ABSTRACT
This paper describes an attempt to utilize paid citizen science in a research project that documented urban park usage during the early stages of the COVID-19 pandemic in two U.S. cities. Strategies used by the research team to recruit, pay, and evaluate the experiences of the 43 citizen scientists are discussed alongside key challenges in contemporary citizen science. A literature review suggests that successful citizen science projects foster diverse and inclusive participation;develop appropriate ways to compensate citizen scientists for their work;maximize opportunities for participant learning;and ensure high standards for data quality. In this case study, the selection process proved successful in employing economically vulnerable individuals, though the citizen scientist participants were disproportionately female, young, White, non-Hispanic, single, and college educated relative to the communities studied. The participants reported that the financial compensation provided by the study, similar in amount to the economic stimulus checks distributed simultaneously by the Federal government, were reasonable given the workload, and many used it to cover basic household needs. Though the study took place in a period of high economic risk, and more than 80% of the participants had never participated in a scientific study, the experience was rated overwhelmingly positive. Participants reported that the work provided stress relief, indicated they would consider participating in similar research in the future. Despite the vast majority never having engaged in most park stewardship activities, they expressed interest in learning more about park usage, mask usage in public spaces, and socio-economic trends in relation to COVID-19. Though there were some minor challenges in data collection, data quality was sufficient to publish the topical results in a peer-reviewed companion paper. Key insights on the logistical constraints faced by the research team are highlighted throughout the paper to advance the case for paid citizen science. Copyright © 2022 Alizadehtazi, Woerdeman, Tangtrakul, Gussenhoven, Mostafavi and Montalto.