Nonprofits offer services to disadvantaged populations, mobilize collective action, and advocate for civil rights. Conducting this work requires significant resources, raising the question: how do nonprofits succeed in increasing donations and volunteers amid widespread competition for these resources? Much research treats nonprofits as cold, rational entities, focusing on overhead, the “price” of donations, and efficiency in programming. We argue that nonprofits attract donors and volunteers by connecting to their emotions. We use newly available administrative IRS 990 e-filer data to analyze 90,000 nonprofit missions from 2012 to 2016. Computational text analysis measures the positive or negative affect of each nonprofit’s mission statement. We then link the positive and negative sentiment expressed by nonprofits to their donations and volunteers. We differentiate between the institutional fields of nonprofits—for example, arts, education, social welfare—distinguishing nonprofits focused on social bonding from those focused on social problems. We find that expressed positive emotion is often associated with higher donations and volunteers, especially in bonding fields. But for some types of nonprofits, combining positive sentiment with negative sentiment in a mission statement is most effective in producing volunteers. Auxiliary analyses using experimental and longitudinal designs provide converging evidence that emotional language enhances charitable behavior. Understanding the role of emotion can help nonprofit organizations attract and engage volunteers and donors.

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Of 728,997 hospitalizations meeting inclusion criteria, 30-day unplanned returns occurred for 96,007 children (13.2%). After adjustment, the patterns of returns were significantly associated with COI. For example, 30-day returns occurred for 19.1% (95% confidence interval [CI]: 18.2, 20.0) of children living within very low opportunity areas, with a gradient-like decrease as opportunity increased (15.5%, 95% CI: 14.5, 16.5 for very high). The relative decrease in utilization as COI increased was more pronounced for ED revisits.

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This book chapter in the Oxford Handbook of Social and Political Trust provides an overview of theory relating participation in voluntary associations to increased levels of trust. It highlights theory that explains how trust is generalized to individuals outside of associations, theory that distinguishes among types of associations in their ability to produce generalized trust, and additional theory that refutes these claims. The chapter also introduces new theory that combines the two most common distinctions—bridging versus bonding associations and connected versus isolated associations. The end of the chapter documents how each of the theories and mechanisms have been supported, challenged, or neglected in existing empirical evidence and concludes with recommendations for how to test theories on trust and participation moving forward.

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In the 1930’s, the Home Owner Loan Corporation (HOLC) drafted maps to quantify variation in real estate credit risk across US city neighborhoods. The letter grades and associated risk ratings assigned to neighborhoods discriminated against those with black, lower class, or immigrant residents and benefitted affluent white neighborhoods. An emerging literature has begun linking current individual and community health effects to government redlining, but each study faces the same measurement problem: HOLC graded area boundaries and neighborhood boundaries in present-day health datasets do not match. Previous studies have taken different approaches to classify present day neighborhoods (census tracts) in terms of historical HOLC grades. This study reviews these approaches, examines empirically how different classifications fare in terms of predictive validity, and derives a predictively optimal present-day neighborhood redlining classification for neighborhood and health research.

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Looking to supplement common economic indicators, politicians and policymakers are increasingly interested in how to measure and improve the subjective well-being of communities. Theories about nonprofit organizations suggest that they represent a potential policy-amenable lever to increase community subjective well-being. Using longitudinal cross-lagged panel models with IRS and Twitter data, this study explores whether communities with higher numbers of nonprofits per capita exhibit greater subjective well-being in the form of more expressions of positive emotion, engagement, and relationships. We find associations, robust to sample bias concerns, between most types of nonprofit organizations and decreases in negative emotions, negative sentiments about relationships, and disengagement. We also find an association between nonprofit presence and the proportion of words tweeted in a county that indicate engagement. These findings contribute to our theoretical understanding of why nonprofit organizations matter for community-level outcomes and how they should be considered an important public policy lever.

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Many nonprofit organizations rely on donations to fund their programs, and a robust literature predicts donations in large-scale quantitative studies. The focus, however, is almost exclusively on the financial characteristics of the organizations, leaving the social context underexplored. In this article, we theorize how ecological context, organizational identity, and social network ties can shape donations. We use the new Internal Revenue Service (IRS) release of e-filed nonprofit reporting forms to consider 95,518 501(c)3 nonprofits around 2015. Using lagged regression models, we find that organizations within a more favorable ecological context, those that use appeals to religion, and organizations with more volunteers report more donations. Furthermore, stressing affiliation with a geographic location is associated with more donations only under certain ecological conditions. The article concludes with a discussion of the implications of these results for nonprofit organizations and social theories regarding what influences donations to organizations.

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