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Society often ascribes negative stereotypes to people experiencing homelessness. However, people experiencing homelessness have been found to display highly nuanced social behaviors. We employ a field dictator game to examine prosocial behavior among 173 unhoused individuals in Nashville, TN. We test whether an unhoused population displays ingroup bias, wherein they are more generous toward other people experiencing homelessness (the hypothesized ingroup) than people not experiencing homelessness (the hypothesized out-group). Additionally, we explore relationships between sociodemographic and personal characteristics (social support, perceptions of deservedness/generosity) and dictator game behavior. We did not observe ingroup bias. However, on average, participants allocated 29% of their game endowment to recipients, consistent with cross-cultural dictator game studies. We found that the duration of homelessness, social support, and gender were associated with dictator game allocations. Additionally, people experiencing homelessness were more generous when they perceived other unhoused individuals would be more generous and deserving. 

Human movement and population connectivity inform infectious disease management. Remote data, particularly mobile phone usage data, are frequently used to track mobility in outbreak response efforts without measuring representation in target populations. Using a detailed interview instrument, we measure population representation in phone ownership, mobility, and access to healthcare in a highly mobile population with low access to health care in Namibia, a middle-income country. We find that 1) phone ownership is both low and biased by gender, 2) phone ownership is correlated with differences in mobility and access to healthcare, and 3) reception is spatially unequal and scarce in non-urban areas. We demonstrate that mobile phone data do not represent the populations and locations that most need public health improvements. Finally, we show that relying on these data to inform public health decisions can be harmful with the potential to magnify health inequities rather than reducing them. To reduce health inequities, it is critical to integrate multiple data streams with measured, non-overlapping biases to ensure data representativeness for vulnerable populations. 

Abstract ObjectivesWith our diverse training, theoretical and empirical toolkits, and rich data, evolutionary and biological anthropologists (EBAs) have much to contribute to research and policy decisions about climate change and other pressing social issues. However, we remain largely absent from these critical, ongoing efforts. Here, we draw on the literature and our own experiences to make recommendations for how EBAs can engage broader audiences, including the communities with whom we collaborate, a more diverse population of students, researchers in other disciplines and the development sector, policymakers, and the general public. These recommendations include: (1) playing to our strength in longitudinal, place‐based research, (2) collaborating more broadly, (3) engaging in greater public communication of science, (4) aligning our work with open‐science practices to the extent possible, and (5) increasing diversity of our field and teams through intentional action, outreach, training, and mentorship. ConclusionsWe EBAs need to put ourselves out there: research and engagement are complementary, not opposed to each other. With the resources and workable examples we provide here, we hope to spur more EBAs to action.