Represents Grant table in the DB

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            "type": "Grant",
            "id": "10747",
            "attributes": {
                "award_id": "2305495",
                "title": "Variants in Biology Education: What can we learn from pandemics?",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "IUSE"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 2366,
                        "first_name": "Mary",
                        "last_name": "Crowe",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
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                    }
                ],
                "start_date": "2023-01-15",
                "end_date": "2023-12-31",
                "award_amount": 49975,
                "principal_investigator": {
                    "id": 26798,
                    "first_name": "Teresa",
                    "last_name": "Mourad",
                    "orcid": null,
                    "emails": "[email protected]",
                    "private_emails": null,
                    "keywords": "[]",
                    "approved": true,
                    "websites": "[]",
                    "desired_collaboration": "",
                    "comments": "",
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                },
                "other_investigators": [
                    {
                        "id": 26797,
                        "first_name": "Warren B",
                        "last_name": "Sconiers",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "awardee_organization": {
                    "id": 1962,
                    "ror": "https://ror.org/03y54e085",
                    "name": "Ecological Society of America",
                    "address": "",
                    "city": "",
                    "state": "DC",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "From March 23-25, 2023, the 8th Life Discovery – Doing Science Biology Education Conference (LDC) will convene at Florida A&M University on the theme, “Variants in Biology Education: What can we learn from pandemics?” This event is co-organized by the Ecological Society of America (ESA), the Botanical Society of America (BSA), and the Society for the Study of Evolution (SSE). There are real impacts on people’s lives and decisions when scientifically based information is not understood and/or rejected. The conference will draw from socio-behavioral research which can be applied to pedagogy. The conference theme wrestles with three key issues impacting teaching and learning which form three thematic tracks: a) adapting to and teaching disease ecology; b) science misinformation, and c) research innovation and careers. These tracks will highlight promising practices, programs, and strategies that can be implemented in the classroom while fostering a longer term effort to improve biology education and career readiness. It will also build on the previous conference which focused on inclusive educational strategies critical to engaging both science and non-science majors, especially underrepresented minority populations.  By facilitating discovery and exchange of tools and resources for STEM and media literacy, the event will position faculty to help generations of digital natives who rely on social media for information to combat false information and extend far beyond the classroom to students’ homes and communities. NSF funds will support the connection and participation of under-resourced faculty in organismal biology and environmental sciences from minority-serving institutions, community colleges and primarily undergraduate institutions, who are frequently isolated across the US.\n\nThe conference will provide a forum for educators to engage in a discipline-based national conversation three years after the onset of the COVID-19 pandemic inexorably rocked the world. Its impact on education has been no less profound. The conference organizers will take advantage of this opportunity to use very real phenomena backed by lived experience to discuss key ideas in ecology and evolutionary biology that have previously been difficult to teach.  At the same time, this conference will provide a platform for educators to discuss approaches to teaching the difference between fake news and learning real science. An exchange of strategies will be beneficial so educators might respond more effectively in different sociopolitical climates to a fast-evolving scientific phenomenon and an even faster “viral resistance” to information based on science. Made visible by the pandemic, innovations in science and research are introducing new questions that can now be asked and answered. The conference will highlight opportunities for emerging STEM and STEM-adjacent careers fueled by technological advancements such as those offered by new RNA research, as well as key findings in the social sciences which are mobilizing new understandings of vulnerability and resilience globally. The conference will also extend education reform efforts propelled by \"Vision and Change in Undergraduate Biology Education\" (AAAS) a decade ago and highlight recent advances to provide a cohesive and modern approach to ecology education through ESA’s Four-Dimensional Ecology Education (4DEE) framework.  The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students.\n\nThis 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": "10760",
            "attributes": {
                "award_id": "2245139",
                "title": "NSF Showcase for DUE Projects at the ACM SIGCSE Symposium",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "IUSE"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 1983,
                        "first_name": "Paul",
                        "last_name": "Tymann",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2022-12-15",
                "end_date": "2025-11-30",
                "award_amount": 182046,
                "principal_investigator": {
                    "id": 13359,
                    "first_name": "Jian",
                    "last_name": "Zhang",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 1306,
                    "ror": "https://ror.org/04dyzkj40",
                    "name": "Texas Woman's University",
                    "address": "",
                    "city": "",
                    "state": "TX",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "The Technical Symposium on Computer Science Education organized by the Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE) is one of the oldest ACM conferences and is SIGCSE’s flagship conference. The Symposium is held annually, in North America, and is the premier venue for computing education researchers to meet and disseminate their work. The NSF showcase at the SIGCSE Technical Symposium provides an opportunity for NSF grant recipients to showcase and disseminate the results of their work. The NSF showcase provides grant recipients the opportunity to circulate their ideas, obtain feedback, recruit collaborators and adopters, and consult with program officers much earlier in the project cycle, providing crucial insights that improve the likelihood of the projects succeeding and the findings being disseminated. The NSF showcase will also include opportunities for members of the computing education community to connect with NSF program officers to explore grant programs and to receive feedback on proposal ideas. \n\nThe NSF showcase will facilitate a discussion among the affinity groups who collectively participate in computing education research, specifically targeting issues related to preparing students who are computationally fluent, and building and enhancing the computing professional workforce, which includes research software engineers, research data science professionals, advanced cyberinfrastructure systems professionals, and others. The NSF showcase provides a way for many computing educators to see NSF projects in progress, to interact with NSF program officers, to learn about NSF programs, and discuss potential projects for funding. The SIGCSE Technical Symposium is regularly attended, with pre-pandemic attendance at 1,900 attendees. The conference primarily serves a US audience with around 90% of the attendees being from the US with an additional 5% from Canada and other attendees from Europe, Asia, and Australasia primarily. The NSF Showcase is funded by the NSF IUSE: EHR Program, which supports research and development projects to improve the effectiveness of STEM education for all students.\n\nThis 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": "4720",
            "attributes": {
                "award_id": "1256700",
                "title": "43rd Linguistic Symposium on Romance Languages: Special Session on Romance Parsed Corpora-New York City - April, 2013",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "Linguistics"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 16364,
                        "first_name": "Joan",
                        "last_name": "Maling",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
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                        "affiliations": []
                    }
                ],
                "start_date": "2013-03-01",
                "end_date": "2014-02-28",
                "award_amount": 13796,
                "principal_investigator": {
                    "id": 16365,
                    "first_name": "Christina",
                    "last_name": "Tortora",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 1143,
                            "ror": "",
                            "name": "CUNY College of Staten Island",
                            "address": "",
                            "city": "",
                            "state": "NY",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 1143,
                    "ror": "",
                    "name": "CUNY College of Staten Island",
                    "address": "",
                    "city": "",
                    "state": "NY",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "The principal object of study for a core area of Linguistics is the individual speaker's knowledge of his/her native language, or \"grammar.\" Given that a speaker's knowledge of grammar is unconscious, a challenge for the discipline is to develop reliable methodologies that uncover the right data and enhance replicability. \"Parsed corpora\" projects are an important component in an emerging methodology being used to uncover the syntactic patterns underlying speakers' use of language. These are texts, both written and spoken, which are annotated with detailed grammatical information, and then used as tools to test hypotheses about statistical tendencies in syntactic patterning. While there is a rapidly growing body of Germanic parsed corpora in the discipline, there have been equally important developments in parsed corpora in Romance.\n\nWith support from the National Science Foundation, a \"Special Session on Parsed Corpora of Romance languages\" will be held at the 43rd Linguistic Symposium on Romance Languages (LSRL43), April 17-19, 2013, at The Graduate Center of The City University of New York. As the largest annual gathering of linguists working on Romance languages, the LSRL affords the perfect occasion to make the Romance linguistics community aware of some of the most exciting recent advances in syntax, which are based on these innovative tools. The objective is to provide a focused discussion of how these parsed corpora can be used as tools by anyone in the discipline, and to thereby foster scientific activity. The Session will include three one-hour talks on both historical and synchronic parsed corpora in Romance languages: (1) the \"Modelling Change: The Paths of French\" corpus, presented by Anthony Kroch and Beatrice Santorini (University of Pennsylvania), (2) the \"Syntax-oriented corpus of Portuguese dialects,\" presented by Ana Maria Martins (University of Lisbon), and (3) the \"Tycho Brahe Parsed Corpus of Historical Portuguese,\" presented by Charlotte Galves (University of Campinas).",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "4583",
            "attributes": {
                "award_id": "1362098",
                "title": "19th Lexical-Functional Grammar Conference",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "Linguistics"
                ],
                "program_reference_codes": [],
                "program_officials": [],
                "start_date": "2014-03-01",
                "end_date": "2015-02-28",
                "award_amount": 12199,
                "principal_investigator": {
                    "id": 15814,
                    "first_name": "Damir",
                    "last_name": "Cavar",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 1310,
                            "ror": "https://ror.org/02ehshm78",
                            "name": "Eastern Michigan University",
                            "address": "",
                            "city": "",
                            "state": "MI",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [
                    {
                        "id": 15813,
                        "first_name": "Malgorzata",
                        "last_name": "Cavar",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "awardee_organization": {
                    "id": 1310,
                    "ror": "https://ror.org/02ehshm78",
                    "name": "Eastern Michigan University",
                    "address": "",
                    "city": "",
                    "state": "MI",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This award provides support for the 19th Lexical-Functional Grammar (LFG) Conference, to be held July 17-19, 2014 in Ann Arbor, Michigan. A central goal of the LFG framework is to create a model of grammar which is sufficiently sophisticated for theoretical linguists to formulate a model of natural language, but which can also be used in theoretical and applied areas of computational linguistics and natural language processing. Because of its formal rigor, LFG has been used as the theoretical basis of various machine translation tools, for example, AppTek's TranSphere, and the Julietta Research Group's Lekta. The annual conference is the largest annual LFG meeting, offering a venue for the exchange of ideas, and fostering cooperation for theoretical and computational linguists. It has a truly international outreach, with participants coming from Europe, Asia, Australia, and America. This will be the first LFG conference held in the USA since 2007. \n\nThe leitmotif of the 2014 conference is \"Language Documentation and Linguistic Theory.\" It will provide a platform for the discussion of the role of linguistic theories (LFG and other generative models, e.g. Head-Driven Phrase Structure Grammar (HPSG) and the Minimalist Program) in language documentation and descriptive linguistic research. The possibility of using theoretically motivated computational environments (e.g. Finite State Morphologies or syntactic parsers) for ongoing efforts in the domain of under-resourced and endangered languages research is highly relevant in the context of many projects seeking to document and maintain endangered languages. The conference will be followed by a one-day ParGram workshop, and a one-day workshop on unbounded dependencies in LFG.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "12878",
            "attributes": {
                "award_id": "2203723",
                "title": "Building a neurolinguistic corpus of naturalistic conversation to investigate second language grammar",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "Linguistics"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 1351,
                        "first_name": "Josie Welkom",
                        "last_name": "Miranda",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2022-09-15",
                "end_date": null,
                "award_amount": 138000,
                "principal_investigator": {
                    "id": 28824,
                    "first_name": "David",
                    "last_name": "Abugaber",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": []
                },
                "other_investigators": [
                    {
                        "id": 28823,
                        "first_name": "Jonathan",
                        "last_name": "Brennan",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "awardee_organization": {
                    "id": 2176,
                    "ror": "",
                    "name": "Abugaber, David",
                    "address": "",
                    "city": "",
                    "state": "IL",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program and SBE's Linguistics program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Jonathan Brennan at the University of Michigan, this postdoctoral fellowship award supports an early career scientist studying grammar processing mechanisms in native and second (L2) English. Given the increasing interconnectedness of the world as well as the demonstrated benefits to individuals of speaking more than one language, improving the way that second languages are taught is an area of growing importance. A critical part of this involves understanding the brain mechanisms that are involved when learners comprehend grammatical structures. However, previous brain research on language processing has typically involved artificial experimental tasks and stimuli in isolated laboratory settings that are different from what a typical language user encounters in the real world. To address this obstacle, our project harnesses advances in wireless portable brain-scanning and computerized speech recognition to investigate the grammar processing mechanisms that underlie naturalistic conversation in native and second language (L2) English.<br/><br/>Electroencephalograms (EEG) will be recorded during unscripted conversation between native and L2 speaker pairs and synchronized with transcriptions. The observed data will be compared against predictions from computer models based on different possible mechanisms of grammar. Specifically, we test hierarchical models involving nesting of abstract grammatical structures (e.g., such that a phrase like “in the house” involves processing “the house” as an internal subunit) versus sequential models based on how often words co-occur (e.g., “in” is often followed by “the,” “the” is often followed by “house,” etc.). Objective 1 asks whether previous findings of hierarchical processing in native speaker audiobook listening also hold for social interaction. Objective 2 asks whether native and L2 speakers differ in the hierarchical vs. sequential nature of their processing. Objective 3 turns to the mechanisms of social context to ask whether neural signatures of grammar processing are affected by brain-to-brain synchrony. This work informs language teaching praxis by revealing how the statistics of L2 input affect grammar learning. It also broadens participation in neuroscience by using a “crowdsource-able” experiment design with affordable portable brain-scanning devices. Finally, by building an open-access corpus of natural unscripted conversation, the audio, neural signals, and transcriptions are available to future researchers to address other language-related research questions.<br/><br/>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": "5208",
            "attributes": {
                "award_id": "0918613",
                "title": "Collaborative Research: Updating the U.S. Supreme Court Judicial Database",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "LSS-Law And Social Sciences"
                ],
                "program_reference_codes": [],
                "program_officials": [],
                "start_date": "2009-09-01",
                "end_date": "2013-08-31",
                "award_amount": 138122,
                "principal_investigator": {
                    "id": 18438,
                    "first_name": "Keith",
                    "last_name": "whittington",
                    "orcid": null,
                    "emails": "[email protected]",
                    "private_emails": null,
                    "keywords": "[]",
                    "approved": true,
                    "websites": "[]",
                    "desired_collaboration": "",
                    "comments": "",
                    "affiliations": [
                        {
                            "id": 191,
                            "ror": "https://ror.org/00hx57361",
                            "name": "Princeton University",
                            "address": "",
                            "city": "",
                            "state": "NJ",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 191,
                    "ror": "https://ror.org/00hx57361",
                    "name": "Princeton University",
                    "address": "",
                    "city": "",
                    "state": "NJ",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This award is funded under the American Recovery and Reinvestment Act of 2009\n(Public Law 111-5).\"\n\nFor two decades now, virtually all systematic analysis of the contemporary Supreme Court and its members has relied on Harold J. Spaeth's U.S. Supreme Court Judicial Database. This holds for research conducted by social scientists and, increasingly, by legal academics; and it holds for quantitative and qualitative studies, as well as those more descriptive in nature. In fact, several inventories of peer-reviewed journals show that it is the rare article on the Court that derives its data from an alternative source. Monographs published by top presses also regularly rely on the Database, and the many numerical studies of the Court receiving public attention in recent years have made liberal use of the data it houses. Spaeth's product is one of those rare creatures in the law and social science world: an invention that has substantially advanced a large area of study. Without question, the Database has empowered scholars in many disciplines to conduct original, path-breaking research of the highest intellectual merit.\n\nAnd yet, however invaluable the Database, it is now starting to show its age. Along these lines, we see two major sets of issues. First, for many scholars and their students the Database is diffcult to use. Second, the Database|with its emphasis on the modern (post-1946) Court has not kept pace with scholarly interests. Historical institutionalism and its various subsets have pushed scholars to broaden their time horizons. Within the field of public law, analysts have created a veritable cottage industry devoted to studies of the Court of the 19th and early 20th centuries. Even judicial specialists who ground their work in the 21st century are beginning to apply modern social science methodologies to historical data, with the goals of testing theories of institutional development and illuminating current-day practices and patterns. \n\nWith prior support from the National Science Foundation, we have addressed the first concern and brought the Database in line with 21st century technology. We now address address the second issue. Specifically, we broaden the Database's scope by adding many more cases: the 19,675 resolved between 1792, the year of the Court's first published decision and 1946, the earliest year in the current Database. Our hope is that systematic, historical data on the Court will create an even more valuable a public, multi-user Database that will stimulate scholars and their students to explore new avenues of inquiry, as well as to revisit enduring questions that have yet to be addressed with reliable and valid data. In short, the project not only facilitates scholarship of the highest level of intellectual merit; it also has a broader impact on the community of scholars studying the Court by providing a highly reliable, comprehensive, and adaptable Database.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "5215",
            "attributes": {
                "award_id": "0919149",
                "title": "Collaborative Research: Updating the U.S. Supreme Court Judicial Database",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "LSS-Law And Social Sciences"
                ],
                "program_reference_codes": [],
                "program_officials": [],
                "start_date": "2009-09-01",
                "end_date": "2013-08-31",
                "award_amount": 259577,
                "principal_investigator": {
                    "id": 18451,
                    "first_name": "Jeffrey",
                    "last_name": "Segal",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 578,
                            "ror": "",
                            "name": "SUNY at Stony Brook",
                            "address": "",
                            "city": "",
                            "state": "NY",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 578,
                    "ror": "",
                    "name": "SUNY at Stony Brook",
                    "address": "",
                    "city": "",
                    "state": "NY",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This award is funded under the American Recovery and Reinvestment Act of 2009\n(Public Law 111-5).\"\n\nFor two decades now, virtually all systematic analysis of the contemporary Supreme Court and its members has relied on Harold J. Spaeth's U.S. Supreme Court Judicial Database. This holds for research conducted by social scientists and, increasingly, by legal academics; and it holds for quantitative and qualitative studies, as well as those more descriptive in nature. In fact, several inventories of peer-reviewed journals show that it is the rare article on the Court that derives its data from an alternative source. Monographs published by top presses also regularly rely on the Database, and the many numerical studies of the Court receiving public attention in recent years have made liberal use of the data it houses. Spaeth's product is one of those rare creatures in the law and social science world: an invention that has substantially advanced a large area of study. Without question, the Database has empowered scholars in many disciplines to conduct original, path-breaking research of the highest intellectual merit.\n\nAnd yet, however invaluable the Database, it is now starting to show its age. Along these lines, we see two major sets of issues. First, for many scholars and their students the Database is diffcult to use. Second, the Database|with its emphasis on the modern (post-1946) Court has not kept pace with scholarly interests. Historical institutionalism and its various subsets have pushed scholars to broaden their time horizons. Within the field of public law, analysts have created a veritable cottage industry devoted to studies of the Court of the 19th and early 20th centuries. Even judicial specialists who ground their work in the 21st century are beginning to apply modern social science methodologies to historical data, with the goals of testing theories of institutional development and illuminating current-day practices and patterns. \n\nWith prior support from the National Science Foundation, we have addressed the first concern and brought the Database in line with 21st century technology. We now address address the second issue. Specifically, we broaden the Database's scope by adding many more cases: the 19,675 resolved between 1792, the year of the Court's first published decision and 1946, the earliest year in the current Database. Our hope is that systematic, historical data on the Court will create an even more valuable a public, multi-user Database that will stimulate scholars and their students to explore new avenues of inquiry, as well as to revisit enduring questions that have yet to be addressed with reliable and valid data. In short, the project not only facilitates scholarship of the highest level of intellectual merit; it also has a broader impact on the community of scholars studying the Court by providing a highly reliable, comprehensive, and adaptable Database.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "5229",
            "attributes": {
                "award_id": "0921869",
                "title": "Collaborative Research: Updating the U.S. Supreme Court Judicial Database",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "LSS-Law And Social Sciences"
                ],
                "program_reference_codes": [],
                "program_officials": [],
                "start_date": "2009-09-01",
                "end_date": "2013-08-31",
                "award_amount": 366212,
                "principal_investigator": {
                    "id": 18493,
                    "first_name": "Jonathan",
                    "last_name": "Koehler",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 673,
                            "ror": "",
                            "name": "Northwestern University at Chicago",
                            "address": "",
                            "city": "",
                            "state": "IL",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [
                    {
                        "id": 18491,
                        "first_name": "Harold J",
                        "last_name": "Spaeth",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    },
                    {
                        "id": 18492,
                        "first_name": "Andrew D",
                        "last_name": "Martin",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "awardee_organization": {
                    "id": 673,
                    "ror": "",
                    "name": "Northwestern University at Chicago",
                    "address": "",
                    "city": "",
                    "state": "IL",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).\n\nFor two decades now, virtually all systematic analysis of the contemporary Supreme Court and its members has relied on Harold J. Spaeth's U.S. Supreme Court Judicial Database. This holds for research conducted by social scientists and, increasingly, by legal academics; and it holds for quantitative and qualitative studies, as well as those more descriptive in nature. In fact, several inventories of peer-reviewed journals show that it is the rare article on the Court that derives its data from an alternative source. Monographs published by top presses also regularly rely on the Database, and the many numerical studies of the Court receiving public attention in recent years have made liberal use of the data it houses. Spaeth's product is one of those rare creatures in the law and social science world: an invention that has substantially advanced a large area of study. Without question, the Database has empowered scholars in many disciplines to conduct original, path-breaking research of the highest intellectual merit.\n\nAnd yet, however invaluable the Database, it is now starting to show its age. Along these lines, we see two major sets of issues. First, for many scholars and their students the Database is diffcult to use. Second, the Database|with its emphasis on the modern (post-1946) Court has not kept pace with scholarly interests. Historical institutionalism and its various subsets have pushed scholars to broaden their time horizons. Within the field of public law, analysts have created a veritable cottage industry devoted to studies of the Court of the 19th and early 20th centuries. Even judicial specialists who ground their work in the 21st century are beginning to apply modern social science methodologies to historical data, with the goals of testing theories of institutional development and illuminating current-day practices and patterns. \n\nWith prior support from the National Science Foundation, we have addressed the first concern and brought the Database in line with 21st century technology. We now address address the second issue. Specifically, we broaden the Database's scope by adding many more cases: the 19,675 resolved between 1792, the year of the Court's first published decision and 1946, the earliest year in the current Database. Our hope is that systematic, historical data on the Court will create an even more valuable a public, multi-user Database that will stimulate scholars and their students to explore new avenues of inquiry, as well as to revisit enduring questions that have yet to be addressed with reliable and valid data. In short, the project not only facilitates scholarship of the highest level of intellectual merit; it also has a broader impact on the community of scholars studying the Court by providing a highly reliable, comprehensive, and adaptable Database.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "4727",
            "attributes": {
                "award_id": "1252125",
                "title": "Race, Place & Discretion in the Handling of Drug-Free Zone Charges",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "LSS-Law And Social Sciences"
                ],
                "program_reference_codes": [],
                "program_officials": [],
                "start_date": "2013-04-01",
                "end_date": "2019-03-31",
                "award_amount": 357669,
                "principal_investigator": {
                    "id": 16384,
                    "first_name": "Elizabeth",
                    "last_name": "Griffiths",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 303,
                            "ror": "",
                            "name": "Rutgers University Newark",
                            "address": "",
                            "city": "",
                            "state": "NJ",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [
                    {
                        "id": 16381,
                        "first_name": "Kay",
                        "last_name": "Levine",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    },
                    {
                        "id": 16382,
                        "first_name": "Joshua",
                        "last_name": "Hinkle",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    },
                    {
                        "id": 16383,
                        "first_name": "Volkan",
                        "last_name": "Topalli",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "awardee_organization": {
                    "id": 303,
                    "ror": "",
                    "name": "Rutgers University Newark",
                    "address": "",
                    "city": "",
                    "state": "NJ",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "Since the 1980s, all states have passed \"drug-free zone\" laws providing added penalties for offenders charged with distributing, or possessing with the intent to distribute, any controlled substance in public locations surrounding schools, parks, and public housing.  These laws are intended to keep illicit substances out of areas where children congregate, protect children from exposure to drug use, and foster safe public environments.  Yet little is known about whether these laws have accomplished their intended objectives, under what conditions legal decision-makers patrol these zones and apply these charges, how the criminalization of public spaces may disparately affect minorities and the urban poor, and whether offenders consider the prohibitive \"costs\" of offending in drug-free zones.  \n\nEmploying a sample of 19,063 felony drug cases closed between 2001 and 2009 in Fulton County (Atlanta), Georgia, this research evaluates the conditions under which drug-free zone charges are included in felony drug case processing.  Quantitative spatial analyses (using mapping software) will determine whether the proportion of hyper-criminalized space is greater in inner-city communities than in more suburban locales, and will explore sentencing outcomes by defendant race and racial composition of the offense neighborhoods. Additionally, interviews with police officers and prosecutors will examine whether drug-free zone charges are used conscientiously to incapacitate the most dangerous dealers, provide leverage in plea negotiations, and/or make communities and schools safer.  Finally, interviews with active dealers will probe the extent to which the perceived costs of selling in a drug-free zone may be offset by apparent benefits, such as improved foot traffic or access to prospective customers.  \n\nThis interdisciplinary, mixed methods study will extend our understanding of the collateral consequences of potentially discriminatory drug enforcement policy, thereby providing policymakers with insights regarding the efficacy of drug-free zone penalties and related place-based crime prevention policies.",
                "keywords": [],
                "approved": true
            }
        },
        {
            "type": "Grant",
            "id": "4730",
            "attributes": {
                "award_id": "1332213",
                "title": "The 2013 Space Weather Workshop; Boulder, Colorado; April 16-19, 2013",
                "funder": {
                    "id": 3,
                    "ror": "https://ror.org/021nxhr62",
                    "name": "National Science Foundation",
                    "approved": true
                },
                "funder_divisions": [
                    "Unknown",
                    "MAGNETOSPHERIC PHYSICS"
                ],
                "program_reference_codes": [],
                "program_officials": [
                    {
                        "id": 16387,
                        "first_name": "Rachel",
                        "last_name": "Walker-Kulzick",
                        "orcid": null,
                        "emails": "",
                        "private_emails": "",
                        "keywords": null,
                        "approved": true,
                        "websites": null,
                        "desired_collaboration": null,
                        "comments": null,
                        "affiliations": []
                    }
                ],
                "start_date": "2013-04-01",
                "end_date": "2014-03-31",
                "award_amount": 25000,
                "principal_investigator": {
                    "id": 16388,
                    "first_name": "Meg",
                    "last_name": "Austin",
                    "orcid": null,
                    "emails": "",
                    "private_emails": "",
                    "keywords": null,
                    "approved": true,
                    "websites": null,
                    "desired_collaboration": null,
                    "comments": null,
                    "affiliations": [
                        {
                            "id": 275,
                            "ror": "",
                            "name": "University Corporation For Atmospheric Res",
                            "address": "",
                            "city": "",
                            "state": "CO",
                            "zip": "",
                            "country": "United States",
                            "approved": true
                        }
                    ]
                },
                "other_investigators": [],
                "awardee_organization": {
                    "id": 275,
                    "ror": "",
                    "name": "University Corporation For Atmospheric Res",
                    "address": "",
                    "city": "",
                    "state": "CO",
                    "zip": "",
                    "country": "United States",
                    "approved": true
                },
                "abstract": "This supports the 2013 Space Weather Workshop to be held in Boulder, Colorado on April 16-19, 2013. This annual workshop brings together representatives of industry, academia and government to present papers and discuss issues related to space weather. This is one of the few opportunities for the broad community interested in space weather to get together.  Emphasis at the workshop is on the impacts of space weather on technology including communications, navigation, spacecraft operations and electric power. \n\nIn addition to bringing the three communities interested in space weather together this workshop invites both undergraduate and graduate students. This provides the students with information on research developments and on how that research is relevant to operations.",
                "keywords": [],
                "approved": true
            }
        }
    ],
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        "pagination": {
            "page": 1384,
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    }
}