Global Responses to the COVID-19 Pandemic

Public Organization Review -     

Ethical Numbers: Ethics Training in U.S. Graduate Statistics Programs, 2013–2014

As important members of research teams, statisticians bear an ethical responsibility to analyze, interpret, and report data honestly and objectively. One way of reinforcing ethical responsibilities is through required courses covering a variety of ethics-related topics at the graduate level. We assessed ethics requirements for graduate-level statistics training programs in the United States for the 2013–2014 academic year using the websites of 88 universities, examining 103 biostatistics programs, and 136 statistics degree programs. We categorized programs’ ethics training requirements as required or not required. Thirty-one (35.1%) universities required an ethics course for at least some degree students. Sixty-two (25.5%) degree programs required an ethics course for at least some students. The majority (77.4%) of required courses were worth 0 or 1 credit. Of the 177 programs without an ethics requirement, 19 (10.7%) listed an ethics elective. Although a single ethics course is insufficient for instilling an ethical approach to science, degree programs that model expectations through coursework point to the value of ethics in science. More training programs should prepare statisticians to consider the ethical dimensions of their work through required coursework. Supplementary materials for this article are available online.     

No wonder social workers feel uncomfortable in court

The present article assesses the adversary systemper se and asks the question, Is there any place for courtroom antics and histrionics in cases involving children? Social workers are uncomfortable before the august body of thecourt, not because of any lack of education or knowledge on their part but because of the nature of the adversary process itself.     

Value,attitude, and belief determinants of willingness to accept a facility for the homeless

Basic values, attitudes toward the homeless, and specific beliefs about a proposed facility were examined, along with the NIMBY (Not In My BackYard) phenomenon, to explore if, and to what degree, these factors affect community acceptance or rejection of a facility for the homeless. Previously designed Protestant ethic (PE) and Humanitarian-Egalitarian (HE) scales were used to measure two basic values (Katz & Hass, 1988). Scales to measure attitudes toward the homeless and beliefs about a planned facility were developed. As predicted, values, attitudes, and beliefs correlated with each other and were related to plan acceptance, so that HE, pro-homeless attitudes, and positive beliefs about the plan were positively related to acceptance, and PE, anti-homeless attitudes, and negative beliefs about the plan were positively related to rejection. Also as predicted, four proximity measures were all related to acceptance of the plan.     

Predicting body fat using weight–height indices

While body fat is the most accurate measure of obesity, its measurement requires special equipment that can be costly and time consuming to operate. Attention has thus typically focused on the easier to calculate body mass index (BMI). However, the ability of BMI to accurately identify obesity has been increasingly questioned. This paper focuses attention on whether more general body mass indices are appropriate measures of body fat. Using a data set of body fat, height, and weight measurements, general models are estimated which nest a wide variety of weight–height indices as special cases. In the absence of a race and gender categorisation, the conventional BMI was found to be the appropriate index with which to predict body fat. When such a categorisation was made, however, the BMI was never selected as the appropriate index. In general, predicted female body fat was some 10 kg higher than that of a male of identical build and predicted % body fat was over 11 percentage points higher, but age effects were smaller for females. Considerable racial differences in predicted body fat were found for males, but such differences were less marked for females. The implications of this finding for interpreting recent research on the effect of obesity on health, society, and economic factors are considered.