#mapparoma

2018

Scientific Peer-Reviewed Open Access Journal – SocioEconomic Challenges (SEC), ISSN (print) – 2520-6621, ISSN (online) – 2520-6214 was founded in 2016 and registered by the Ministry of Justice of Ukraine (Certificate No. KB 22380 – 12280Р from October 31, 2016). Ukraine Urgent Memo, 2023 Academic Work Censored https://gvoskop.wordpress.com/2023/12/06/academic-work-censored/

Journal of Social Equity and Public Administration

Written by the coeditors-in-chief, this essay introduces the Journal of Social Equity and Public Administration (JSEPA) and situates it among other public administration journals. Its mission, aims, and scope are explained. Manuscripts are welcomed that identify and probe societal structures and dynamics that create or perpetuate inequity, or that overcome it. Published for a global audience, it is a theoretically and methodologically inclusive journal. Because social equity is a moving target, always evolving, the pages of this journal will reflect its course.

Poverty & Public Policy

Equality, diversity and inclusion, 2024

2010

Statistics in Medicine, 2008

Efforts to monitor, investigate, and ultimately eliminate health disparitiesacross racial/ethnic and socioeconomic groups can benefit greatly from spatiotemporal models that enable exploration of spatial and temporal variation in health. Hierarchical Bayes methods are well-established tools in the statistical literature for fitting such models, as they permit smoothing of unstable small-area rates. However, issues presented by ‘real-life’ surveillance data can be a barrier to routine use of these models by epidemiologists. These include (1) shifting of regional boundaries over time, (2) social inequalities in racial/ethnic residential segregation, which imply differential spatial structuring across different racial/ethnic groups, and (3) heavy computational burdens for large spatiotemporal data sets. Using data from a study of changing socioeconomic gradients in female breast cancer incidence in two population-based cancer registries covering the San Francisco Bay Area and Los Angeles County, CA (1988–2002), we illustrate a two-stage approach to modeling health disparities and census tract (CT) variation in incidence over time. In the first stage, we fit race- and year-specific spatial models using CT boundaries normalized to the U.S. Census 2000. In stage 2, temporal patterns in the race- and year-specific estimates of racial/ethnic and socioeconomic effects are explored using a variety of methods. Our approach provides a straightforward means of fitting spatiotemporal models in large data sets, while highlighting differences in spatial patterning across racial/ethnic population and across time. Copyright © 2008 John Wiley & Sons, Ltd.

LSE Research Online Documents on Economics, 2019