Purpose: This study investigated the relationship among information awareness, access, and socioeconomic deprivation in the context of local health information. Drawing on theories of information poverty and the digital divide, this study examined how socio-economic deprivation influences individuals’ ability to become aware of and access local health information.
SAFETI is the first Mason–DOLI Innovation Lab initiative that turns more than 15 years of detailed Virginia workplace-accident records into forward-looking, preventive insights. Using predictive models, the computational approach developed for SAFETI estimates the likelihood of a fatality occurring within a specific time frame and sector, along with its associated probability. This shift from reactive to preventive measures is enabled by advanced spatio-temporal and predictive analytics.
This study investigates the experiences and concerns of public librarians responsible for statistical data management and explores strategies to address related challenges. In-depth interviews were conducted with ten librarians handling statistical tasks at public libraries in Metropolitan City A and Province B in the Yeongnam region. Findings revealed that librarians had established a systematic workflow involving data collection, internal verification, data entry, and external verification.
Access to disability services information depends on many factors, from an individual’s digital literacy, social connections and physical mobility to the interface design of websites. However, it is also true that the availability of disability services information (e.g., how to apply for a Medicaid Waiver) and how such information is managed and provided to end users in Virginia are also critical factors that shape people’s information access. This assessment focuses on understanding the latter, namely, the “information ecology” of disability services in Virginia.
This paper details an investigation into the information management challenges encountered by disability service providers. Prior research has mainly focused on understanding the information management challenges related to user records or internal organizational systems. However, this study posits that the information access patterns of disability services users are significantly influenced by their interactions with service providers’ information management practices in localized settings.
Public servants tasked with implementing rules or policies on the street-level often make discretionary decisions based on local context. Lipsky has labeled them street-level bureaucrats. During the COVID-19 pandemic, as most face-to-face interactions facilitated by local government moved online, many street-level decisions were moved to screens, representing the actions of who Bouvins and Zouridis refer to as screen-level bureaucrats. Discretionary decision-making among public servants continued, but much of it centered on the collection, analysis, and use of data.
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.
Information behavior research to date has mainly focused specific cases or representative surveys at the individual level, because each individual has unique contexts that shape their behavior. However, they have not fully benefited from aggregate-level analyses due to mainstream theories’ focus on a contextualized understanding of information. To address this gap, we adopt the theory of local information landscapes, that focuses on the material aspects of community dynamics, and analyze national-level aggregate data on book circulations in public libraries across South Korea.
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).
In the public sector, governments and the people they serve increasingly collaborate to coproduce public services. To support the coproduction of municipal services, specifically, local governments have incorporated various digital technologies into their information systems. How do digital technologies affect community residents' engagement in coproducing municipal services?