Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1385&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1397&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1386&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "427", "attributes": { "award_id": "2210237", "title": "Conference: 2022 Marine Microbes GRS and GRC", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [], "program_officials": [ { "id": 823, "first_name": "Michael", "last_name": "Sieracki", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": "2022-08-31", "award_amount": 26300, "principal_investigator": { "id": 824, "first_name": "Chase C", "last_name": "James", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true }, "abstract": "The Gordon Research Seminar (GRS) and Gordon Research Conference (GRC) on Marine Microbes together create an international forum for sharing cutting-edge research on the ecology, evolution, and function of microorganisms in the ocean biosphere. The meeting bringstogether top scientists from around the world who have diverse backgrounds and expertise in order to provide an integrated program on marine microbial life, covering cutting edge research on viruses, Bacteria, Archaea and Eurkarya protists, spanning pelagic and benthic realms, trophic food web dynamics (photoautotrophy, chemoautotrophy, heterotrophy and mixotrophy) and their interactions and impact on biogeochemical cycles. Both the Seminar and Conference are organized in thematic sessions, with the goal of highlighting new methodological approaches and emerging questions in the field while stimulating rigorous discussion. This award enables early career participants (postdoctoral researchers and graduate students in the marine microbiology research community with diverse backgrounds) to attend both the 2022 Gordon Research Seminar (May 28-29, 2022) and Gordon Research Conference (May 29- May 29, 2022) on Marine Microbes. The rationale is to facilitate the attendance and participation of postdocs and graduate students in the GRS so they have an opportunity to present their research among peer scientists and establish connections and confidence in this setting. The GRS exposes young, early-career scientists to cutting-edge research on marine microbes (ranging from computational to theoretical to experimental to observational, and spanning all relevant disciplines from ecology to biogeochemistry to evolution), provide opportunities to network among peers, and foster relationships that will hopefully lead to lifelong collaborations. It also provides career guidance and scientific mentoring through the participation of select senior-level research mentors and discussion leaders. The GRS increases student and postdoc participation in the subsequent GRC which has oral presentations from a diverse group of young and established scientists who play leading roles in marine microbial research. The 2022 meeting is of special importance since the 2020 meeting was postponed due to the global COVID- 19 pandemic. It is even more important now that researchers can reconnect and have vital discussions about novel research, in an environment that fosters networking and collaboration.The respective themes of the 2022 Marine Microbes GRS and GRC are “Integrated Microbial Oceanography” and “Interconnected Microbial Ocean.” These themes highlight some of the pressing challenges and opportunities for innovation and collaboration in the field of marine microbiology. The “Integrated Microbial Oceanography” GRS focuses on research at the nexus of approaches of study marine microbes that bridges across methods, experimental systems, and scales to form a more holistic understanding of the ocean microbiome. The complementary GRC is on the “Interconnected Microbial Ocean,” and aims to highlight the vital functional roles of microorganisms, their ecological interactions, and their feedbacks on marine physiochemical environments. The Marine Microbes GRS/GRC are arguably the only meetings that coalesce such a diverse array of researchers (from career stages, disciplines, areas of expertise) related to marine microbes. The GRC meeting format emphasizes personal interactions, unpublished, cutting-edge research, and community-building. As such, these meetings continue to be an exceptional opportunity for the exchange of scientific ideas, developing new collaborations, gaining experience in presenting research (especially for early-career scientists), and are a crucial platform for addressing pressing challenges and opportunities for the field of marine microbiology. The meetings are highly interactive, stimulating environments that drive scientific conversations and community forward. A critical part of achieving our meeting goal is participation from a diverse array of scientists to the meeting site.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "426", "attributes": { "award_id": "2147375", "title": "FAI: A novel paradigm for fairness-aware deep learning models on data streams", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 818, "first_name": "Juan", "last_name": "Wachs", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2025-08-31", "award_amount": 392993, "principal_investigator": { "id": 822, "first_name": "Feng", "last_name": "Chen", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 199, "ror": "", "name": "University of Texas at Dallas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 819, "first_name": "Latifur R", "last_name": "Khan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 820, "first_name": "Xintao", "last_name": "Wu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 821, "first_name": "Christan E", "last_name": "Grant", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 199, "ror": "", "name": "University of Texas at Dallas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Massive amounts of information are transferred constantly between different domains in the form of data streams. Social networks, blogs, online businesses, and sensors all generate immense data streams. Such data streams are received in patterns that change over time. While this data can be assigned to specific categories, objects and events, their distribution is not constant. These categories are subject to distribution shifts. These distribution shifts are often due to the changes in the underlying environmental, geographical, economic, and cultural contexts. For example, the risks levels in loan applications have been subject to distribution shifts during the COVID-19 pandemic. This is because loan risks are based on factors associated to the applicants, such as employment status and income. Such factors are usually relatively stable, but have changed rapidly due to the economic impact of the pandemic. As a result, existing loan recommendation systems need to be adapted to limited examples. This project will develop open software to help users evaluate online fairness-in algorithms, mitigate potential biases, and examine utility-fairness trade-offs. It will implement two real-world applications: online crime event recognition from video data and online purchase behavior prediction from click-stream data. To amplify the impact of this project in research and education, this project will leverage STEM programs for students with diverse backgrounds, gender and race/ethnicity. This project includes activities including seminars, workshops, short courses, and research projects for students. This project aims to develop a new and innovative paradigm for designing, implementing, and evaluating online fairness-aware Deep Learning (DL) models. Such models would be used for classification tasks in noisy and non-stationary data streams. This project will focus on five areas. First, the project will explore how to ensure a variety of fairness principles are incorporated in a DL model in online and non-stationary settings. The project will also look at how to identify a neural network architecture that will reflect the causal structure and be adaptive to distribution shifts. The project also looks at how the DL model will learn global initialization of primal parameters (associated with model accuracy) and dual parameters (associated with model fairness). Finally, the project looks at how to make online learning algorithms robust to uncertainties in model estimation of fairness and how to, ultimately, interpret the fairness of an online DL model. By bridging the areas of neural architecture search, online meta-learning, and fairness-aware deep learning techniques, this project advances state-of-the-art research in Fairness in AI. This project will offer the following innovations: (1) disentangle underlying sensitive and non-sensitive causal variables from raw features via causal representation learning; (2) identify adaptive architectures for data streams via differential architecture search; (3) learn effective initializations for both primal and dual model parameters in an online-within-online manner; (4) develop robust versions of the algorithms to deal with uncertainties in model fairness and tasks, and (5) identify the training examples and latent causal variables responsible for model adaption using local and global interpretations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "425", "attributes": { "award_id": "2112033", "title": "STTR Phase I: Broad Spectrum Antimicrobial Surface Coating (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 815, "first_name": "Anna", "last_name": "Brady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-02-15", "end_date": "2022-10-31", "award_amount": 256000, "principal_investigator": { "id": 817, "first_name": "Dana", "last_name": "Totir", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 225, "ror": "", "name": "NANOIONIX, LLC", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 816, "first_name": "Steven L", "last_name": "Suib", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 225, "ror": "", "name": "NANOIONIX, LLC", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to minimize the number of hospital-associated infections which contribute to almost 100,000 deaths each year in the US at an annual cost exceeding $30 B. Reducing the surface-borne transmission of pathogens can limit the spread of pathogenic diseases, thus minimizing transmission from contaminated surfaces in both public and healthcare settings is of utmost importance. Disinfectants can inactivate pathogens but require an active engagement that places undue burden on personnel and the environment; furthermore, the success rate varies, and the results do not persist. Most current antimicrobial materials are expensive, toxic to humans and the environment, and show minimal viral inactivation. Self-decontaminating surfaces provide a much-needed solution to these limitations, especially in areas with high-touch surfaces and large population flow. Customers, from hardware and elevator manufacturers to hospitals and airlines, will benefit from an effective, low-cost, environmentally sound solution to decontamination and customer safety for conditions such as the current COVID-19 pandemic. This project has potential impact for the $8 B antimicrobial coatings market, while delivering improved clinical outcomes. This STTR Phase I project proposes to demonstrate the efficacy of a breakthrough, permanent ceramic coating technology against both viruses and bacteria. A pure ceramic coating that exceeds the Environmental Protection Agency’s (EPA’s) requirements will be synthesized and deposited on relevant substrates. The key to reaching this goal is gaining an understanding of the mechanism of microbial inactivation – believed to be the spontaneous generation of reactive oxygen species (ROS) on the surface of the ceramic – and how to maximize them in a practical coating. Spectroscopic techniques will be used to rapidly assess the number and type of ROS generated and thus the efficacy of the materials. Optimization will occur through the addition/substitution of targeted alkali, alkaline earth, transition, and/or main-group metals to control the lattice of the material and lock-in specific valence states to optimize the ability of the ceramic to generate large numbers of the appropriate reactive oxygen species. Tests will be performed against both viral and bacterial challenges to correlate the results of the rapid screening assessment with antimicrobial effectiveness. Pure ceramic thin films will be deposited, and the antimicrobial efficacy of these films tested.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "424", "attributes": { "award_id": "2149191", "title": "The Impact of Disruptions to Migration on Land Use and Resilience in Agricultural Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 810, "first_name": "Jeffrey", "last_name": "Mantz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-05-01", "end_date": "2025-10-31", "award_amount": 415617, "principal_investigator": { "id": 814, "first_name": "Amanda", "last_name": "Carrico", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 172, "ror": "", "name": "University of Colorado at Boulder", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 811, "first_name": "Katharine", "last_name": "Donato", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 812, "first_name": "Emily", "last_name": "Burchfield", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 813, "first_name": "Christopher", "last_name": "Small", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 172, "ror": "", "name": "University of Colorado at Boulder", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will investigate the complex linkages between migration, rural livelihoods and land use focusing specifically on mass return migration to rural areas during the COVID-19 pandemic. Using a mixed-methods approach that integrates longitudinal survey data with remotely sensed land cover data, this project will reveal how pandemics effect rural communities’ livelihoods. This project builds on a previously conducted environment and migration survey in 2019 that collected detailed socio-economic data from 4000 households by conducting a follow-up survey in 2022 of the same households. These survey results coupled with the land cover change data will illustrate agriculture changes over this four-year period caused by disruptions to migrant networks, labor supply, and employment. The results of this study will explain how migration impacts agriculture and land use, results that provide an understanding of how rural communities cope with the socio-enviromental impacts of disruptions like a pandemic.The question of how migration impacts land use change in rural areas is fundamental for understanding factors that impact food security and livelihoods. To address this question, this team of researchers will investigate how migration and land use in rural areas vary over time and across contexts; how the large-scale return of migrants has impacted land use; and how migration, livelihood activities, and land use correlate with resilience during the pandemic. By linking historical land cover data with detailed retrospective household survey data, the project will reveal how field-scale land cover dynamics interact with household- and community-dynamics over time and during periods of stress. Findings from this work will be shared with community stakeholders who face pressing and difficult questions about how to prepare and support rural communities during times of economic stress and transition. The data, methods and tools developed from this project will be widely available and are generalizable to rural settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "423", "attributes": { "award_id": "2151477", "title": "SBIR Phase I: Continuous Manufacturing for Nucleic Acid Lipid Nanoparticles to Improve the Supply Chain of Therapeutics and Vaccines (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 808, "first_name": "Kaitlin", "last_name": "Bratlie", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-02-15", "end_date": "2022-11-30", "award_amount": 256000, "principal_investigator": { "id": 809, "first_name": "Antonio P", "last_name": "Costa", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 224, "ror": "", "name": "DIANT PHARMA INC.", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 224, "ror": "", "name": "DIANT PHARMA INC.", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the need for advanced manufacturing technology that can produce future therapeutics and vaccines. Future clinical treatments will rely on continuous manufacturing to meet demand, both with respect to volume and drug product personalization. This project will incorporate continuous manufacturing principles and process analytical sensors and technology. These processes will enable faster responses to global health crises, such as the COVID-19 pandemic.This Small Business Innovation Research (SBIR) Phase I project will develop a compact, end-to-end, advanced manufacturing system for nucleic acid lipid nanoparticles. This new system will follow current Good Manufacturing Practice (cGMP) and will support end-to-end manufacturing by connecting to a nucleic acid assembly system and a fill-finish system to produce injectable-ready materials. One major goal of this research is to advance the understanding of nanoparticle drug delivery to enable manufacturing injectable ready materials on demand and on-site.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "422", "attributes": { "award_id": "2151672", "title": "SBIR Phase I: A platform for simulating the combined effect of human behavior and environment on airborne infectious spread (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 806, "first_name": "Alastair", "last_name": "Monk", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": "2023-02-28", "award_amount": 255842, "principal_investigator": { "id": 807, "first_name": "Adam", "last_name": "Ryason", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 223, "ror": "", "name": "INTELLIGENT MEDICINE INC", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 223, "ror": "", "name": "INTELLIGENT MEDICINE INC", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to minimize infection by contagious diseases, such as COVID-19. This project advances a cloud-based platform for simulating particle flow in heavily populated, dynamic environments. It will enable facility managers and health/ safety stakeholders to simulate viral particle dispersion in indoor environments for design and mitigation procedures (disinfection, evacuation, etc.). This technology can play a role in mitigating the ongoing effects of the current COVID-19 pandemic and better prepare facilities for the next pandemic. This Small Business Innovation Research (SBIR) Phase I project supports facility planning and response of infectious disease outbreaks. The project advances a hybrid computational approach to utilizing multi-scale fluid analysis for faster-than-real-time multimodal simulation. The research objectives are to: (1) create a simulation platform that can parallelize equations and perform at near real-time or real-time, which will provide a means to simulate multimodal interactions in real buildings, such as contamination spread in fluid flow, when analyzed with human behavior and mobility; (2) characterize and validate the results of the simulator by measuring particle spread in multiple real building scenarios. It is anticipated that the simulation results of particle trajectory and surface contamination will be at least as accurate as state-of-the-art high-fidelity computational fluid dynamic techniques, but delivered in real time. This project will provide an environment and behavior-specific simulation essential for optimizing airflow and facility controls to reducing airborne infectious transmission.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "421", "attributes": { "award_id": "2207436", "title": "RAPID: Using Mobile Phone Data to Understand the Impacts of the COVID-19 Pandemic on Food Assistance Use in Alaska", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [], "program_officials": [ { "id": 802, "first_name": "Erica", "last_name": "Hill", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-02-01", "end_date": "2023-01-31", "award_amount": 200000, "principal_investigator": { "id": 805, "first_name": "Guangqing", "last_name": "Chi", "orcid": "https://orcid.org/0000-0003-0888-7964", "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": "['https://arcticpolaris.org']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 803, "first_name": "Junjun", "last_name": "Yin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 804, "first_name": "Megan", "last_name": "Mucioki", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic has strained national and international transportation systems, affecting the cost and availability of food and other essentials. The pandemic has also exacerbated economic inequalities, disproportionately affecting vulnerable and low-income communities. In Alaska, most households rely on costly imported foods, and many, especially those with children, are experiencing food insecurity and undernutrition. This project investigates the impact of the COVID-19 pandemic on household use of food assistance in urban Alaska over the past three years. Through an innovative methodology using mobility data and spatial analysis, the PI team evaluates links between social and demographic variables and food pantry access, identifying food insecurity hotspots where need is greatest. This methodology may be applied elsewhere in the U.S. to identify and assist communities facing food insecurity. Working with local partners, research findings will be rapidly disseminated to stakeholders to inform food assistance programs. Research findings will also be used for university curriculum development and workshops. More broadly, assessment and response to food assistance needs during periods of crisis will improve the household security of vulnerable and low-income Americans.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "420", "attributes": { "award_id": "2148566", "title": "The Impact of Covid-19 on the Educational and Career Outcomes of First-Generation College Students and their Families", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 798, "first_name": "Jeffrey", "last_name": "Mantz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-07-01", "end_date": "2025-06-30", "award_amount": 355166, "principal_investigator": { "id": 801, "first_name": "Katherine A", "last_name": "Mason", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 222, "ror": "https://ror.org/05gq02987", "name": "Brown University", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 799, "first_name": "Andrea", "last_name": "Flores", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 800, "first_name": "Sarah", "last_name": "Willen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 222, "ror": "https://ror.org/05gq02987", "name": "Brown University", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true }, "abstract": "The Covid-19 pandemic has greatly disrupted the education of first-generation college students—those whose parents did not complete a college degree. These students and their parents are often low-income, racial/ethnic minorities, and/or of an immigrant background. Compared to other families, they have fewer resources to absorb the impact of the educational and social crises stemming from the pandemic, but also have more at stake in completing a college degree. In families of first-generation college students, parents and children strive together for individual and collective success based on the belief that higher education will advance the family's economic mobility, improve their social status, and help them fulfill their obligations to each other. This research examines how the Covid-19 pandemic has affected the educational and life goals of first-generation college student families and the actions taken in support of these goals. The project findings, to be shared in public-facing documents and web-based formats including a public archive, informs university supports and social services for vulnerable learners and families. This project is jointly funded by Cultural Anthropology and the Established Program to Stimulate Competitive Research (EPSCoR).The project hypothesizes that the Covid-19 pandemic has led first-generation college students and their families to prioritize caretaking actions aimed at immediate practical needs over the longer- term goals of better lives enabled by education. This hypothesis will be investigated through three years of data collection and analysis. Sixty parent-student pairs will each participate in: 1) two years of monthly journaling on the Pandemic Journaling Project (PJP) platform, created by two of the PIs in May 2020; 2) two one-on-one interviews with researchers; and 3) two interviews conducted between parent and student. These varied methods will capture families' shifting thinking, goals, and actions in relation to education and well-being. Understanding these perspectives and choices will advance theories of how families seek to create meaningful lives through both education and caregiving in the wake of crisis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "419", "attributes": { "award_id": "2148920", "title": "Memorialization, Contested Knowledge, and the Sociopsychological Impacts of Disinformation in the Context of COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 794, "first_name": "Jeffrey", "last_name": "Mantz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-06-01", "end_date": "2025-05-31", "award_amount": 350415, "principal_investigator": { "id": 797, "first_name": "Sarah E", "last_name": "Wagner", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 174, "ror": "https://ror.org/00y4zzh67", "name": "George Washington University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 795, "first_name": "Joel C", "last_name": "Kuipers", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 796, "first_name": "Roy Richard", "last_name": "Grinker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 174, "ror": "https://ror.org/00y4zzh67", "name": "George Washington University", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "The waves of infection and variants of SARS-CoV-2 causing social disruption, sickness, and death continue to reveal a crisis in scientific expertise and authority, as well as the widespread politicization of the pandemic among policymakers and their constituents. This project examines how disinformation (the intentional airing of misleading information), misinformation (falsehoods), and the “infodemic” (a condition of excessive information that makes the solution to a problem more difficult to achieve), influence how individuals and communities in the United States mourn the dead. It focuses on how people manage their social and psychological lives when COVID-19 deaths are variously mourned, dismissed, or blamed on others in a politically fractious environment. The study contributes to understanding the social impact of misinformation and informs public policy responses to both the current pandemic and future public health crises that result in mass fatality, incomplete mourning, and politicized death. The project will also train eighteen graduate and undergraduate students in scientific research methods over the course of the three-year study.While most studies of public debates focus on texts, such as political speeches, newspaper and scholarly articles, this project explores what behaviors, in the context of the pandemic, have become central to the experience of mourning, and how mourners seek accountability in homes, cemeteries, grief counseling sessions, rituals, virtual commemorations, and social media posts, among other venues. In doing so, it addresses: (1) how COVID-19 misinformation has shifted over the course of its evolution; (2) how contested knowledge has shaped the mourning process for COVID-19 victims and their families; (3) how COVID-19 mourners have defined and pursued accountability in their efforts to counter misinformation; and (4) how altered burial, funeral, and commemorative practices affect mourning. Through social media analysis, in-person and virtual ethnographic engagement, and in-depth interviews, the project analyzes claims and counterclaims in their linguistic, media, and social relational contexts of use. Data and findings will contribute to anthropological understanding of ritual, particularly its efficacy in a contested environment, as well as provide important insight into the processes and consequences of incomplete mourning during a prolonged public health crisis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "418", "attributes": { "award_id": "2152423", "title": "NSF SoS: DCI Identifying Effective Science Communication Outcomes with Social Media During the COVID-19 Pandemic", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 792, "first_name": "Mary", "last_name": "Feeney", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-04-01", "end_date": "2025-03-31", "award_amount": 370093, "principal_investigator": { "id": 793, "first_name": "Noriko", "last_name": "Hara", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 221, "ror": "https://ror.org/01kg8sb98", "name": "Indiana University", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 221, "ror": "https://ror.org/01kg8sb98", "name": "Indiana University", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "Throughout the COVID-19 pandemic, people have increasingly sought scientific information online, especially through social media. Although the COVID-19 pandemic has compelled both laypeople and scientists to use online social media to communicate, there is a large gap in how scientists communicate knowledge and how laypeople understand and interpret scientific information. The proposed project aims to examine the best practices and lessons learned from scientists working on COVID-19-related topics who interact with the public using two-way social media communication tools. This project examines and identifies research-based strategies to help scientists improve online science communication using social media to better inform, engage, and inspire the broader population to strengthen support of America’s global leadership in science. The proposed project’s goal is to empirically examine the functions used (e.g., retweets) and content posted on social media platforms, as well as interview data with users of these platforms (scientists and the public), to develop research-based strategies for scientists to engage with the public using two-way online communication. The research team will use a mixed method approach to convert results into strategies, as well as a Toolkit of resources, for helping scientists use social media. The data will be collected through observation of social media platform functions (Twitter and Reddit AMA), content analysis of online interactions, and interviews with 45 COVID-19 related scientists and 15 lay participants. The expected outcomes of the study will contribute a theoretical model of two-way online science communication and advance the field of Science of Science and social media research. The research findings will be shared with the public, and two informational videos (one for scientists, and the other for the public) will be distributed along with the Toolkit for scientists via social media.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1385, "pages": 1397, "count": 13961 } } }