Researchers and policymakers want to better understand the dynamics of the Care Economy, but reliable, timely, and comprehensive statistics on caregivers are severely lacking. Misty Heggeness, Professor and Co-Director of the Kansas Population Center at the University of Kansas, therefore proposes to create The Care Board, a user-friendly online dashboard containing high-quality statistics about the U.S. Care Economy. The idea is to cover all activities, paid or unpaid, that contribute to the development of human capital, including the maintenance of another human being’s ability to thrive. Measuring such work is a challenge for many reasons, not least because many caregivers hold multiple jobs. The Care Board will use standard definitions from sociology and economics that account for these nuances. To the extent possible, data will be disaggregated by age, gender, parental status, race, ethnicity, educational attainment, poverty status, income, geographic area, and household configuration. To begin, Heggeness’ team will publish statistics on care workers based on traditional publicly available data sources, such as the Bureau of Labor Statistics, the American Time Use Survey, and the Current Population Survey. Some examples include the number of hours and percent of individuals who spend time engaging in (paid or unpaid) care work as a primary, secondary, or supervisory activity; or the number of families receiving benefits from WIC. The indicators will be improved over time using state-of-the-art methods to link administrative records with traditional survey microdata that Heggeness helped develop as a research economist at the Census Bureau. The Care Board will also feature data on federal and local policies like parental leave that affect caregivers’ ability to work for pay. With over a dozen years of experience in the federal statistical system, Heggeness is prepared to meet these statistical, methodological, and organizational challenges. She also plans to disseminate Care Board data through conference presentations, seminars, and user trainings. Encouragingly, top leadership at the Census Bureau have taken an active interest in this pilot. If all goes well, it could help launch a major effort by the federal statistical system to begin officially measuring how caregivers underpin U.S. economic progress.

The Sloan Foundation and other science funders naturally care about making basic research more productive, or, in other words, increasing the value of scholarly outputs per grant dollar we spend. Among the many factors influencing that ratio, researchers’ ability to plan, organize, and lead projects could be potentially important. Management training, after all, demonstrably enhances team performance in industries that range from manufacturing to healthcare. But beyond anecdotes, no one knows much about how academics run their laboratories. This is particularly striking in comparison to other sectors of the economy whose management practices have been extensively studied and improved. Economist Daniela Scur is therefore launching the first large-scale and methodologically sophisticated survey of organizational practices in academic research. She brings years of practical experience that includes running parts of the vaunted World Management Survey. Her team has already begun testing questions and protocols that explore ethics, mentoring, inclusiveness, climate, and other factors of concern in academic settings. Biomedical research laboratories are the first target because their operations are relatively homogenous, identifiable, team-oriented, and expensive. Eventually the plan is to survey 2500 from around the country. To date, they have already made adjustments to their survey instruments and plans based on a pilot project at the Harvard Medical School. Even there, the preliminary findings are tantalizing. Compared with those actually running or working in their labs, the PIs contacted were often unaware of what management practices were in place and overestimated their quality in any case. The full survey will adhere to, and benefit from, standards developed by the World Management Survey. In addition to documenting current practices, the survey results will be used to design and test interventions for teaching leadership skills that scientists do not normally learn in graduate school. Mr. Sloan, the consummate executive and productivity expert who also loved both scientific research as well as management education, would likely take particular delight in this use of his funds. 

Neither in grade school nor in research seminars does anyone actually present every detail of a mathematical proof with complete rigor. Our faith in a given theorem is ultimately based on the belief that mathematicians could, if asked, fill in all the missing definitions and arguments rather than on the belief that they have already anticipated and answered every possible question. As proofs have grown more complicated and lengthy, even famous mathematicians sometimes admit that they are not quite sure whether their argument is entirely correct. Shouldn’t computers be able to help? Among open-source software projects designed to assist with formulating and checking mathematical proofs, one has emerged as the clear frontrunner. Launched by Leonardo de Moura when he was working at Microsoft Research in 2013, it is called “The Lean Proof Assistant.” A Lean user inputs a theorem statement along with the steps of a purported proof in a special language. Based on the definitions, results, and logical rules it already knows, the program tries to check each step mechanically. In some cases, it can suggest shorter arguments. In others, it may interactively request more details. But once verified this way with super-human reliability, the theorem and its proof become part of the resources that Lean can call upon going forward. So far, educational resources based on Lean are helping students learn to construct proofs even when a skilled teacher is unavailable. Publications like Wired, Nature, and Quanta have hailed Lean, the last of these calling the Version 3 release “one of 2020’s biggest breakthroughs in mathematics.” Even Fields Medalists like Peter Scholze praise Lean, which helped verify an important proof of his that was so long, subtle, and impenetrable that he described it as “a thick jungle.” Despite all this excitement, Lean is still in its developmental stages with much hard work left to improve automation, scalability, usability, and sustainability. As Sloan found out years ago, usual academic structures and incentives are not well suited for such tasks. This is the motivation for launching a “Focused Research Organization.” Known as a FRO, this is a new type of nonprofit start-up pioneered by PI Adam Marblestone. Each FRO takes on a specific challenge and works on it exclusively for a few years before disbanding. During this time, the FRO will be incubated at the new nonprofit called Convergent Research founded with core funding and backing from Schmidt Futures. Lean creator Leonardo da Moura will lead the FRO technical team, which, in addition to mathematical experts and software engineers, will also include product, project, and community managers. The sustainability plan calls for spinning out a nonprofit Lean Foundation as has been done successfully by other major open-source software projects supported by Sloan that have turned out to be totally transformational. In this case, Lean stands to accomplish nothing less than accelerating the use, discovery, and learning of mathematical truths.

Life as we know it is primarily chemistry: all living organisms are composed of carbon-based molecules such as proteins, carbohydrates, and nucleic acids that are the result of chemical reactions between different elements like carbon, hydrogen, oxygen, nitrogen, and sulfur. Understanding the basic principles underlying chemical reactions is important to understanding life. When thinking about reactions in a chemical context, scientists typically think about reactants interacting in a homogeneous solution that’s essentially the same in any given place. But the cytoplasm, the liquid in cells where biochemical reactions take place, is a biological context that’s quite different from the simplified models of chemistry textbooks. Cytoplasm is a heterogeneous fluid that looks and functions differently across the cell and so it’s not accurately represented by simplifying assumptions of homogeneity. Precisely how these assumptions are distorting our picture of cellular chemistry, and therefore our understanding of fundamental biochemistry, is not well understood. This grant supports Lauren Zarzar and Ayusman Sen at the Pennsylvania State University who will study how solution heterogeneity influences reactivity for three important classes of biochemical reactions. First, they will study autocatalytic reactions, in which one of the reaction products facilitates (i.e. is a catalyst for) the same, or a coupled, reaction. Autocatalysis is a mechanism for chemical self-replication and is considered a key aspect of the prebiotic chemistry that gave rise to life. Next, the team will study enzyme reaction cascades, a sequence of enzyme-catalyzed reactions whereby the product of one reaction is the reactant for the next reaction. They’ll focus on chemotaxis (chemical activity that leads to motion towards or away from a higher concentration of some substance) to study how solution structure affects enzyme cascades. Finally, they will study polymerization reactions and, in doing so, address an important question in prebiotic chemistry: how polymers with specific monomer sequences arise without a specific sequence-directing mechanism. Ultimately, this project will deepen our understanding of specific reactions central to cellular chemistry and shed light on the role solution heterogeneity plays in driving the chemistry of life.

This grant supports Ben Machta at Yale University who will use tools from information theory and statistical physics to explore how bacteria process signals from their environment, and how they use this information to drive behavior. Machta will use bacteria to study one aspect of information processing: how noise (spurious signal accompanying the information-carrying signal) limits bacterial behavior. Specifically, Machta  will investigate how bacteria navigate their local chemical environment through chemotaxis (movement along a concentration gradient of a substance) and how they communicate with one another through quorum sensing (chemical signaling that reflects the density of nearby bacteria). Grant funds will allow Machta to determine the theoretical limit on the rate at which E. coli acquire behaviorally-relevant information (the concentration of so-called attractant molecules) and to measure this information-acquisition rate, to provide the first direct measurement of whether any organism’s biochemical sensory system approaches the performance limits imposed by the laws of physics. Additionally, Machta and colleagues will study how E. coli amplify signals without introducing noise via experiments that will test whether equilibrium or non-equilibrium models do a better job of describing chemotactic signal amplification. Finally, the researchers will use V. cholerae bacteria as a model organism to study the fidelity of information transmission as multiple signals propagate through the quorum sensing signal processing pathway. Collectively, these experiments will provide an important demonstration of how the tools of  information theory and statistical physics can be used to gain mechanistic insight into the information processing that drives behavior in simple living systems. 

This grant provides ongoing support to the Open Energy Outlook (OEO) Initiative, a multi-disciplinary, open-source, publicly available energy system model collaboration led by scholars at Carnegie Mellon University and North Carolina State University. The OEO Initiative involves input from over 40 consulting external subject matter experts from fields such as policy, electricity, buildings, and transportation, and it provides an open-source platform that makes energy system analysis more accessible to a range of stakeholders and applicable to different geographies and sectors. Grant funds will provide the organizational resources necessary to help grow and sustain the OEO Initiative over the coming years, involving three primary tasks. First, the team will update the open-source modeling platform that the OEO Initiative is based on, called the Tools for Energy Model Optimization and Analysis (Temoa) model, to better represent recent energy policy developments and legislation. Second, the team will develop a strategic plan that charts the longer-term path for their research, fundraising, and operational model, which includes establishing a consortium of funding partners from industry, nonprofits, and other foundations. Finally, the team will participate in research partnerships that will apply and extend the OEO Initiative framework to specific states, sectors, and other regions and countries. These research partnership efforts are expected to train 4-6 graduate students at a variety of institutions deploying the Temoa model. Funds will primarily go towards supporting the Executive Director role in managing the OEO Initiative.

The are many dimensions related to the local implications of renewable energy generation that have yet to be explored in much depth, especially impact that tend to be less visible stages along the supply chain lifecycle. As policies are developed that look to grow renewable energy infrastructure while also aiming for an equitable distribution of benefits, these questions as to how communities will be impacted across the renewable supply chain become increasingly pressing. This grant funds a highly interdisciplinary team at Boston University, the University of Delaware, and Virginia Tech to analyze eight case studies relating to the equity and justice dimensions of renewable energy production in the U.S. Funded case studies will focus on several different stages of the renewable energy supply chain, including resource extraction, construction and manufacturing, electricity generation in rural areas, and end-stage issues like recycling, disposal, and decommissioning.  Studies will be divided evenly between wind and solar generation and will focus on a wide range of geographies including critical mineral mining in Utah and Texas, solar panel manufacturing in Ohio, offshore wind installation along the Northeast Coast, a solar e-waste recycling in Kansas, and wind turbine blade disposal in Iowa. Study methods will include semi-structured interviews with key stakeholders, focus groups, expert elicitations, and observations to explore community experiences, opportunities, and vulnerabilities. The research team will draw on several conceptual frameworks to analyze the equity dimensions of the renewable energy supply chain. These include a feminist lens that addresses gender power dynamics, an anti-racist lens that focuses on racial discrimination, an Indigenous lens that explores historical patterns of land appropriation, and a post-colonial lens that relates to broader geopolitical factors. The team will link these frameworks with the empirical case studies to develop a fuller, multi-dimensional conceptualization of energy justice that promises to help illuminate the impacts of renewable energy development throughout the United States and provide important insights across all stages of the renewable energy supply chain.

One of the challenges to making electricity markets operate more efficiently is that most consumers pay flat electricity prices. While this rate structure provides consumers with cost certainty and insulates them from higher prices during extreme events, it does not provide price signals when electricity demand is high and therefore expensive. Some states and utilities are attempting to encourage load shifting or reduced use of electricity during key moments of grid stress through demand response programs, including time-of-use (TOU) programs that define peak and off-peak periods with different prices well in advance, and critical peak pricing (CPP) programs that announce and implement higher electricity prices on shorter notice. Uptake of these demand response programs remains limited in the United States, and there is a lack of research as to how consumers respond to these programs, especially in non-coastal and rural areas. This grant, resulting from an open Request for Proposals on Energy System Electrification, supports a team of economists and engineers from the Massachusetts Institute of Technology and the University of Massachusetts, Amherst aiming to empirically study consumer participation in demand response programs in rural areas through a randomized controlled trial (RCT). Grant funds will allow the team to complete three phases of work through partnerships with local electric cooperatives who have agreed to deploy demand response pricing experiments among their consumer bases. First, the team will implement a demand response RCT, covering at least one winter and one summer season, with a total sample of 43,000 electricity consumers. Participants will be offered different enrollment incentives and information relating to TOU and CPP programs. Next, the team will integrate findings from this RCT into an energy system capacity expansion model that will help understand the impact on broader energy system operations. Finally, the team will analyze the distributional and equity dimensions of the RCT, and they will assess what those findings might imply for other demand response programs across the country. Results from this research will also help electric cooperatives and similar utilities design and implement demand response programs.

The goal of this project is to grow and diversify the field of energy and environmental (EEE) economics by supporting an integrated set of training and early-career scholar engagement efforts taking place at the Energy Institute at Haas, based at the University of California, Berkeley. Four programmatic activities will be funded through this grant. The first is Grad Camp, a week-long, summer training course that brings 60 graduate students per year from across North American universities to the University of California, Berkeley for a rigorous introduction to cutting-edge research in EEE. The second is Energy Camp, a multi-day, early-summer gathering of 60 graduate students, postdoctoral fellows, junior faculty, and more established faculty to share and work on early-stage research projects. Three promising graduate students from the previous year’s Grad Camp will be invited to attend and present at the next year’s Energy Camp. The third is the EEE Undergraduate Mentoring Program, undertaken in partnership with Berkeley’s Opportunity Lab, which will prepare 18 Black, Indigenous, and Latina/o/x undergraduates per year at Berkeley for EEE graduate study by pairing these students with graduate student and faculty mentors. The fourth is research funding for two EEE graduate students per year that are working on seed projects designed to produce publicly available datasets or outputs that can be used by other scholars in the field. This proposal will help ensure that these programs will continue to enrich the EEE field and train the next generation scholars from a diverse range of backgrounds and institutions.

This grant provides ongoing support to Pecan Street, a non-profit research organization based in Austin, Texas seeking to improve researchers’ access to high resolution residential electricity use data by instrumenting households with energy monitoring devices. Pecan Street installs eGauge devices in participating households to directly measure power flow at the level of the circuit breaker. Each household gets access to their own energy use information, and Pecan Street collects and uploads the data to Dataport, a data sharing system for academic and commercial researchers. Grant funds will allow Pecan Street to greatly expand and diversify the number of instrumented homes in the research testbed by 40%, adding at least 50 homes in each of 4 different geographies, 210 homes in total: Atlanta, Georgia; Central Pennsylvania; Oklahoma City, Oklahoma; and Portland, Oregon. All of the newly instrumented homes supported in this project will be from communities of color or lower-income communities not yet represented in Pecan Street’s network. Pecan Street will work closely with academic researchers and local community-based organizations (CBO) in each region to engage participating households and use the collected data to study questions of interest to that particular area. Funds will allow Pecan Street to engage 750 new Dataport users, produce 10-20 journal publications, train multiple graduate students across the four local research projects, support the involvement of the CBOs, and update the Dataport infrastructure with upgraded storage and computer processing capacity. This effort will improve our ability to understand household electricity usage and, ultimately, help to facilitate the transition to low-carbon energy systems.