Classifying human beings according to race and ethnicity may seem straightforward to some but it, in fact, belies a difficult process. No standard procedure exists for categorizing according to race and ethnicity, calling into question the variables’ use in research. This article explores the use of race and ethnicity variables in the nursing research literature. Content analysis was conducted of a sample of 337 original research studies published in Nursing Research from the years 1952, 1955, and then every 5 years (...) through to 2000. Of the 337 research articles reviewed, 167 mentioned race, ethnicity, or their 81 code words or phrases. Out of the 167 articles, 153 used race or ethnicity to describe the study sample, and 45 of the 167 articles included race or ethnicity as an element of data analysis. Throughout the sample, there was substantial inconsistency related to race and ethnicity categorization, meanings of the terms, and use of these variables. Specificity related to conceptual assumptions, definitions, and context was missing and, as a result, data interpretation and understanding are suspect. The integrity of nursing knowledge requires that nurse researchers recognize and address the difficulties inherent in using race and ethnicity in health research. (shrink)

Drawing on interviews and observational work with practicing U.K. plant scientists, this article uses Michel Callon's work as a tool to explore the issue of collaboration between academic science and business, in particular, calls by the Biotechnology and Biological Sciences Research Council for a return to “public good” plant science. In an article titled “Is Science a Public Good?” Callon contributed to the debate about the commercialization of science by suggesting that commercialization and the public good need not be incompatible. (...) Moving away from arguments that center on the effects of business involvement in science, he suggested that analysts use another model, centered on “diversity.” This model allows us to ask what society might want from science, what public good science might look like, and how public good science can be ensured while also recognizing that science cannot be easily separated from the market. (shrink)