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The Great Divide Between the Wealth of Nonprofits and Their Communities

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2024-05-08

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Green, Chelsea. 2024. The Great Divide Between the Wealth of Nonprofits and Their Communities. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.

Abstract

Amidst the confluence of rising inequality and increasing nonprofit wealth, is this increasing institutional wealth making a meaningful impact on communities? Furthermore, are nonprofit institutions in more marginalized communities more likely to receive funding, or less likely?

To address these questions, Chapter 1 begins by investigating which nonprofit organizations receive more financial resources --including grants from government sources--and why. Drawing on three original datasets, the findings highlight a curious phenomenon: community-related factors explain little additional variation in nonprofit organizational wealth, particularly when controlling for their organizational purposes. However, Stochastic Gradient Descent learning was applied to the models, revealing noteworthy results. First, a positive relationship between community inequality and nonprofit organizational wealth exists. Second, different forms of racism (structural v. institutional) experienced by nonprofits' surrounding communities predict different effects on the wealth of nonprofit organizations themselves. This chapter notably contributes 1) the first research to quantify the effects of historical redlining policies on modern-day nonprofit wealth, and 2) the largest ever original dataset ---and subsequent empirical investigation ---of government grant contributions to nonprofits.

Chapter 2 then examines the relationship between the structure of organizational landscapes and community level wealth. Deploying two additional original datasets, nonprofit presence and power are found to explain very little additional variation in community wealth when controlling for other community-related factors. However, they do explain additional variation in community inequality among the most marginalized American communities, but in a perhaps counterintuitive direction: for some organizational types, increased nonprofit power and presence is associated with greater community inequality. Furthermore, nonprofits explained greater variation in inequality where they were most scarce, but also where they possessed the most resources. Finally, nonprofits representing a wide and surprising array of functions---far beyond what might seem immediately relevant to community wealth--- seem connected to community inequality at the most granular geographical levels.

In light of these striking findings, Chapter 3 proposes a new theory of action to bridge the divide between nonprofit organizations and their communities. I argue that the way individuals navigate organizations--- often multiple of them---are key to how people can get what they want. Using Hirschman's exit, voice, and loyalty as a starting point, this chapter leaps beyond the traditional confines of choice sets available to individuals and expands upon them. Emphasizing how individuals navigate multiple institutions, rather than just one, to advance their interests offers a theoretical lens through which to view the interactions between community members and the organizations that surround them.

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inequality, machine learning, nonprofit organizations, organizational behavior, organizational wealth, Organizational behavior

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