Computing diversity in undergraduate admissions decisions

The Supreme Court decision in the University of Michigan case in 2003 ruled the university's admissions procedures unconstitutional, giving minorities an unfair advantage of acceptance. The ruling stated race may still be used in admissions decisions to achieve diversity, but that race could not be used to give applicants preferential treatment in the admissions process. Motivated by this case, a researcher, Juan Gilbert, developed a computer based clustering method to aid admissions committees in choosing diverse entering classes. This method was evaluated using undergraduate admissions data sets from two public universities. Gilbert's method suggested diverse entering classes but did not select well based on merit. A method of improvement is introduced that maintains the academic characteristics of the university through classification, while suggesting diverse entering classes more academically similar to those actually accepted

Polarization and Belief Dynamics in the Black and White Communities: An Agent-Based Network Model from the Data

Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities--models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities

Polarization and Belief Dynamics in the Black and White Communities: An Agent-Based Network Model from the Data

Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities-models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities

A comparison of the frequencies of risk factors for depression in older black and white participants in a study of indicated prevention

BACKGROUND: To compare the frequencies of risk factors, we describe risks for depression as a function of race among consecutively admitted participants in a randomized clinical trial of indicated depression prevention in later life. METHODS: Seventy-two black and 143 white participants were screened for risk factors for depression. RESULTS: Black participants were more likely to have fewer years of education and lower household income. They were more likely to be obese, live alone, experience functional disability, have a history of alcohol and drug abuse, and have lower scores on the Mini-mental State Examination and the Executive Interview (EXIT). White participants were not found to have greater prevalence or higher mean score on any risk factor. On average, black participants experienced approximately one more risk factor than white participants (t(213) = 3.32, p = 0.0011). CONCLUSIONS: In our sample, black participants had higher frequencies of eight risk factors for depression and a greater mean number of risk factors compared to white participants.http://dx.doi.org/10.1017/S104161021000152