While many occupations turned to remote work during the COVID-19 pandemic, domestic work by definition requires workers to enter other people’s households, and they often work in close proximity to their employers. With domestic workers proactively handling COVID19 risks as part of their already precarious jobs, there is a need for a conceptual understanding of risk management to aid this occupational group during a public health crisis.
The goal of the project is to understand information inequality across geographical regions in South Korea and visualize them using an AI-backed visualization tool. Our plan, spanning three years, revolves around the development of an intuitive platform for the purpose of visualizing these disparities. During the first year, we aim to construct comprehensive metrics for assessing the level of informational inequality, based on the theory of local information landscapes (LIL theory).
As organizations and individuals provide various information to multiple systems within a region, the information becomes fragmented, making it difficult for people to access the necessary information. Individuals have limited resources to navigate all the sources and use only part of the available ones. Disability service information is further fragmented due to diverse actors, ranging from government agencies to for-profit organizations, who often provide only partial information.
Certain U.S. population groups have suffered higher rates of infection and mortality than whites during the COVID-19 pandemic, including Latinx. Public health officials blamed disparities on overcrowded housing and work in essential industries prior to the vaccine’s availability. This study (n=34) focuses on the intersectionality of social locations for undocumented Latinx immigrants living in a relatively affluent suburb and working in the construction and service sectors.
This research will develop and design new data-driven risk prediction principles and management (DDRPM) tools that anticipate and manage a variety of community risks, which fire departments are increasingly required to respond to, including medical, fire, and safety emergencies. Today, much of their work focuses on community risk reduction (CRR), a paradigm that seeks to mitigate risks before they lead to emergencies in the first place. The CRR paradigm will leverage new data-driven risk prediction and management (DDRPM) tools to predict and respond to a variety of community risks.
Social services, traditionally, have been organized around their missions, such as education or safety or health. A newer approach, called "wrap-around services" or "systems of care," organizes services around individuals and their specific context and needs. These systems face many challenges when applied in real-world settings. Application processes often focus more on the potential of technologies and less on the realities, histories, and needs of communities. The proposed research addresses this gap by evaluating the implementation of a system of care in a real-world setting.
Value sensitive design (VSD) is a methodology that focuses on examining potential stakeholders' values and establishing designers' values of ethical imports in designing a technological system. While this approach provides effective ways to incorporate users' values in technology design, understanding teachers' values in culturally responsive teaching (CRT) poses unique challenges due to their interactions with students' cultural identities, school environments, and community contexts.
Delaying routine health care has been prevalent during the COIVD-19 pandemic. Macro-level data from this period reveals that U.S. patients under-utilized routine health care services such as primary care visits, preventative tests, screenings, routine optometry care, dental appointments, and visits for chronic disease management. Yet, there is a gap in research on how and why patients understand risks associated with seeking or delaying routing health care during an infectious disease pandemic.
The 311 systems that city officials currently deploy can efficiently detect non-emergency civic issues such as potholes and trash. From a socio-technical perspective, residents can re-appropriate the technology for their own purpose adding new capacities and affordances not initially intended. For example, when Hurricane Irma hit Miami in 2017, residents used 311 systems to report disaster-related issues, which led city officials to adapt the system by creating a new category.
Urban renewal was a project of the American government that aimed to reconstruct poor urban neighborhoods. Because community-level data that shows the underlying mechanisms of urban renewal has not been curated in a systematic way, due to the complexity and volume of the relevant archival collections, we aim to digitally curate property acquisition documents from the urban renewal projects that affected the Southside neighborhood of the city of Asheville, North Carolina, in the form of a map-based, interactive web application. This paper reports early findings from interviews.