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We present a programmatic approach to incorporating ethics into an undergraduatemajor in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum fromtop-to-bottomas our majors progress from our introductory courses to our senior capstone course, as well as from side-to-side through co-curricular programming. We also provide six examples of data science ethics modules used in five different courses at our liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated into existing courses at different levels of instruction with minimal disruption to syllabi. We connect our efforts to a growing body of literature on the teaching of data science ethics, present assessments of our effectiveness, and conclude with next steps and final thoughts. [ABSTRACT FROM AUTHOR]

Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects "diffusing" into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti's Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP set have network position and non-network differences (such as demographic, attitudinal, or behavioral differences) compared to the remaining members of the target group (non-SPs). Methods: A first-year class at a private residential university (N = 1342) completed network and non-network measures. Analyses were restricted only to heavy drinkers, leading to a final analytic sample of 529. Results: SPs and non-SPs differed on multiple network variables, but did not differ on most demographic, attitudinal, and behavior variables. Conclusions: As designed, the SP program identified participants who were distinguished by their network position. The fact that they did not also differ on other characteristics shows the SPs are not significantly different than heavy drinkers who were not selected. [ABSTRACT FROM AUTHOR]