ResumoApesar de constituir quase metade da população brasileira, os afro-brasileiros são sub-representados nas empresas, em particular nos altos escalões. Algumas empresas no Brasil estão desenvolvendo iniciativas em favor da diversidade que visam à inclusão de afrodescendentes, entre outros grupos historicamente discriminados, no mercado de trabalho. Durante cinco meses, o autor desta comunicação investigou e entrevistou representantes desses programas de diversidade no Rio de Janeiro e em São Paulo. Serão apresentados os resultados de sua pesquisa, que analisa as estratégias, justificativas e impacto da promoção da diversidade racial no setor privado.Palavras-chave: negros, diversidade, recursos humanos, responsabilidade social empresarial, investimento social privado. AbstractWhile Afro-Brazilians make up nearly half of Brazil's population, they are under-represented in businesses, especially in the upper echelons. Some businesses in Brazil are developing initiatives to promote diversity that seek to increase the representation of Afro-Brazilians among other historically discriminated groups in the private sector. During five months, the author of this report investigated and interviewed representatives of these diversity initiatives in Rio de Janeiro and São Paulo. It analyzes the situation of blacks in the labor market and in businesses, the ethical and economic justifications for diversity initiatives, and the strategies and results of such initiatives.

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Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES).Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets.Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.

ABSTRACT:The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 10,000+ attributes covering over 200 nation states spanning over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We discuss the status of this work and report on major findings.

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