Jason Jurjevich
 

>Data For Good<

Harness the power of geographic data to:
  • Illuminate the lived experiences of individuals and communities
  • Expose social and economic inequality
  • Support the development of equitable, sustainable, and resilient cities

 
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Jason Jurjevich, PhD

School of Geography, Development & Environment

University of Arizona

 
 

Present

University of Arizona

 

2010

Ph.D. in Geography, University of Arizona

 

2005

MA in Geography, University of North Carolina at Charlotte

 

As a broadly trained human geographer, I use critical quantitative methods to expose social and economic inequality in cities. I have a particular interest in the census, migration, and housing, with recent work examining housing injustice in Baltimore and Tucson.  Currently, I am an Assistant Professor in the School of Geography, Development & Environment at the University of Arizona.

Since 2010, my work has been cited in numerous media outlets, including National Public Radio (NPR), Univision, CityLab, Governing Magazine, New York Times Magazine, Atlantic Cities, and The Chronicle of Higher Education. 

In 2018, I launched Census 20/20, a nationwide-focused project to foster community preparedness and inspire individual action to support a fair and accurate census in 2020. 

In September 2022, I launched my most recent project, Mapping Racist Covenants. This project highlights the breadth of racist covenants, conditions, and restrictions (CCRs) across neighborhoods and subdivisions in Tucson between 1912 -1968 using interactive web-based mapping.

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Articles, Datasets, Book Chapters, and Reports

 

Research article

Summer 2026

Hannah K. Friedrich, Beth Tellman, Jason R. Jurjevich, Mark Kear, and Laura Bakkensen. “Do Battle With Insurance”: Post- Hurricane Insurance Litigation in Southwest Louisiana." The Russell Sage Foundation Journal of the Social Sciences.

 

Overview

Census data are foundational to democracy, research and equitable urban policy. In this article, I first review the accuracy of the 2020 Census. The data show that the 2020 Census, while accurate, excluded millions of Americans; undercounts were severe for people of color, immigrants, and other marginalized communities. Second, I explain the US Census Bureau’s decision to protect individual privacy by intentionally distorting census data with differential privacy, leading to the ‘digital displacement’ of certain populations. Together, the ‘double whammy’ of worsening coverage error and differential privacy disproportionately affects communities of color and other marginalized groups, underscoring issues of data justice. I argue for practicing statistical citizenship, a theoretically informed approach that properly situates data limitations and simultaneously recognizes the politics of census data to support data justice.

Research article

February 2026

Jason R. Jurjevich. “Census Undercounts, Digital Displacement, and Data Justice: What Social Scientists and Data Users Need to Know About the 2020 US Census." International Journal of Urban and Regional Research (IJURR). DOI: 10.1111/1468-2427.70069

 

Overview

The Mapping Racist Covenants (MRC) project tells the story of racist covenants in Tucson, specifically by mapping the geography of racial covenants across Tucson neighborhoods and subdivisions, focusing on those enacted between 1912-1968. This research deposit includes the data, documents, and geographic shapefiles created for the MRC project.

Dataset

September 2025

Jason R. Jurjevich, Yoga Korgaonkar, Christine Kollen, Arden Holloway, and Liz Wilshin. “Data and Geographic Shapefiles for Mapping Racist Covenants in Tucson, AZ." University of Arizona Research Data Repository. DOI: 10.25422/azu.data.25447900

 

Overview

Comparative urban research in the USA has an unacknowledged data and methodological problem at the metropolitan scale, rooted in geographic and definitional boundary changes of urban areas across time. In this article, we introduce a new spatial dataset, decision criteria, and methodological protocol for longitudinal and comparative research with US metropolitan statistical areas (MSAs)—known as ‘metros’—in a way that centers a ‘city-centric’ approach to comparison while significantly reducing spatial error and bias. Our improved dataset covers the 50 largest MSAs from 1980-2020.

Research Article

March 2025

Jason R. Jurjevich, Katie Meehan, Nicholas M.J.W. Chun, and Greg Schrock. “Advancing Methods for Comparative Urban Research: A City-Centric Protocol and Longitudinal Dataset for US Metropolitan Statistical Areas.”
PLOS One.
DOI: 10.1371/journal.pone.0316750

 

Overview

This Article presents a longitudinal analysis of household access to running water—a vital component of social infrastructure—in the 50 largest US cities since 1970. The results indicate that water access has worsened in an increasing number and typology of US cities since the 2008 global financial crash, disproportionately affecting households of color in 12 of the 15 largest cities. We provide evidence to suggest that a ‘reproductive squeeze’—systemic, compounding pressures on households’ capacity to reproduce themselves on a daily and societal basis—is forcing urban households into more precarious living arrangements, including housing without running water.

Research article

December 2024

Katie Meehan, Jason R. Jurjevich, Lucy Everitt, Nicholas M.J.W. Chun, and Justin Sherrill. “Water Access Worsens for Low-Income Households of Color in Elite US Metros.” Nature Cities. DOI: 10.1038/s44284-024-00180-z

 

Overview

In Baltimore, Maryland, more than 55,000 homes—roughly 30 percent of all residential plots—are subject to ground rent, a legacy of British feudal property law. Under this landlord–tenant system, the homeowner makes payments to the ground leaseholder, who maintains rights to the land. Using census and ground rent administrative data, we map the geography of ground rent in Baltimore. Our results reveal that originally a tool of class dispossession, ground rent became racialized in the 1950s and 1960s and today overwhelmingly affects Black communities and low-income households. We rely on a critical quantitative framework to illustrate how people, place, power structures, and relationality produce the pernicious and predatory “ground rent machine.”

Research article

June 2024

Jason R. Jurjevich and Dillon Mahmoudi. “The Ground Rent Machine: The Story of Race, Housing Inequality, and Dispossession in Baltimore, Maryland.” Annals of the American Association of Geographers. 114(7):  1505-1525. 
DOI: 10.1080/24694452.2024.2353172

 

Overview

Our research documents emerging trends and persistent gaps in urban water access over the past 20 years, before and after the Great Recession of 2008. Focusing on 15 major metropolitan areas and drawing on analysis of nearly two decades (2000-2017) of Census data, we identify racialized disparities in household water access, compare trends between cities and over time, and point to worsening conditions for urban dwellers, especially renters.

Comprehensive report

September 2021

Katie Meehan, Jason R. Jurjevich, Alison Griswold, Nicholas M.J.W. Chun, and Justin Sherrill. “Plumbing Poverty in US Cities: A Report on Gaps and Trends in Household Water Access, 2000 to 2017.” DOI: 10.18742/pub01-601

 

Overview

In this study, we explain the drivers of infrastructural inequality in the 50 largest metropolitan areas. Our analysis reveals spatial and sociodemographic patterns of racialized, class-based, and housing disparities that characterize plumbing poverty.

Research Article

November 2020

Katie Meehan, Jason R. Jurjevich, Nicholas M.J.W. Chun, and Justin Sherrill. “Geographies of Insecure Water Access and the Housing-Water Nexus in US CIties.” DOI: 10.1073/pnas.2007361117

 

Overview

In this article we explore the understudied socio‐environmental contradiction where the actual environmental outcomes of neighborhood transformation may not be what we expect.

Research Article

March 2019

Jennifer L. Rice, Daniel Aldana Cohen, Joshua Long, and Jason R. Jurjevich. “Contradictions of the Climate-Friendly City: New Perspectives on Eco-Gentrification and Housing Justice.” IJURR: International Journal of Urban and Regional Research. DOI: 10.1111/1468-2427.12740

 

Overview

Aging and lacking infrastructure are major impediments to economic development in rural America. To address these issues, civic leaders often look to state and federal infrastructure grant/loan funding, where eligibility is often based on income requirements established by the US Census Bureau’s American Community Survey (ACS). The problem, especially for rural communities, is that ACS data contain a high degree of statistical uncertainty (i.e., margin of error) that is often disregarded for determining program eligibility. Using an example from Oregon, I recommend guidelines for how states can assist rural communities with statistically unreliable ACS estimates.

Research Article

April 2019

Jason R. Jurjevich.  “Confronting Statistical Uncertainty in Rural America:  Toward More Certain Data-Driven Policymaking Using American Community Survey (ACS) Data,” in The Geographical Analysis of Population—Essays in Honor of David A. Plane. Rachel A. Franklin, editor.  London:  Springer.  DOI:  10.1007/978-981-13-9231-3_7

 

Overview

Many planners do not understand the statistical uncertainty in ACS data, find it difficult to communicate statistical uncertainty to stakeholders, and avoid reporting MOEs altogether. These practices may conflict with planners’ ethical obligations under the AICP Code of Ethics to disclose information in a clear and direct way.

Research Article

April 2018

Jason R. Jurjevich, Amy L. Griffin, Seth E. Spielman, David C. Folch, Meg Merrick, and Nicholas N. Nagle. “Navigating Statistical Uncertainty: How Urban and Regional Planners Understand and Work with American Community Survey (ACS) Data.” Journal of the American Planning Association. DOI: 10.1080/01944363.2018.1440182

*Selected by JAPA editors as a finalist for 2018 Paper of the Year.

 

Overview

To illustrate how migration streams can exhibit very different levels of ‘political effectiveness,’ this research substantively addresses three key issues under-examined in the current literature: 1) the ability of migration to both reinforce and dilute party strength, 2) the changes in partisanship at the origin and destination of migration streams effected through processes analogous to ‘packing’ and ‘cracking’ in electoral redistricting literature, and 3) the importance of migration selectivity. This research uses an innovative, albeit far-from-precision method to suggest how recent U.S. migration trends may portend changes in Republican and Democratic partisanship.

Research Article

September 2012

Jason R. Jurjevich and David A. Plane. Voters on the Move: Compositional Effects of Migration on State Partisan Politics.”  Political Geography.  31(7):  429-443.  DOI:  10.1016/j.polgeo.2012.08.003

 

Overview

Our analysis of special county-to-county migration tabulations of Census 2000 data discloses that, when flows are disaggregated by age, radically different patterns of net population redistribution are taking place upward and downward within the national urban hierarchy. The movements at the late-career, empty-nester, and retirement stage are the most “demographically effective” or unidirectional. The elderly fleeing large metropolitan areas have been congregating in micropolitan and rural counties with special climatic and other natural amenities. The opposite net flow is found for younger adults, who have been flocking into megametropolitan conurbations.

esearch Article

January 2009

David A. Plane and Jason R. Jurjevich “Ties that No Longer Bind?  The Patterns and Repercussions of Age-Articulated Migration Up and Down the US Urban Hierarchy.” Professional Geographer. 61(1): 4-20. DOI:  10.1080/00330120802577558

 

Overview

Certain populations require more data distortion to guarantee the same level of privacy compared to larger populations. Given this situation, we explore two questions in this study: 1) how reliable are differentially-private data for Arizonans of color?  2) to what extent does differential privacy introduce unequal data distortion among Arizonans of color at sub-county geographies? 

We explored the effects of differential privacy, a new tool of disclosure avoidance in census data, for communities of color in Southern Arizona.

 

Overview

Using past census household non-response rates as a proxy for the HTC population, this report provides detailed range projections of Arizona’s Census 2020 HTC population, by county, under three scenarios.

Arizona is traditionally a state with a high Hard-to-Count (HTC) population. In Census 2010, only 77.6% of Arizona households mailed back their census form, ranking Arizona’s census participation 38th across the 50 states and Washington, DC.

 

Overview

State and local governments, as well as philanthropic organizations, share a responsibility to secure funding that supports efforts that will fairly and accurately count all Oregonians, including individuals in hard-to-count (HTC) communities.

 

We found that funding for Census 2020 in Oregon required raising at least $7.0 to $8.4 million.