National Science Foundation Build & Broaden Grant Award
The Center for Data Analytics and Visualization in Urban Research
DATA LITERACY ~ DEMOCRATIZATION OF DATA KNOWLEDGE ~ CROSS-DISCIPLINARY RESEARCH
Undergraduate Research Fellows
Student Opportunity: The Faculty Fellows affiliated with the Kean University Center for Data Analytics and Visualization in Urban Research seek undergraduate students in social science and urban studies related majors to work alongside Faculty Fellows engaged in cross-disciplinary research in social sciences using data analytics and visualization to advance research on urban studies.
Undergraduate Research Fellows will be paired with Faculty Fellows and Mentors to form interdisciplinary research teams conducting collaborative research for a one-year commitment. Undergraduate Research Fellows participate in the intellectual life of the Center and over the course of the summer, receive a stipend of $3,500 (8 weeks of work in support of research project, 30 hours/week, $15/hour). Students are supported and expected to present their contributions to the project at Kean University Research Days or similar event. They are also expected to attend the two data analytics and visualization workshops per semester during the academic year (AY). The Center for Undergraduate Research and Fellowships (CURF) from the Office of Research and Sponsored Programs (ORSP) will provide a $1,000 stipend for the Fall semester and the National Science Foundation, Build and Broaden Program will provide $1,000 for the Spring semester. The total stipend, including the AY and Summer will be $5,500. Undergraduate Research Fellows with the support of their Faculty Fellows and Mentors, may have the opportunity to present their work at regional or national conferences.
Project Overview: The purpose of this project is to build a scholarly community whereby faculty in the Social, Behavioral, and Economic Disciplines (SBE) and STEM disciplines at Kean University can leverage their discipline-specific knowledge and skill sets to engage in cross-disciplinary, collaborative, data-driven urban research through the following initiatives:
- To build an ecosystem whereby faculty in the Social, Behavioral, and Economic Disciplines (SBE) and STEM disciplines at Kean University can leverage their discipline-specific knowledge and skill sets to engage in cross-disciplinary, collaborative, data-driven urban research.
- To cultivate the Center of Data Analytics and Visualization in Urban Research to support urban research and examine the different possibilities for urban knowledge produced by Kean University scholars.
- To increase the number of undergraduate students conducting SBE urban research with data analytics and visualization.
- To build foundational concepts, including data literacy, democratization of data, knowledge, and cross-disciplinary collaborative research for faculty and students.
Principal Investigator: Julia Nevárez, Ph.D.
National Science Foundation / Build and Broaden 2023-2026
Terms of Undergraduate Research Fellowship
Application Link:
- Application opens on November 27th
- Application will closes on January 16th
Eligibility Requirements:
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Currently enrolled Sophomore or Junior at Kean University
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A minimum GPA of 3.2 or above
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Analytical and Evaluative skills
Duration of the Internship
- One year commitment starting Spring 2024 semester
Ngoc Dao, Ph.D. & David Joiner, Ph.D.
Associate Professors
College of Business and Public Management & School of Integrative Science and Technology (IST)
Directory (Dao)
Directory (Joiner)
Economic Conditions and the Gig Economy: Measuring the Impact and Implications for Social Welfare Programs
Background and Motivation: “Gig” (internet-mediated freelance) employment rose substantially over the past two decades; roughly 16% of American adults have ever earned money through an online gig platform. Gig jobs include those that are mediated through smartphone apps and other online platforms to perform tasks such as meal delivery, grocery delivery, and providing rides, and typically do not involve a formal employer-employee relationship. Gig workers are usually not covered by the legal rights and protections enjoyed by traditional employees (apart from the 2020 CARES Act which expanded unemployment benefits to gig workers), but gig jobs may appeal to those who seek flexible hours, self-directed work, and tax contributions.
Aim(s): To our knowledge, no existing study links gig work and social welfare participation among the working-age population. The proposed study will fill these gaps through the following three specific aims: (1) examining how federal welfare receipt and benefits differ for gig workers versus others; (2) examining how economic conditions shape the size of the gig workforce; and (3) exploring how the pandemic affects gig employment as well as the relationship between gig work and federal welfare receipt. The results of this study will help inform policy makers how future changes in the gig economy may affect social welfare. Findings will have important implications for the fiscal status of the social welfare system.
Hypothesis/Research Questions: Our collaborative exploratory interdisciplinary study addresses the following research questions: (1) What is the size of gig employment and its movements overtime? (2) How economic conditions shape the size of gig workers? (3) What are the association between gig work and participation in social welfare programs (food stamps, Medicaid, TANF, and disability benefits)? (4) How did the Pandemic affect gig employment and the relationship between gig work and social welfare income receipts?
Approach: Data will be prepared in STATA. Analysis will be conducted in Python with standard data analytics and machine learning packages (e.g., numpy, pandas, statmodels, linregress, regplot, keras, skelarn, Tensorflow, PyTorch). We will use two data sets to examine our research questions: (1) Current Population Survey Annual Social and Economic Supplement (CPS ASEC, 2005-22) and Contingent Worker Supplement (CWS, 2017); and (2) Survey of Household Economics and Decision Making (SHED, 2017-20).
Students will be required to attend two data analytics and visualization workshops each semester, participate in research for a maximum of 10 hours per semester and 30 hours during 8 weeks in the Summer.
Galia Shokry, Ph.D. & Daehan Kwak, Ph.D.
Equity In Action Postdoctoral Fellow & Assistant Professor
The Dorothy and George Hennings College of Science, Mathematics and Technology
Directory (Shokry)
Directory (Kwak)
Climate Justice in Action: Addressing Gentrification Impacts of Urban Climate Resilience Planning and Placemaking
Background and Motivation:
As green resilience infrastructure (GRI) becomes increasingly integral to urban planning for climate adaptation, it is highlighted for cost-effectiveness and diverse benefits, such as recreational opportunities, improved health outcomes, stronger social networks, and enhanced property values. However, recent research uncovers potential drawbacks, notably green climate gentrification (GCG), which disproportionately impacts low-income and minoritized communities, potentially leading to their displacement and increased exposure to new climate risks. This compounds existing vulnerabilities, creating a complex intersection of challenges. Despite heightened awareness, environmental action often prioritizes climate urgency and may perceive GCG as a socio-economic issue beyond its purview. A pressing need exists for proactive, collaborative, and inter-sectoral efforts to integrate climate adaptation and social justice goals, recognizing their interconnectedness for the long-term stability, health, and well-being of urban residents.
Aim(s) and Research Questions:
Our study seeks to (1) identify and map compounding social and neighborhood-level factors contributing to communities’ vulnerability to gentrification induced by climate action; (2) assess the effectiveness of communities’ response strategies, distinguishing the most/least supportive external interventions. Two research questions guide our investigation: (1) Which geographies are most vulnerable to GCG, and which social and neighborhood-level factors contribute to the vulnerability of these locations? (2) What strategies do communities employ to adapt to GCG, and under which conditions are these strategies most effective?
Approach:
Our approach combines quantitative and qualitative methods to understand the complex dynamics of GCG impacts in two NJ urban areas. This involves (1) employing geo-visualization tools for spatial analysis and vulnerability mapping to identify susceptible geographies; (2) engaging communities through surveys and interviews to explore socio-economic factors and adaptive strategies; (3) assessing the effectiveness of community response strategies and external interventions. To enhance accessibility and collaboration among civic organizations, local officials, and researchers, we plan to establish an interactive web-based platform, with real-time data sharing, co-mapping, and analysis.
Students will be required to attend two data analytics and visualization workshops each semester, participate in research for a maximum of 10 hours per semester and 30 hours during 8 weeks in the Summer.
Jared P. Van Ramshorst, Ph.D. & George Avirappattu, Ph.D.
Assistant Professor & Associate Professor
Center for Interdisciplinary Studies & The Dorothy and George Hennings College of Science, Mathematics and Technology
Directory (Van Ramshorst)
From the Border to the Big Apple: Asylum, Immigration, and the Politics of New York City’s Emerging “Humanitarian Crisis”
Background and Motivation:
Since spring 2022, more than 100,000 immigrants have arrived in New York City, most of them from countries in the Caribbean and Central and South America. Many immigrants lack access to food and shelter, and few have local connections and ties to the city. While these families and individuals have petitioned for asylum in the U.S., immigration court backlogs mean the process could take years, thereby stranding immigrants in New York City with little resources to draw upon. Such events have purportedly overwhelmed the city’s capacity to respond to the increase in immigration, with government officials repeatedly declaring a “humanitarian crisis” as local agencies scramble to accommodate immigrants in various spaces scattered throughout New York City’s five boroughs.
Aims:
To date, studies have not yet examined the spatial politics of this so-called “crisis.” We seek to fill this gap through the following aims: (1) Examine the ways in which New York City has responded to recent arrivals of immigrants from the Caribbean and Central and South America (2) Investigate how this response has transformed the landscape of asylum and immigration within and beyond the city (3) Explore the utility of analytical tools such as mapping, Markov Chains, and spatial analysis in the context of asylum and immigration. In doing so, we hope to deepen understandings of asylum, immigration and the politics of reception and settlement.
Hypothesis/Research Questions:
Our proposed study addresses the following research questions: (1) What issues, politics, and tensions have emerged in New York City’s so-called “humanitarian crisis”? (2) How have New York City officials and adjacent nongovernmental organizations responded to recent arrivals of immigrants from the Caribbean and Central and South America? (3) In what ways has this response transformed the landscape of asylum and immigration within and beyond the New York Metropolitan Area? (4) What utility do analytical tools such as mapping, Markov Chains, and spatial analysis hold for better understanding asylum and immigration?
Approach:
We will utilize a mixed-methods approach, including mapping and spatial analysis vis-à-vis Adobe Creative Cloud and geographic information systems (GIS) alongside critical policy analysis to address these research questions. Additionally, we plan to employ analytical tools such as Markov Chains to explore their utility in the context of immigration and the city’s emerging “humanitarian crisis.”
Students will be required to attend two data analytics and visualization workshops each semester, participate in research for a maximum of 10 hours per semester and 30 hours during 8 weeks in the Summer.