Census 2020

Subsidizing Luxury: Neoliberalism, Urban Redevelopment and the Geography of Educational Inequity

In recent decades, city governments have looked to neoliberal redevelopment policies to stimulate urban redevelopment and growth. Public private partnerships, tax increment financing zones and tax abatements are regular policy tools implemented to spur redevelopment in areas that have experienced substantial disinvestment. Redevelopment policies are critical in efforts to spur investment and population growth in neighborhoods that have lost population. But, little consensus exists to determine when is the appropriate time to end these incentive programs in neighborhoods. Should these tools still be used in areas where housing markets have rebounded and where signs of gentrification are evident?  While these tools are widely used and very popular among policymakers, a substantial body of research has found these neoliberal development strategies to reallocate public resources to the affluent while undermining traditional public institutions, such as schools, who rely heavily on property taxes for their financial needs.

Given that these redevelopment policies are most often targeted to urban neighborhoods that are served by schools with older infrastructure and greater student needs, neoliberal redevelopment policies can exacerbate the geography of educational inequity in metropolitan areas. Analysis by Good Jobs First has found that even accounting for poor data tracking, at least $1.8 billion in revenues were lost to public schools as a result of this policy in 2018 alone. The revenue lost could have funded an additional 27,000 teachers in these school systems. The influence of tax incentives on urban education in particular has spurred the topic of redevelopment policy to emerge within teacher union contract negotiations. Our recent research project sought to better understand the influence of residential tax incentives on the public education system in Columbus.

We focused our analysis on the city’s residential tax abatement program. While larger corporate tax abatements are often discussed in the media, very little attention is paid to residential tax abatements. The residential tax abatements provide 100% tax abatements for up to 15 years on residential properties built or substantially rehabbed in core urban neighborhoods. These incentives can be very important in fostering redevelopment for neighborhoods who are experiencing challenging market conditions. But some critics have questioned why abatements are still in place in neighborhoods that have experienced substantial redevelopment?

Our analysis sought to understand the characteristics of residential properties that were listed for sale or had been sold with a tax abatement in the prior 3 years. We researched MLS listings for the past three years building a database of residential properties sold or currently listed for sale with a residential tax abatement in the zip codes targeted for tax abatements.

Area map of study area and zip codes used for analysis

Our preliminary findings suggest that a very large proportion of the residential tax base is lost to through the abatement program. Properties with residential tax abatements are selling at costs much higher than nearby real estate values and are primarily only affordable to high wealth households. In short, the abatement program is subsidizing luxury housing at the expense of resources for public education in the city.

We identified 365 residential units with a tax abatement sold in the past three years (or currently listed for sale). These 365 residential units represented more than $132 million in taxable value, given the current structure of the residential tax abatement program, these properties would account for a loss of more than $130 million in tax base each year for the next 15 years. Hypothetically, even if property values did not increase, the cumulative cost of these 365 tax abated units over the course of 15 years would represent nearly $2 billion in property values that would go untaxed.

Tax abated properties are selling for much higher sales prices than local real estate values and are most likely only affordable to high wealth households. The average sales price for a 2-bedroom residential unit with a tax abatement was $434,000. A household would need at least $130,000 in annual income to afford the average tax abated 2-bedroom unit in the core of the city.

description of impacts of residential tax abatements

Figure 2: Summary of residential tax abated properties identified in our database of abated residential sales and listings.

In contrast, the median annual household income for families with children in these abatement areas is approximately $29,000. Residential abatements provide substantial cost savings to buyers and conversely loss of tax base for the school district. The highest price tax abated property was a 2-bedroom luxury condominium in the arena district which sold for $1.6 million.

Listing description and taxes paid for the most expensive residential tax abated property in our database (a 2-bedroom luxury condominium).

Figure 3: Listing description and taxes paid for the most expensive residential tax abated property in our database (a 2-bedroom luxury condominium).

The real estate taxes paid for this property was $3,100 in 2019, without the abatement the real estate taxes paid should have been more than $33,000. Thus, to subsidize this luxury condominium, the public tax base is denied more than $30,000 in taxes annually, for up to 15 years.

While it is still challenging to fully understand the effects of residential abatements on the fiscal health of the Columbus City Schools, early analysis finds some alarming trends in the long-term sustainability of the district’s tax base.

Columbus City Schools district taxable value per pupil (and state ranking) 1989 to 2019.

Figure 4: Columbus City Schools district taxable value per pupil (and state ranking) 1989 to 2019.

Data from the Ohio Department of Taxation indicates that Columbus City schools tax base is declining in contrast to other districts in the State of Ohio. When ranked against districts across the state based on the taxable value of property per pupil, Columbus City Schools was ranked 107th (out of 610 districts) in 1989 and in 2019 has fallen to ranking 423rd.

More importantly, these policies also represent an alarming disconnect between urban redevelopment policy and the sustainability of the Columbus City School district. While the abatement programs have helped spur an influx of high wealth households into abatement areas, they degrade the public resources available to the nearly 30,000 children (of which more than half live in households with income under the poverty line) in abatement areas. A diminished tax base means fewer resources to upgrade older school buildings, support the needs of students who need special services and programming within schools and impacts the district’s resilience in responding to the increased needs produced by the COVID-19 pandemic.

Our preliminary results suggest that these neoliberal development tools bolster the real estate market but at the expense of resources for children in these neighborhoods. While real estate sales have soared in these redeveloping areas, students in Columbus City schools contend with an under resourced school district. We call for a reforming urban redevelopment policies to be less focused on recruiting high wealth households and re-centered on meeting the needs of children within these core urban neighborhoods.

 

Jason Reece, Assistant Professor,

City & Regional Planning, Knowlton School

 

Victoria Abou-Ghalioum, Graduate Fellow,

School of Environment and Natural Resources

Administrative Data: Impacts on Decennial Census and Research

The Demographic Research area of the Center for Economic Studies (CES) within the U.S. Census Bureau is responsible for researching and developing innovative ways to use administrative records in decennial census and survey operations. Our team of demographers, economists, geographers, and sociologists evaluate a wide array of administrative data from other federal agencies, state governments, and third party organizations. We assess the quality and coverage of these datasets and investigate how they may be useful for the Census Bureau’s data collection and processing efforts.  In addition, we use linked census, survey, and administrative records data to conduct scholarly research and to create estimates that could not be created without linked data to better inform the American Public.

Much of the work we do hinges on the ability to link records for people across different data sources. We are able to do this because another area at the Census Bureau first uses personally identifiable information (PII), such as name, date of birth, etc., to assign anonymous unique identifiers to individuals in our census, survey, and administrative data sets. They then strip off all PII and provide an anonymized file that includes these unique identifiers to researchers like myself to investigate important research questions.

One type of analysis we often perform involves linking survey data to administrative records to see if responses to survey questions match what we find in administrative records for people found in both data sources. For example, my colleagues and I linked responses from the Current Population Survey (CPS) on Medicare coverage to Medicare enrollment data and measured the extent of survey misreporting of Medicare coverage.  In this study, we found that survey responses were mostly consistent with enrollment data but we did note a small undercount of Medicare coverage in the CPS. In another case, we linked responses by American Indians and Alaska Natives regarding Indian Health Service (IHS) coverage in the American Community Survey (ACS) to IHS Patient Registration data. With this study, we found much higher levels of discordance between survey responses and administrative records. While some of the differences we found were likely due in part to definitional differences between the data sources, our analysis also suggested true inconsistencies in reporting of Indian Health Service coverage.

We also use linked data to understand how people’s responses to decennial census and survey questions change over time. For example, we have examined responses to census and survey questions on race and Hispanic origin. In one study on American Indians and Alaska Natives, we found considerable changes in racial responses between the 2000 and 2010 censuses, and by linking individuals to their responses in ACS data we were able to evaluate the characteristics of those who changed their race and those who did not.  In another project we evaluated how people reported their Hispanic origin in the 2000 and 2010 censuses and the ACS and examined the characteristics associated with a change in response, including the impact of changes in question wording and other data collection aspects.

My current work uses linked survey and administrative records data to increase our understanding of participation in social safety net programs.  This work is part of a joint project between the Census Bureau and the U.S. Department of Agriculture’s Economic Research Service and Food and Nutrition Service, as well as multiple state partners.  States that participate in the project send us data on people that receive Supplemental Nutrition Assistance Program (SNAP), Women, Infants, and Children (WIC), as well as data on Temporary Assistance for Needy Families (TANF) benefits. We link these records to ACS data to estimate eligibility and participation in each of these programs by various demographic, socioeconomic, and household characteristics.  We send our estimates of eligibility and participation back to the states with the aim of providing data that can inform program administration. For example, if we find that a particular characteristic or geographic area is associated with high rates of eligibility for a particular program but low rates of participation, it may indicate the need for further outreach.

The team I work with recently developed a visualization displaying these estimates for a few states. The visualization allows users to examine WIC eligibility and participation rates among infants and children at the county level by various characteristics. We are currently developing a similar visualization for SNAP recipients, which will include both children and adults. This is an example of the estimates we can produce with blended data that provide the public with additional information.

Renuka Bhaskar is an OSU alumna and a senior researcher in the Center for Economic Studies at the U.S. Census Bureau. Any opinions and conclusions expressed herein are those of the author and do not represent the views of the U.S. Census Bureau.

Making Sense of Census Data Resources

In my role as Ohio State’s Geospatial Information Librarian, a lot of the work that I do is related to helping researchers – at all levels and across a wide variety of disciplines – think through how they can locate, analyze, and visualize geographic data. And a lot of the time, data products provided by the U.S. Census Bureau will be relevant for addressing the research questions that they are asking.

When we hear the word “census” in 2020, our thoughts likely turn to the decennial census, and for good reason. It is hard to overstate the importance of the 2020 Census in terms of political representation and federal funding allocation, and the ways these will impact our communities over the next decade.

But it’s also important to note that census data products cover a lot more than the decennial census. In fact, the U.S. Census Bureau conducts more than 130 different surveys and programs, including the American Community Survey (ACS), Current Population Survey (CPS), Economic Census, and Longitudinal Employer-Household Dynamics (LEHD) program, to name a few.

More recently, the U.S. Census Bureau has also been releasing a variety of interesting experimental data products, which are described as “innovative statistical products created using new data sources or methodologies that benefit users in the absence of other relevant products.” Two that garnered some attention earlier this year and that have recently gone through a second phase are the Household Pulse Survey and Small Business Pulse Survey, which provide data about the social and economic effects of the COVID-19 pandemic on American households and businesses, respectively.

As mentioned in an earlier post, data products from the U.S. Census Bureau are free and publicly available. Here are a few different ways you can access these data for research, teaching, or class assignments:

U.S. Census Bureau

A lot of census data products are directly accessible in data.census.gov, a new platform that replaced American FactFinder in early 2020. The platform features a new search interface aimed at making it easier for users to locate the data they need, with more datasets planned to be added over time. It’s also possible to browse and download data tables for various programs by topic and year. If you are unable to find the data you are looking for through either of those options, you can always go directly to the website for the specific program you are interested in to see what data access options are available (and see here for the list of all surveys and programs). TIGER data products are also publicly available for working with census data in a GIS.

data.census.gov is the U.S. Census Bureau’s new platform for facilitating data access

IPUMS

IPUMS is a great resource for accessing a number of historical and contemporary census data products not readily available elsewhere. For example, NHGIS – the National Historical Geographic Information System – provides access to summary data tables and GIS-compatible boundary files from 1790 to the present and for all levels of U.S. census geography. For those working internationally, IPUMS also recently announced the launch of IHGIS – the International Historical Geographic Information System – with data tables and GIS-compatible boundary files from population, housing, and agricultural censuses from a number of countries, with more to be added over time.

Up to this point, all of the data resources I’ve been discussing have been more focused on providing summary data, presented in aggregate at different levels of U.S. census geography. But various IPUMS products also provide access to historical and contemporary census microdata, that is, individual records containing information collected about persons or households. IPUMS USA, for example, provides access to harmonized microdata from decennial censuses from 1850 to 2010 and American Community Surveys from 2000 to the present, though geographic information for these records is limited compared to summary data. IPUMS also recently announced the release of the Multigenerational Longitudinal Panel (MLP), which links individuals’ records between censuses spanning 1900-1940, with plans to extend back to 1850 in the future.

All IPUMS data products are free and publicly available, though there is a registration process required before gaining access to these data.

IPUMS provides access to various unique historical and contemporary census data products

Licensed Resources

In addition to the public data resources described above, the University Libraries licenses several resources that provide access to census data products in a fairly user-friendly way, especially for beginners. PolicyMap and Social Explorer are two examples, both of which include interactive map viewers that facilitate some geographic exploration of the data without the need to download and import data into a GIS every time. I have worked with instructors in various departments who have incorporated one of these databases into an assignment or recommended them as data sources for student projects. One other important note about Social Explorer is that it includes data tables for the 1970, 1980, 1990, and 2000 decennial censuses normalized to the 2010 census geographies to facilitate longitudinal comparisons, with data available down to the tract level.

Social Explorer has a number of interactive map viewers for exploring census data variables

This list of census data resources is by no means exhaustive, but I hope it will be a good starting point for those looking to use census data products for research, teaching, or class assignments. Have fun exploring these resources, especially if you are new to census data or less familiar with some of the other surveys and programs conducted by the U.S. Census Bureau. And if you are having trouble finding the data you need or have other questions, you can always contact a librarian.

Joshua Sadvari

Assistant Professor, Geospatial Information Librarian

University Libraries

The Ohio State University

Map Production to Support 2020 Census Programs and Operations

Maps have always played a significant role in conducting a census. This post discusses map production within the Geography Division of the U.S. Census Bureau to support the 2020 Census.

Although most of the field operations for the 2020 Census were conducted on digital instruments rather than paper, there is still a need for paper maps to support many operations. For instance, staff in the area census offices (ACOs) use large-format paper maps to help understand and visualize the boundaries of the collection geographic areas within their ACO or to visualize the workload for a particular operation. Other operations, such as Remote Alaska, Update Enumerate, and the Island Areas Census, are conducted entirely on paper. In these cases, staff use small-format maps to locate their workloads and annotate updates in the field.

In order to provide the number of maps required for geographic programs and field operations under strict production timelines, the Census Bureau utilizes the Census Automated Map Production System (CAMPS). CAMPS is automated mapping software that runs in a batch environment. CAMPS was developed in the lead up to the 2010 Census and continues to be a major part of production mapping. Cartographers design maps by setting up project parameter tables that describe everything from the title that will appear on a map to the appearance of labels and features for each feature class that will appear on a map. During peak operations, CAMPS creates thousands of map sheets per hour. For example, for the Local Update of Census Addresses Operation (LUCA), CAMPS created more than 800,000 unique map sheets over an 11 day period!

Largely due to the digital nature of many 2020 Census operations, most operations requested that we create large-format maps on as few sheets as possible, preferably a single sheet for each mapping entity. This presented some design challenges as CAMPS traditionally scales maps to as many sheets as needed based on the density of a particular geographic type within the subject area. Due to the large variety of the sizes of the subject areas for some map types, we designed multiple scale-dependent parameter configurations for each map type. Figure 1 shows a map of the Dayton ACO. This map was created in CAMPS and identifies the boundaries of the ACO. This map type included maps with scales as small as 1:1,000,000 and as large as 1:11,000 for the ACOs in the contiguous U.S.

Although we created the vast majority of our 2020 Census field maps in CAMPS, we also used commercial mapping software to produce maps, using manual interactive design and scripting. We designed map document templates in the commercial mapping software and developed scripts to automate the creation of the maps. For the Island Areas Census, we created approximately 5,600 basic collection unit (BCU)-based maps with imagery. Figure 2 shows an example of one of these maps in Guam, which was used in the field along with additional small-format maps to conduct the Island Areas Census.

Web maps and web map applications have also become a large part of our work for the 2020 Census. Web maps are particularly valuable for the communication of 2020 Census concepts to the general public and our partners. We developed web map applications to aid in outreach efforts in hard-to-count communities with the Response Outreach Area Mapper and to indicate how the Census Bureau planned to conduct the census with the Type of Enumeration Area Viewer, the In-Field Address Canvassing Viewer, and the Mail Contact Strategies Viewer. We were able to communicate with the public about the participation of local partners in programs such as LUCA, the Participant Statistical Areas Program, and the New Construction Program. In addition, we found the web map applications to be useful for the internal tracking of the status and progress of programs.

We are currently planning and developing maps and cartographic products for the next phase of the 2020 Census: data dissemination.

Kevin Hawley is an OSU alumnus and chief of the Cartographic Products and Services Branch in the Geography Branch at the U.S. Census Bureau. Any views expressed are those of author and not necessarily those of the U.S. Census Bureau.

 

You can see more of Kevin Hawley’s important work and its basis in Geography below.

Why We Count: Geographers and the US Decennial Census

My first job out of graduate school, before I was even finished with my PhD, was at the US Census Bureau in Washington, DC. I joined shortly after Census 2000, following the advice of one of my advisors who had spent a very happy year’s sabbatical with the Population Distribution group and believed it would be a good place for me to start my career. He wasn’t wrong. My arrival coincided with the best part of the 10-year census cycle, avoiding the dry, quiet mid-decade years, as well as the ramping-up period that immediately precedes the count, and being tasked with only the fun part: analyzing the data (Fig. 1) and helping to tell the story of a decade of U.S. population change.

Figure 1: Census 2000 Migration Analysis

Source: Migration of the Young, Single, and College Educated: 1995 to 2000, https://www.census.gov/prod/2003pubs/censr-12.pdf

Much has since changed. Census 2000 was the last decennial census to include the long form—the sample of “fun” questions that asked a subset of the population about income, education, commuting, ancestry, migration, and so on. This meant that the post-census years were overwhelmingly rich with information that hadn’t been collected for a decade. Nowadays we have the American Community Survey (ACS) to provide more timely, ongoing information and rely on the decennial census only for the “short form” data: housing type and age, race, ethnicity, sex, and household relationship for each person living in a housing unit (see Figure 2 for Census 2010 short form).

Over the years, I’ve moved on from the Census Bureau and into more traditional academic positions. However, although it has been almost 20 years since I’ve worked directly with the census, my research still depends on census data. This is common for US-based population geographers, as well as sociologists, demographers, and other social scientists—what the census lacks in detail and frequency it makes up for in geographic detail and numbers (theoretically 100 percent of the population!). Along with the ACS, the census allows us to answer “what” and “where”. Other Census Bureau surveys, such as the Current Population Survey (CPS), can offer detail and frequency, but not the tract-level information many of us need and want.

Figure 2: First page of Census 2010 Form

Source: https://www.census.gov/history/pdf/2010questionnaire.pdf

The Census is “geography” in so many more ways than published research. True, it’s all about counting people, which on the face of it sounds like demography. Scratch beneath the surface, however, and there isn’t a single aspect of the Census that is not about place and geography. Start with the purpose of the Census: the drawing and delineation of geographies of representation. Undercounts—groups and individuals the Census fails to count—are also geographical, concentrated in particular places.

In fact geography underpins every aspect of the Census Bureau’s work—an entire division of the Decennial Census programs is devoted to Geography. This makes sense: a first step to counting people is updating and maintaining address files of housing units across the entire country. For many US-based geographers, our first encounter with the Bureau is often in search of geographical and not demographic data: TIGER/line files of roads, state or county boundaries, for example.

The combination of geographic and demographic data produces other information that we consume in our academic and personal lives. Ever hear people talking about the Columbus, Ohio, metropolitan area and wonder how decisions about metro areas are made? Working with the Census Bureau, the Office of Management and Budget (OMB) decides on metropolitan (and micropolitan) standards following public consultation—for example, what ties counties together as a metropolitan unit? These rules or “delineations” are then applied to Census Bureau data and lists and geographies of metro areas are published. These geographies are used by a wide range of academic researchers and policymakers, but also—very importantly—are used for disbursement of federal funding. So we rely on the Census Bureau not only for counting people but also drawing the boundaries of everyday political life that affect every one of us.

As I grow older, I admit I am less interested in the geographies of the census and more fascinated by the way in which our census both leads and follows, where social change is concerned. What do we measure? Where? For whom? Our census is socially constructed and I believe this is something to be proud of—every decade, different questions are asked and the ways of answering evolve. Where once enumerators made decisions about the race of respondents, now individuals self-identify. Where once race was categorical and unidimensional, now the form strives to capture the nuances of identity (more than one race, but also combinations of race). Where once the “head of household”—the person completing the Census form—was assumed to be the male breadwinner, now we simply have a “householder.” Where once same-sex households were assumed to reflect respondent error, now the form explicitly makes space for a wider variety of household types. Is this perfect? No! Many of these changes were demanded: the Census Bureau followed, not led. I do believe it reflects a society wrestling with difficult concepts, though, and I would encourage each of us in our research and private lives to help push our survey instruments to continue to evolve.

Moreover, the struggle to accurately measure mutable concepts and identities is simultaneously a statistical and social quandary—this is interesting and challenging! The 2020 form, for example, still asks for respondent “sex” and offers two responses: male and female. Many would argue that while this question may be technically correct, it does not capture current social understanding of gender identity. How future forms efficiently* capture both biological/assigned-at-birth sex as well as gender—and how these are then tabulated—will be challenging in many ways, but also worthwhile. The questions we ask say as much about who we are as the responses.

A final thing to be proud of (and know about): census data are free and accessible. A strong data infrastructure has emerged over time to facilitate and preserve this access, both at the Bureau but notably through NHGIS and IPUMS.

Happy Census 2020! It’s likely to be a historical census** and possibly not in a good way (pandemics are not good for censuses). Be counted and remember that geographers count!

* because a long, complicated form is less likely to be completed

** it will be in good company; most of the 1890 files were destroyed in a 1921 fire

 

Rachel Franklin
Professor of Geographical Analysis
Spatial Analytics and Modelling Lab: SAM@Newcastle
Centre for Urban and Regional Development Studies (CURDS)
School of Geography, Politics and Sociology
Newcastle University

Editor, Geographical Analysis

A First Step

I’m not a geographer by training or by discipline. I do have two Bachelor’s degrees in the following majors; Criminology, International Studies, Russian, and Political Science. I also have a Master’s degree in Public Policy and Administration. This doesn’t mean a whole lot, but what it does mean is that, there are certain issues that I’ve looked at through varying lenses depending on what discipline you’re talking about. As an example, policing and law enforcement in Criminology, Political Science, and Public Policy vary on methodology, cause and effect, history, and how to move forward depending on which one or which class you’re engaged in. The Cold War is different when you investigate the perspectives from an international relations lens versus a purely Russian cultural lens. None of them are wrong but none of them are 100% correct either. We, as human beings, engage in our world in different ways and the impacts of those actions snowball to coalesce into a much larger picture. If nothing else, what these varying disciplines have taught me is to think critically, think outside the box, and never to accept the given status quo.

Now, you would think, that something as simple as counting people would be – just that – simple. However, that is far from the case.

Yes, from a political science perspective, the census is written into the Constitution of the United States and accounts for distribution of representation across the country. The short answer about what the census is, can be wrapped up in a nice little bow by the following video.

However, the reality of the Census, is something much more complicated, long-lasting, and carries with it the ability to change our nation on a fundamental level. As the representation shifts across the country with each census count, the outcomes determine not only votes in the House of Representatives but resources distributed, prevailing ideologies, future political, social, and economic policies, and electoral college votes. Many people look at the census as a benign exercise and means very little the them personally, after all, it has little impact on their individual day to day lives.

The exact opposite is true. Maybe it’s the political science or public policy speaking, but for me, the fundamental importance of the census is the basis for everything else. The census is the first step in our nation deciding what type of country we want to be, what we value, and what is important to us. The census allows the voters to decide what type of leaders we send to Washington, and what the priorities are for the future.

The census is not the last step or the only step in changing our country and making it better, but it is the first. The first in a long line of standing up to be counted, and of encouraging the same of others – even against their fear and the prejudice they may face. The census is a call to action for anyone who is or isn’t happy with the policies being enacted on their behalf. If you ignore the call and are not counted, you are doing a disservice to yourself, your neighbors, and your community.

What does any of this have to do with Geography?

Great question! If you’re not a student of Geography-like me-, you’re not the only person asking it.

Geography is a varied discipline that encompasses not only cartography and maps, but the study of what makes those maps what they are, why people are where they are. It encompasses sustainability, mobility, climatology, social justice issues, immigration and migration, as well as land use. What does all this mean?

Well, the population isn’t spread evenly across the country. We’ve all seen the red and blue maps on election nights and how the distribution of those populations have an impact on viewpoints, ideologies, and politics. We know that the country is divided in their way of life: urban and rural. These divides correlate to race, economic status, education, and a whole host of other demographic markers that can be identified. We’ve also seen how the policies of our government impact land use, our national parks, and the regulations enacted to protect citizens from harmful pollutants. Becky Mansfield’s post regarding EPA deregulation is a great example. In Geography, not only are these issues discussed but form the foundation for critical thinking along lines that focus on the world around us and our impacts on it. The census, either directly or indirectly, has an impact on all of us. And in the end, what this all amounts to is power. Who has it? Who should get it?

We are at a critical stage. The U.S. Census bureau will end counting efforts on September 30th (a full month early), according to NPR. This means that if you hadn’t already filled out the questionnaire online, then your time is running out. You don’t have to go anywhere or talk to anyone to complete your census entry. It is the easiest first step to being a part of the process of representation you can ask for. Now is your chance to step up and be counted, just click the link below.

 

 

Suzanne M.S. Mikos

Department Manager

Department of Geography & Center for Urban and Regional Analysis

 

References and Links:

Locating the Rural Forested Community; Aka When Bugs Bunny Saved the Day

In 2012, about a dozen people began meeting at the Socio-environmental Synthesis Center (or SEYSNC) in Annapolis, MD, as part of a new project: Rural Forest Communities at a Tipping Point? Trends & Actionable Research Opportunities. We were a group of researchers spanning the social and environmental sciences from Virginia, Maine, Oregon, Ohio, Wisconsin, Quebec, and elsewhere, and we were interested in a seemingly straightforward, yet in practice elusive, concept of the rural forested community. We knew from the work we conducted in forested regions of the US and Canada that these areas had experienced dramatic employment shifts, out of extractive industries like timber or mining, manufacturing jobs in textile mills, and other activities that had previously made more intensive use of the land.

We were particularly interested in forested ecosystems that had experienced some regrowth and restoration of a variety of plant and animal species, and understanding how loss of traditional industries, burgeoning new industries like tourism, “green” manufacturing, or call centers seeking cheaper land and labor costs, were intersecting with new demographic trends, like exurban or second-home migrants.

We wanted to know which rural forested communities were able to offset job losses as traditional industries waned, while managing new threats to forests in the form of parcelization and forest fragmentation, climate change, coordination of forest management, invasive species and pests, among other factors. We had big questions we wanted to answer: if rural community and forestry futures were intertwined, in what ways were communities working to maintain or enhance these joint prospects? Were certain types of economic strategies (pursuing tourism over manufacturing) better or worse for the community or the forest? Our collective experience in studying small field sites across North America, and our transdisciplinary orientation, was to provide a rich foundation for answering these questions.

What follows is a story about data. Well, it’s really about teamwork, interdisciplinarity, measurement, accuracy versus precision, and how cartoons once came to our proverbial rescue.

Lesson 1: Collaboratively define a research object

We had assembled an intrepid disciplinary team of around a dozen ecologists, remote sensing specialists, environmental economists, rural sociologists, and geographers, among others. We all agreed in principle about the threats to rural forested communities in North America, and eagerly discussed similarities and differences among our regions. However, when it came down to specifying exactly what the defining characteristics of rural forested communities might be, and what data we would use to identify them spatially (what is rural? What is a forest? What is a community??), we were in trouble.

Figure 1: Locating the rural forested counties of the U.S. (Bell et al. 2019).

We argued that the word “community” means something specific in ecology, yet remains vague or contradictory across the social sciences. We argued that the Census counts record someone’s residence, not their place of work, and commuting relationships vary regionally and across the urban-rural continuum. How do we precisely map which forest is used by which people? How much vegetation cover should there be to define a forest, in such an ecologically diverse place as the continental U.S., even? There is no clear geographic definition of what constitutes a rural forested community. But we needed to operationalize data – census data on population, economic census data on employment and occupation, land-cover datasets for information on forest extent, etc.

People are mobile and drive for miles to harvest or hike in wooded areas. Trees are stationary, yet their benefits to people and animals extend beyond the boundaries of the forest. There will always be a spatial mismatch (Bell 2005) in assimilating data from ecological and social systems, and we were likely to underbound (leave out areas that fit our conceptual understanding of these places) or overbound (include areas that didn’t really fit with what we want to study) our identification of actual rural forested communities.

The more we discussed how we were going to measure this idea we had, this concept that we knew existed in the “real world,” the more we began to struggle. We began to brainstorm terms that might capture the idea. Of course, being scientists, we wanted clever acronyms for those terms.

The suggestion came up to identify a placeholder, such as a name or object that would be easy to remember, to communicate effectively until we figured out exactly what we wanted to call this phenomenon. Voices got louder. The tone got more heated. Scribbles were madly filling up the white board. We were at an impasse. I sat back, observing some of the chaos.

“George!”, I said, “Why don’t we just call it George!”

A dozen heads snapped around to look quizzically at me. I had just thought about the Abominable Snowman in Bugs Bunny. When Bugs misses that left turn at Albuquerque and ends up in the Himalayas (neocolonial problems with this representation aside), the Snowman picks him up as a pet, and says, “My own little bunny rabbit, I will hug him and squeeze him, and name him George.”

So we agreed to use the placeholder George, to stand in for this concept that we could all imagine but could not agree how to measure, so that we could move on to develop our larger conceptual framework, and all the factors we wanted to consider (Morzillo et al. 2015, van Berkel et al. 2018): roads, governing institutions, ecological conditions, political economy, etc. We got a lot of mileage out of simply invoking the name George, over and over and over.

Lesson 2: Know when to “lump” and when to “split”

Ultimately, we realized that our big group had substantive tensions in focus. The ecologists, broadly, were most interested in forest resources in situ, focusing more directly on the people, and the houses, that were in the midst of or on the edge of those forests. The social scientists on the other hand, were most interested in the function of the community rather than individual plots of land: how were local institutions navigating big structural economic changes, and how were community strategies for development differentially experienced by residents?

Eventually, we broke the puzzle into two pieces – understanding the extent, spatial patterns and regional variations across these forested regions (van Berkel et al. 2018), and hypothesizing how differing local characteristics correspond with trajectories of change (decline, tourism, new types of production) (Morzillo et al. 2015).

There is a literature about “lumpers vs. splitters” (Endersby 2009); i.e., whether scientists tend to be more comfortable with broad generalization, or whether more specificity, and more categories or exemplars, are necessary to capture finer-scale variation. I have been in several interdisciplinary teams in my 20-year career, and have experienced this phenomenon multiple times. What’s most interesting to me as a researcher and teacher is that no perfect theory and no perfect dataset can ever solve this conundrum. It is fundamentally a social one, that requires interpersonal communication and understanding. And, like all good inquiry, it depends on the research question.

Lesson 3: Specialize as needed

Ultimately, our SESYNC group, which was assembled from several existing projects, tag-teamed the two foci: alternatively, looking at settlements within forested pixels (van Berkel et al. 2018), versus forests within 100 miles of communities (Munroe 2019).

A somewhat smaller plucky band: the rural sociologist, the human dimensions expert, the two most open-minded economists I have ever known, and myself, have continued to forge ahead. This subset, when we received funding from the USDA National Institute of Food and Agriculture, continued to refine our definition of rural forested communities, a region we now refer to as Eunice.

Figure 2: The (smaller) interdisciplinary team in Logan, Ohio. Photo Credit: Kymber Anderson

What were the lessons of this experience? Well, anyone can claim to be a quarterback on Monday morning, so take these as intended. What I personally learned is the following:

  • Don’t shy away from tough conversations. It’s not impolite to disagree about concepts or data.
  • Focus on what you can agree on, and what you can’t.
  • Be willing to change, follow the inspiration of the moment.
  • Be generous ex post (you’ll note we were generous with coauthorship).

In the endnotes of our first published paper, we have an acknowledgement to “George.”

 

Acknowledgements

I’d like to thank my close group of collaborators, Kathleen Bell, Chris Colocousis, Mindy Crandall, Anita Morzillo and the rest of the SEYSNC team, past and present. All errors herein are my own.

Darla Munroe

Professor & Chair

Department of Geography

The Ohio State University

 

Links

http://www.sesync.org/

https://www.sesync.org/rural-forest-communities-tipping-point-trends-and-actionable-research-opportunities

https://portal.nifa.usda.gov/web/crisprojectpages/1009211-biodiversity-ecosystem-services-and-the-socioeconomic-sustainability-of-rural-forest-based-communities.html

https://en.wikipedia.org/wiki/Hugo_the_Abominable_Snowman

References

  • Bell, K. P. (2005). Spatial analysis and applied land use research. Land Use Problems and Conflicts, 118.
  • Bell, Kathleen P., Mindy Crandall, Darla K. Munroe, Anita Morzillo, & Chris Colocousis (2019). Rural forested landscapes, economic change, and rural development. 2019 North American Meetings of RSAI, Pittsburgh, PA. 15 November.
  • Endersby, J. (2009). Lumpers and splitters: Darwin, Hooker, and the search for order. science, 326(5959), 1496-1499. DOI: 10.1126/science.1165915
  • Fry, J. A., Xian, G., Jin, S. M., Dewitz, J. A., Homer, C. G., Yang, L. M., … & Wickham, J. D. (2011). Completion of the 2006 national land cover database for the conterminous United States. PE&RS, Photogrammetric Engineering & Remote Sensing, 77(9), 858-864.
  • Munroe, D. K., Crandall, M. S., Colocousis, C., Bell, K. P., & Morzillo, A. T. (2019). Reciprocal relationships between forest management and regional landscape structures: applying concepts from land system science to private forest management. Journal of Land Use Science, 14(2), 155-172. https://doi.org/10.1080/1747423X.2019.1607914
  • Morzillo, A. T., Colocousis, C. R., Munroe, D. K., Bell, K. P., Martinuzzi, S., Van Berkel, D. B., … & McGill, B. (2015). “Communities in the middle”: Interactions between drivers of change and place-based characteristics in rural forest-based communities. Journal of Rural Studies, 42, 79-90. https://doi.org/10.1016/j.jrurstud.2015.09.007
  • SEDAC, & US census Bureau (2000). Census block data on poverty, housing stock, education and key demographic. Retrieved from: http://sedac.ciesin.columbia.edu/.
  • Van Berkel, D. B., Rayfield, B., Martinuzzi, S., Lechowicz, M. J., White, E., Bell, K. P., … & Parmentier, B. (2018). Recognizing the ‘sparsely settled forest’: Multi-decade socioecological change dynamics and community exemplars. Landscape and Urban Planning, 170, 177-186. https://doi.org/10.1016/j.landurbplan.2017.10.009

The 2020 U.S. Census and Indigenous peoples

The 2020 Census is in full swing in the United States. By the end of the Census in December, virtually every American citizen will have been asked to provide information to the Census—whether it is via the traditional forms we receive in the mail, via telephone, or online. Americans are consistently reminded of the importance of the Census—besides providing a more accurate count of the population of the country, its states, and the many counties/parishes/boroughs, cities, towns, villages that comprise each state, it has economic and political ramifications. According to the U.S. Census Bureau, Federal funding is guided by population shifts, states can gain or lose Congressional representation based on their new populations, and local governmental units draw boundaries or allocate resources based on information gathered in the Census. If those reasons aren’t enough, we also are faced with the ‘threat’ of a Census enumerator coming to our front doors to collect the information, or in some cases, a $100 fine. Clearly, it is important for Americans to do the Census.

However, for one group of Americans, the Census both carries deeper historical and contemporary significance. For the over 570+ Federally recognized tribes (including Alaskan Native tribes) in the United States, information from the Census helps influence Federal funding for tribally-focused programs, as well as allowing tribes to make local planning decisions for tribal programs and services. However, Federal counting of Indigenous peoples in the United States has a very fraught history that is linked with colonialism and dispossession of tribal lands and political power. For example, tribal ‘rolls’ were routinely used from the late 19th century to count members of tribes and determine their blood quantum, deeming them worthy or unworthy of allotments and/or tribal citizenship. Federal policies such as relocation/termination and sending Indigenous children to boarding schools have created a legacy where many tribal members do not trust the Federal government or its initiatives, making it very difficult to secure Indigenous buy-in to the Census, as Kirsten Carlson writes.

Even when Indigenous people have participated in the Census, there has been notorious undercounting of Indigenous tribes and individuals; according to this report by the National Congress of American Indians, the percentage of Indigenous people that have been undercounting has ranged anywhere from 4.9% (in the 2010 Census) to 12.2% (in the 1990 Census). The same report echoes the relative mistrust in Indigenous communities as to the purposes and benefits of doing the Census. The rise of the COVID-19 pandemic in the United State also represents a barrier to participation, as does technological barriers that are often present on reservations (lack of Internet access, etc.) and the fact that the Census Form is not offered in tribal languages. Of course, there is also the fact that the Federal definition of who is an ‘American Indian’ or ‘Alaska Native’ does not always matchup with tribal or individual definitions of Indigeneity (see Liebler, 2018 for a more detailed explanation).

With clear political and economic ramifications at stake, and in an effort to counteract the problematic history of counting Indigenous people, the U.S. Census Bureau has undertaken a massive effort to attempt to solicit as much participation in the 2020 Census by Indigenous peoples in the United States as possible. One way that this has occurred is through an increase in the dissemination of information related to what the Census is, and what it means for Indigenous communities in the United States. A wide variety of press releases, handouts and multimedia have been made available for tribal governments and tribal citizens to learn more about the Census, including articles, brochures, podcasts, sample invitation letters, and even videos that explain more about the Census enumeration process. A press kit provides additional information, including a really great blog post from the Director of the U.S. Census Bureau, that talks specifically about the importance of the Census for Indigenous people, with a particular focus on Alaskan Natives.

However, the Census Bureau is not the only ones that are working hard to ensure an accurate count of Indigenous people in 2020. Indigenous people themselves have taken many steps in order to get the word out in their own communities to explain the importance of participating in the 2020 Census. Much of this work occurs at a national level, such as via the U.S. Indigenous Data Sovereignty Network, founded by Northern Cheyenne tribal member and all-around Indigenous badass Dr. Desi Rodriguez-Lonebear. But, there is also a lot of work that happens at a local level. Tribes such as the Pullayup Tribe in Washington, the Navajo Nation, and many others have not only built relationships with the U.S. Census Bureau, but they are also taking their own actions to help drive up participation. Tribal nations have sought to overcome mistrust regarding the Census is by involving Indigenous people in the collection process. My own tribe, the Leech Lake Band of Ojibwe sent out a call earlier this year for Census takers, for example:

Leech Lake Band of Ojibwe Posting

It is clear that tribal nations understand the importance of the Census to their communities, and to holding the Federal government accountable to its obligations to tribes as part of the nation-to-nation framework that characterizes the relationship between Indigenous nations and the United States. Through cooperation between tribes and the Census Bureau, as well as steps that tribes are taking themselves, the process of including Indigenous people in the Census will hopefully improve, allowing for the conditions necessary for Indigenous nations to receive the support and services they need.

Deondre Smiles (Ph.D., 2020, OSU Geography)

President’s Postdoctoral Scholar

Department of History

The Ohio State University

Census Data: A Personal Note on Some Challenges and Successes

The census data we use today is a symbol of American democracy. The U.S. Constitution states that “the actual enumeration shall be made … within every subsequent term of ten years, in such manner as they shall by Law direct” (Article 1, Section 2). After this historical point, the census has a brand new meaning beyond the mere means for the royalty or state to make their economic or political gains. Today, U.S. census data are commonly used for mapping and many other purposes. It is literally the textbook example of spatial data and applications in GIS and cartography education. Indeed, the U.S. census has empowered individuals and organizations around the world. A few simple clicks on an interactive map shown below, for example, will reveal some stunning pattern of spatial dynamics across America, even at a county level.

Map to explore census data of U.S. Counties

An interactive map to explore census data of U.S. counties.

However, as useful and powerful as the census data are, shortcomings and challenges are also noticeable. Let’s start from a spatial perspective and ask ourselves this question: are census data safe? The following map comes from the dark side of using census data. It was made by Nazi Germany circa 1940, before the U.S. formally entered the Second World War. This map details the first and second generation of middle and western Europe immigrants in the United States, based on the publicly available data from the 1930 U.S. Census. It also has a label at the top left corner that reads “For official use only!” Its cartographic achievement aside, this map was used by the Nazi propaganda machine to strategically spend their war money to persuade the public opinion in the U.S. to avoid being involved in the war raging in Europe. Many believed such a campaign was successful to some extent. It is safe to say that, ever since then, the use of the census data and maps in today’s affairs, from political campaigns to social media disinformation to foreign meddling of our elections, is everything but the lack of imagination.

“20th Century Through Maps” Courtesy of British Library (permission pending)

The arguably darkest moment of the U.S. census also came in the Second World War, when the census information used by the U.S. government directly led to the internment of Japanese Americans after the Pearl Harbor attack. So is it really provocative to ask will the census data, mapped or not, put us in danger? Will history repeat itself in the 21st century? Will another ethnic group become the victims? While the 2020 census eventually did not include citizenship questions, it should not be the time to celebrate. Instead, we should ask will such questions ever come back, and in what form? These issues may be beyond the scope of the census, but the census has been the vehicle that carries these issues.

Also from the spatial perspective, it is well known that census geographies are designed in a hierarchical fashion where the blocks are the smallest spatial units and from there we can aggregate to units such as block groups, tracts, and counties. Census tracts have been considered to be the relatively stable units for statistical analysis because by design they aim to have an ideal population of 4,000. But why should space be delineated in such a fixed and perhaps artificial way? What if we can re-arrange the blocks and come up with different kind of units that are compatible with the official tracts? This is a notoriously difficult task because there are an astronomical amount of ways to recombine the blocks. But if we test some algorithms on a manageable number of units, we can see how the world can be different. The two figures below show the result of such an exercise. It is clear that we can actually achieve a better set of spatial units where the population is more evenly distributed and more centered around the ideal size. Also, the new aggregated units show no significant spatial auto-correlation, which makes them more suitable for statistical analysis.

Visual representation of Population of the 284 census tracts in Franklin County, Ohio.

Population of the 284 census tracts in Franklin County, Ohio.

Visual representation of Population of the 284 new units that are aggregated using the 887 census block groups in Franklin County, Ohio.

Population of the 284 new units that are aggregated using the 887 census block groups in Franklin County, Ohio.

Issues related to spatial units are not new and have been around in statistics and geography for at least more than a half century. Computational advances have made it possible to explore new and different approaches to spatial organization. The question is: how can we embrace such a new way of thinking about these statistical units? Should we even go down this rabbit hole where things will become constantly changing.

We can certainly read the history of the use of census data through different lenses. But, however we read it, we will find both bright and dark sides that are full of conflicts, betrayal, conspiracy, struggle, and promises. The world envies the richness of the census data available in the United States that dates back to the beginning days. From this perspective, I personally do see more promises than anything else, as the new century should be the time for us, the research community as well as the general public, to re-imagine what the census data could be.

 

Ningchuan Xiao, Professor

Department of Geography

The Ohio State University