Equation Modeling and Item Response Theory analyses were used to detect DIF by race. Additionally, after identifying DIF items, we performed qualitative interviews (n=47) to explore explanations for DIF.

Results:

Findings revealed racial differences in volunteerism patterns. Black individuals were more likely to volunteer in social organizations (P(χ²,2) = 0.00), while White respondents were more engaged in youth-related work. Several survey items showed DIF by race, particularly “volunteering at schools or other youth-related work” and “volunteering for other relevant organizations or causes.” Qualitative findings reinforced these results, highlighting that Black participants were more often employed by community organizations, reflecting structural and cultural differences in volunteer engagement.

Conclusion:

Our findings emphasize the need for intervention planners and policymakers to account for racial variations in volunteerism. Standard survey measures may inadequately capture these differences, leading to biased assessments of social capital. Future research should refine measurement tools for cultural relevance and examine how structural factors shape racial disparities in volunteer work.

We conduct experimental economic games to study how reputational stake influences people’s decision-making. Players make a series of “Dictator Game” decisions, splitting an endowment between themselves and a recipient. Crucially, recipients are not anonymous strangers but are other community members, presented via photo. By varying the identity of the recipient and whether they will come to know the identity of the donor, we effectively vary the reputational exposure of the donor's decision. We expect that players will be more generous when their decisions have greater reputational stake. This greater reputational stake could come from: the revelation of the donor's identity, the social proximity of donor and recipient, and their respective network positions. We conduct these games in eight rural communities in five countries (India, Colombia, Nepal, Morocco, and Mexico), where we already have full sociodemographic and social network data. This entails over 1500 players and almost 50,000 allocation decisions.

While there is substantial cross-site variation in the average amount given (implying different cultural norms), we find strikingly similar effects of social proximity and revelation across sites. Donors give more of their endowment to friends or friends-of-friends, as opposed to more distant recipients. We further find a small but consistent effect of revelation on Dictator Game allocations: donors give more of their endowment when their identity is revealed, as opposed to being kept anonymous. There is greater heterogeneity in how revelation interacts with social proximity and the network position of donor and recipient, the implications of which we discuss.