Independent and arthouse cinemas participating in the Science on Screen program pair screenings of classic, cult, or documentary films with lively introductions by working scientists who discuss ways in which the film touches on science, technology, engineering, or mathematics.  Past offerings have included a screening of the 1980s slapstick comedy Airplane! paired with a discussion of automation in aviation, a screening of Fight Club paired with a discussion of the psychology of aggression, and a screening of Soylent Green paired with a discussion of the future of the global food supply. The program is headed by Cambridge’s Coolidge Corner Theater (CCT), which promotes the program within the arthouse cinema community, makes suggestions for entertaining film/discussion pairings, and administers small grants to participating theaters to promote screenings and recruit local scientists. In addition, CCT organizes a national “Science on Screen day” when all participating theaters hold coordinated screenings, and gives an annual presentation at the Arthouse Convergence, an industry gathering of more than 600 arthouse and independent cinemas. Funds from this grant provide two years of continued support for the Science on Screen program, including funds to expand the number of participating theaters and improve the program’s web presence.

This grant funds efforts by Allessandro Acquisti at Carnegie Mellon University to examine, through laboratory, online, and field experiments, how Privacy Enhancing Technology (PET) can affect consumer behavior and welfare. Examples of PET tools include ad blockers like Ghostery, surveillance blockers like Tor, and cookie blockers like Beef Taco. Acquisti and his team will have PET software installed on the computers of some experimental subjects and then observe how their online behavior changes relative to a control group. They will then measure and analyze the subsequent differences in consumer behavior, like purchases or sites visited, as well as changes in the prices, products, or search results offered by websites and search engines to the two groups. The work promises to provide valuable new data on how concerns about privacy shape the way we conduct our lives online.

This grant funds research by University of Michigan economist and professor of education Brian Jacob, who has designed a randomized controlled trial to study the effects of behavioral interventions on enrollment in the Teacher Loan Forgiveness (TLF) program. The TLF is a federal initiative that forgives up to $17,500 in student loans to teachers who teach for five years in a school serving students from low-income families.  The complicated, multistage qualification process for the program offers a unique opportunity to test how various interventions might work, by randomly assigning applicants to different groups during the process and subjecting them to slightly different form designs, requirements, defaults, and choice architectures. The TLF thus serves as an excellent opportunity to study how to design federal benefits programs in ways that maximize their uptake. Funds from this grant will support Jacob and his research team as they conduct this two-year study.

Behavioral economists tout examples of how small changes in the way options are presented can have large effects on the decisions people make. The term “nudging” refers to such “choice architecture” modifications that help, but do not force, people to behave more in line with how they wish they could. To count as a nudge, the behavioral intervention should be easy and inexpensive to disregard. So, for example, putting fruit at eye level is a nudge; banning junk food is not. Large-scale experiments, both by academics and by governments, have shown that nudging can help people eat better, reduce their energy consumption, or save more for retirement. These are relatively straightforward applications, though. Others raise harder questions about who ultimately benefits, who loses, and by how much. For example, do people like being nudged? Should people like being nudged? All things considered, when does nudging actually make society better off? Does it matter much if people know they are being nudged? This grant funds a series of experiments by University of Chicago economist John List to examine these and related issues. List’s team has designed two large randomized controlled trials with almost 50,000 subjects in total, one focused on energy conservation and another on food choices. Along with measuring the direct effects of nudges, List will rigorously examine participants’ decisions to opt in or out of being nudged, allowing him to estimate any associated welfare losses experienced by consumers.

Behavioral economics catalogs examples of how people fail to act as naпve economic models say they should. In theory, such examples should lead to revised models of economic behavior that are more sophisticated, nuanced, and accurate. These have been slow in coming. To date, behavioral economists have been more concerned with classifications and applications than with foundations, representations, or explanations. Courses and textbooks tend to take up one anomaly or bias after another, without much of a conceptual or analytic framework to offer. Funds from this grant support a project by Harvard economist Andrei Shleifer to develop a theoretical framework that can systematically accommodate many of the anomalous behaviors detected by behavioral economists. Shleifer will attempt to do this through further development of “salience theory,” which hypothesizes that certain facts or pieces of information can appear more salient or command more attention at the moment of decision. These salient facts are then overweighted by decision-makers relative to their nonsalient cousins, causing decision-makers to deviate from the rational behavior predicted by, say, expected utility theory. Grant funds will support Shleifer as he continues to develop salience theory and use it to incorporate the diverse insights of behavioral economics into satisfying, predictive models of human economic behavior. Topics to be explored include the role stereotypes and generalization play in decision-making, how being surprised affects salience, and how attitudes about what is or is not normal shape what people pay attention to.

Launched in 2008 with the help of the Alfred P. Sloan Foundation, the World Science Festival is perhaps the world’s premiere science festival, bringing first class scientists from all over the globe to New York City to lead the public in a weeklong series of panels, presentations, and events in celebration of all that is fun and fascinating about science. More than 50 panels and events are targeted at all ages and education levels, with recent panels devoted to such diverse topics as the science and history of beer-making, the use of electrical stimulation to improve cognitive function, and the effects of zero gravity environments on the human body. To increase its reach beyond New York City, the festival produces online and video segments and education material for science teachers to incorporate into their curricula. Funds from this grant provide continued support to the World Science Festival for another three years.

Empirical articles and the data they use have not always been carefully connected. That makes it hard to replicate findings, to reuse data, or to build on previous work rather than just duplicating it. This grants supports the development and expansion of a new platform, DUOS (Dataset-Utilization Open Search), that links existing papers with the standard datasets and methodologies they use. Conceived by Svetlozar Nestorov of Loyola University, the system allows researchers, graduate students, and policymakers to find the published results of performing particular kinds of calculations on particular sets of survey data. Nestorov’s initial work has focused on the Current Population Survey, the primary source of labor force statistics in the United States. Student research assistants have manually compiled hundreds of linkages between the survey and the published academic literature. This information constitutes a training set for machine-learning algorithms that, when sufficiently developed, will be able to scan the online literature and extract links automatically. Grant funds support the continuation of Nestorov’s work and its expansion to other datasets, including the Survey of Income and Program Participation (SIPP) run by the U.S. Census, and the Panel Study of Income Dynamics (PSID) funded by NSF. Once developed, tested, and refined, Nestorov’s machine-learning software for automating DUOS operations will be made freely available for use in fields besides economics.

The BioBus is a fully mobile research lab that visit schools and public science events in New York City. Outfitted with state-of-the-art microscopes and run by a diverse team of young scientists, the BioBus is a mobile science field trip where students can use a phase-contrast video microscope to make movies of crawling amoeba, use a scanning electron microscope to image a fly eye, or use a fluorescing microscope to see glowing, streaming plant chloroplast. In 2014, the BioBus visited 88 K-12 schools in New York City, bringing high-quality, engaging education to some 16,000 students, 57 percent of whom were African-American or Latino. Funds from this grant support the continued operation and expansion of BioBus. Over the next three years, Cell Motion Laboratories, the parent organization of the BioBus, will build another BioBus mobile lab and, in partnership with Columbia University, build a “BioBase” community lab in Harlem, which will allow students to continue their educational experiences once the BioBus has moved locations, and expand its educational offerings to underserved students in Harlem.

Science Goes to the Movies is a new public television program produced by the CUNY TV Foundation that reviews current movies and television shows from a scientific perspective. Topics discussed in early episodes include visualizing black holes, Birdman and the prevalence of hallucinations, and depictions of women scientists in the Big Bang Theory. Hosted by neuroscientist Heather Belin and journalist Faith Sailie, Science Goes to the Movies premiered in February 2015 and is reaching a growing audience through integrated use of broadcast, cable, web, and mobile platforms and has performed well in its native market of New York City. Funds from this grant provide production support for the show as it explores possible distribution to a national audience through PBS’s Executive Programming Service, bringing the series to half the PBS stations in the country with a net audience of more than a million viewers.

The basic process of moving large tabular data from one environment to another is fraught with issues. Ambiguous column headings and messy metadata can make it difficult and time consuming to understand exactly what a data file contains. As researchers move data from repository to research tool (and often through a series of research tools), the opportunities for error proliferate. Rufus Pollock of the Open Knowledge Foundation has developed a lightweight approach to structuring metadata about tabular datasets. With the Pollock approach, tabular datasets are packaged and moved with files that describe the data—datatypes, formatting, source, etc.—allowing research tools like Matlab, Excel, and Stata to appropriately parse the data inside. He describes this “data package” model as the equivalent to a shipping container for data, making it easier to standardize the entire logistics process. Funds from this grant continue development of the Pollock’s “data package” standard. Funded activities include the development of validators and extensions that would make it easy to export and import data packages from standard research tools (essentially adding new “Save As” and “Open” options); outreach to specific user communities to model use of the specification for individual disciplinary communities; the launch of several pilot projects integrating the data package model into existing user workflows; and building a broader development community around the need for better tools for efficient and trusted storage, transport, and analysis of large tabular data.