This grant provides two years of continued support to the University of Oregon’s Biology and the Built Environment Center (BioBE). Led by microbiologist Jessica Green and architect GZ Brown and founded with the assistance of a 2010 Sloan Foundation grant, the BioBE Center aims to develop a predictive science of the built environment microbiome by bringing together a multidisciplinary research team of microbiologists, engineers, architects, and building experts. Over the next two years, Center researchers will launch a number of research projects that attempt to expand our understanding of how ventilation, structure, and daylight influence the composition and function of indoor microbial communities. Specific topics to be studied include how antimicrobial compounds influence the indoor microbiome and how that influence is mediated by building design, how restricting exchange with outside air affects community composition indoors, and whether earlier findings suggesting that design influences the microbial dust communities are generalizable across building types. In addition to supporting the Center’s research, additional grant funds support the Center’s training and outreach activities designed to bring new talent into the field and disseminate research results widely among the scholarly community and public.

Funds from this grant support a program at the University of Southern California School of Cinematic Arts that encourages top film students to write, direct, and produce films with accurate, high-quality scientific content. Grant funds support a number of interrelated activities at USC, including an annual production grant competition, which gives two $22,500 grants to help quality student scripts become films, two $15,000 screenwriting awards given to the best student science-themed scripts, and an annual $17,500 animation award for the best science themed animation produced by a student animator. In addition, USC hosts an annual seminar that introduces students to the program and brings in working scientists to expose students to cutting-edge scientific research and discoveries and an annual screening night where winners’ works are screened. USC also helps facilitate student interaction with industry professionals and the submission of science themed works to film festivals and other dissemination outlets.

This grant provides continued support for a fellowship program by the National Bureau of Economic Research (NBER), which supports young economics scholars whose research focuses on issues relating to the labor market for aging workers. Fellowships are awarded for a single year, with a review at the end of the first year and a second-year of funding available but conditioned on satisfactory progress in the first year.  The annual selection process includes a broadly disseminated call for proposals that is sent to an extensive list of U.S. Ph.D.-granting economics departments, to researchers who are members of the Society of Labor Economists, and to researchers affiliated with the NBER research programs in Aging, Labor Studies, and Public Economics. Applications are then reviewed by a panel of experts on labor economics, aging, and public finance. Fellows are selected based on the panel’s evaluation of their potential to make important contributions to understanding the determinants and consequences of labor market activity at older ages. Funds from this grant will support three cohorts of four doctoral students beginning with the 2016-17 academic year.

This three-year grant provides continuing support for efforts by the University of California, Los Angeles School of Theater, Film, and Television to encourage top film students to write and produce accurate, engaging films about science and technology. The UCLA program includes a yearly $10,000 screenwriting award given to the best student script that explores scientific themes or characters; a yearly $30,000 directing award given toward the production of a dramatic or comedic film about science or technology; and a yearly day-long colloquium that brings working scientists and researchers into the classroom to expose students to exciting new developments in science and introduce them to the narrative possibilities that science and technology offer the aspiring filmmaker. Additional grant funds pair student filmmakers with scientific mentors who advise students on the scientific content of their work and ensure that scripts depict science and the scientific endeavor accurately.

This grant provides three years of continued support to the American Film Institute’s (AFI) efforts to encourage young screenwriters and filmmakers to write and produce compelling, engaging narrative films that explore scientific themes or have scientists, engineers, or mathematicians as major characters. AFI’s program includes three annual award programs: a $25,000 award given to the best student film project that brings science and technology to life; a $10,000 annual screenwriting award given to the best science-themed script; and a yearly tuition scholarship worth $35,000 given to an incoming filmmaker with a background in the hard sciences who wishes to incorporate scientific themes in his or her filmmaking. In addition, AFI holds a seminar series where established actors, writers, directors, and producers talk to students about science and Hollywood, and provides access to working scientists to serve as mentors on student scripts.

Whereas retirement in a traditional marriage of breadwinner and homemaker involves a single retirement decision, in a two-earner marriage, the decisions are dual, and in many cases, joint. Yet, exactly what the pathways are for both members of working couples as they transition from full employment to full retirement are less than clear. This grant to the RAND Corporation supports a research project aimed at increasing our understanding of couples’ work and retirement trajectories by developing a theoretical model describing joint work-to-retirement transitions that can be applied to 12 waves of the Health and Retirement Study data. The data will allow the RAND team to examine how preferences for joint retirement and opportunities for partial retirement interact in the retirement decision, provide the first estimates of the prevalence of different joint work-to-retirement trajectories, and examine how factors such as age differences, part-time work opportunities, and leisure cause couples to make similar or different retirement transitions. In addition, the RAND team will explore how multistate models can be applied to the analysis of Health and Retirement Study data to explain retirement transitions across a range of pathways from full-time work to full-time retirement, including transitions through part-time employment.

This grant supports the Digital Public Library of America to expand its nationwide service hub network. Service hubs are on-ramps in each state for uploading and sharing digital content from the smallest private collection in a remote rural library to the largest state library or museum. As such, they are the key to DPLA's grass-roots, bottom-up, decentralized approach to building a national digital library. Hubs host locally provided digital content for the DPLA, correct and add metadata to uploaded items, coordinate local events and public outreach, and collaborate with state cultural institutions on digital initiatives. Grant funds will allow the DPLA to add eight new service hubs to its current roster of 15, increasing coverage by 50 percent and moving the institution closer to its goal of being a truly national digital library. Funds from this grant also support a DPLA initiative to partner with authors, publishers, libraries, and the White House to launch a new service network that provides free eBooks to children.

What do behavioral economists really know? Lessons learned so far seem more about isolated, but intriguing, examples rather than coherent or unifying principles. What counts as accepted doctrine is based almost exclusively on empirical results about particular phenomena such as loss aversion, probability weighting, altruism, hyperbolic discounting, and social comparisons. One would expect, therefore, that experts would be rather good at predicting the outcomes of standard experiments about standard topics in behavioral economics. This grant funds a research project by Devin Pope of Chicago and Stefano DellaVigna of Berkeley that test that hypothesis. First, Pope and DellaVigna will ask experts to forecast the effects of 17 different behavioral interventions or “nudges” in standard, simple, familiar, and carefully specified experiments. Second, they will run these experiments as described in a common setting. A large number of subjects will be asked to perform an effortful 10-minute task online. Each will be assigned to one of the 17 different framings, incentive structures, or other treatments. Just by keeping everything else equal except these behavioral interventions, the experimenters will be able to draw conclusions about the relative magnitudes and probabilities of various effects. Third, they will compare the expert forecasts with the experimental results. It is possible, of course, that all the predictions will turn out to be quite accurate—or not. In any case, such an exercise should help identify what behavioral economists do agree upon and, therefore, what we have learned from behavioral economics.

Among big questions about the economics of science, two of the most important and challenging concern investments in research and development (R&D): How do the inputs to R&D map into scientific breakthroughs? And how do the inputs to R&D map into broader social returns? This grant funds efforts by Benjamin Jones of Northwestern University to make fresh progress on each of these questions. First Jones will focus on the productivity of scientific teams, investigating how the characteristics of individual team members contribute to overall performance in different contexts. We know little about what makes effective scientific collaboration. For theoretical work, perhaps the strength of the strongest researcher drives results; in the lab, perhaps the strength of the weakest researcher matters most; and, in other situations, it may be some kind of average over everyone. Jones will use output and productivity data on scientific team composition to try to understand how these different skills and training fit together to influence scientific productivity. In a second effort, Jones will investigate the time delays between investments in and payoffs from R&D. Starting with NSF and NIH grant numbers, he will link newly available microeconomic data that trace how long it takes in various fields for grants to turn into papers, for papers to turn into patents, and for patents to turn into adopted technologies. Jones will then use these data to calculate societal returns to government investment in science.

This grant supports University of Pennsylvania computer scientist Aaron Roth in his work to develop, analyze, and evaluate “differentially private” algorithms for use in scientific discovery. First developed by mathematicians concerned about privacy, differentially private algorithms are ways of querying sensitive datasets. An algorithm or database query is “differentially private” if the results it returns would be provably the same even if an individual record were randomly replaced by another record in the queried dataset. Since the results such algorithms return do not depend on whether a given record is or is not included in the dataset, one cannot reverse engineer who is in the dataset from the results it generates. The privacy of the data is thereby protected. As it happens, this privacy protecting feature has uses outside the concern to protect privacy. Differentially private algorithms also prevent data mining and overfitting. Since differentially private algorithms produce the same results regardless of whether a given observation is randomly replaced by another, it is difficult to use them to craft results tailored to the particularities of the data you happen to have collected. At present, however, differentially private algorithms are more exciting in theory than in practice. They tend to be laborious and slow. What’s needed is further development and testing of such algorithms with scientific applications in mind. Dr. Roth is working on just such an approach, trying to develop practical applications of differentially private algorithms that are streamlined and reliable enough to be used in everyday scientific practice and analysis.