The Urbanization Perceptions Small Area Index: An Application of Machine Learning and Small Area Estimation to Household Survey Data
Urban and rural definitions are abundant in government, academic literature, and data-driven journalism. Equally abundant are debates about which factors should be used to define these terms. Absent from most discussion is evidence about how people perceive or describe their neighborhood. Moreover, as housing and demographic researchers have noted, the lack of an official definition of suburban obscures the fact that a majority of Americans live in a suburban setting. The Department of Housing and Urban Development asked 2017 American Housing Survey (AHS) respondents to describe their neighborhood as urban, suburban, or rural. We used the AHS "neighborhood description" data to create the Urbanization Perceptions Small Area Index (UPSAI). We applied machine learning techniques to the AHS neighborhood description question to build a model that predicts how out-of-sample households would describe their neighborhood (urban, suburban, or rural), given regional and neighborhood characteristics. We then applied the model to the American Community Survey aggregate tract-level regional and neighborhood measures, creating a predicted likelihood the average household in a tract would describe their neighborhood as urban, suburban, and rural. Our approach uses existing federal data to create an innovative new data product of substantial interest to researchers and policy makers.
FIRST AUTHOR
Emily Molfino, U.S. Census Bureau
SECOND AUTHOR
Shawn Bucholtz, U.S. Department of Housing and Urban Development
THIRD AUTHOR
Jed Kolko, Indeed
KEY WORDS
Urban, suburban; small area estimation; American Housing Survey; machine learning
FIRST AUTHOR
Emily Molfino, U.S. Census Bureau
SECOND AUTHOR
Shawn Bucholtz, U.S. Department of Housing and Urban Development
THIRD AUTHOR
Jed Kolko, Indeed
KEY WORDS
Urban, suburban; small area estimation; American Housing Survey; machine learning
Transit's Effects on Redlined Neighborhoods: Job Dynamics in Historically Disinvested Neighborhoods
2002-2017
2002-2017
We evaluate the recent effects of proximity to Fixed-Rail Transit (FRT) on economic development in redlined neighborhoods, before, during and after the Great Recession, 2002-2017. Discriminatory mortgage-lending practices in previous periods have led to disinvestment and intractable challenges in poor and minority urban neighborhoods. The opening of new transit stations has attracted unprecedented investment in these places. Theoretical conflicts over development have impeded a clear picture of the outcomes of transit expansion in disinvested neighborhoods. Results on the impacts of new investment have varied across metropolitan areas and by transit system modes (commuter rail, light rail, streetcar). In some cases, there has been an ongoing inability to attract needed reinvestment; in others, gentrification-driven displacement of poor residents has occurred. This paper analyzes shifts over time of jobs in redlined zones near light rail transit, using contingency tables and principle components to statistically flesh out the outcomes of transit proximity across the timeline before, during, and after the Great Recession in Dallas, Texas. We hypothesize that station-area outcomes vary by demographic segment of the population, and regional-scale economic strength and growth. Also, neighborhoods in the greatest decline will have attracted the lowest level of investment.
FIRST AUTHOR
Robert E. Hibberd, University of Arizona
SECOND AUTHOR
Arthur C. Nelson, University of Arizona
KEY WORDS
Redlining; Transit-Oriented Development; Principle Component Analysis; transportation planning; economic development
FIRST AUTHOR
Robert E. Hibberd, University of Arizona
SECOND AUTHOR
Arthur C. Nelson, University of Arizona
KEY WORDS
Redlining; Transit-Oriented Development; Principle Component Analysis; transportation planning; economic development
Understanding Gender, Income and Commuting in Casablanca City, Morocco
This paper presents the results of the study analyzing the travel patterns of Casablanca City residents (Morocco) with respect to gender and income level. Casablanca is the largest city in Morocco and it is considered as its economic hearth and one of the most dynamic cities in Africa. Presently characterized by a problematic urban sprawl as well as an under development public transport network, the city is knowing a rise of private vehicle use as the main travel mode. For this study, information from the Household Survey data was used to run statistical analysis allowing the comparison of the male and female core travel components and the analysis of the different influences of gender and income on travel behavior and how it varies across the Metropolitan area of Casablanca. The findings highlight gender disparities in matters of travel behavior that are accentuated by the geographical parameter of residential location.
FIRST AUTHOR
Zineb Chamseddine, Hassan II University of Casablanca
SECOND AUTHOR
Asmaa Ait Boubkr
KEY WORDS
Travel behavior; Commuting; Gender; Income
FIRST AUTHOR
Zineb Chamseddine, Hassan II University of Casablanca
SECOND AUTHOR
Asmaa Ait Boubkr
KEY WORDS
Travel behavior; Commuting; Gender; Income
UNDERSTANDING THE SPATIAL LOCATION STRATEGIES OF PAYDAY LOAN AGENCIES IN TORONTO
Pay day loan firms offer alternative financial services compared to traditional banks. While traditional banks are the more widespread financial service for which credit can be obtained (as they can issue credit cards, cashing cheques and providing loans), they are not the only option for people seeking credit, particular for those seeking short-term loans. In fact, many are "locked out" of this option for borrowing due to access and knowledge. Payday loan services have been critiqued for targeting at-risk segments of populations, as these short-term loans have high associated interest rates. There is, however, limited understanding of differences in the spatial and business strategies of these two groups of financial institutions. Through spatial analysis, this study examines the spatial location patterns of payday loan agencies in comparison to banks in the City of Toronto, Canada as well as the demographic composition of their customers. Location data is analyzed to compare local and global patterns across the city for both types of financial institutions while census data are used to see the characteristics of the populations they are locating near. This analysis shows that there are differences in spatial patterns and targeted customers when comparing payday loan firms and banks.
FIRST AUTHOR
Eric Lum, Ryerson University
SECOND AUTHOR
Evan Cleave, Ryerson University
KEY WORDS
Payday loans; banks; spatial analysis geodemographics
FIRST AUTHOR
Eric Lum, Ryerson University
SECOND AUTHOR
Evan Cleave, Ryerson University
KEY WORDS
Payday loans; banks; spatial analysis geodemographics
Understanding the Tribal Disenrollment Epidemic: The Unintended Consequences of the Indian Gaming Policy
Recently, over 80 Native American tribes have banned or disenrolled members of their tribes or denied citizenship to eligible individuals. This phenomenon has received media attention nationwide, and even the term the "disenrollment epidemic" was coined. Many speculate that at least some of it is driven by the greed associated with the multi-million dollar revenues of tribal casinos, which are sometimes distributed in per capita payments to all tribal members. Since a tribe's involvement in gaming might be endogenous, I employ an instrumental variable approach to test whether gaming has been driving disenrollments. In particular, I use machine learning to select an optimal subset of instruments for a Native American tribe operating a casino from the set of potential instruments all meeting the exclusion restriction and associated with the geographical characteristics of reservations, such as their proximity to an MSA, an interstate highway, or a border of a neighboring state with no brick and mortar casinos. I find that a tribe's involvement in gaming causes a large and statistically significant increase in the probability of a forced disenrollment episode but not of a banishment or citizenship denial episode. This paper contributes to the larger literature on club goods.
FIRST AUTHOR
Anna Malinovskaya, Cornell University
KEY WORDS
Social justice; machine learning; indigenous issues
FIRST AUTHOR
Anna Malinovskaya, Cornell University
KEY WORDS
Social justice; machine learning; indigenous issues
Understanding White Spaces in Our Architecture: The Racist Geography of Bakersfield's South High School
and its Plantation Neighborhood
and its Plantation Neighborhood
The killing of George Floyd, and events leading up have forced the nation to recognize Confederate memorials/monuments as symbols of hate intent on glorifying white supremacy and disenfranchise African Americans. Municipalities, corporations, US Military and the state of Mississippi have responded by removing confederate inspired memorials/monuments from their public and corporate spaces.
This urgency has however yet to reached the City of Bakersfield, Kern High School and Greenfield Elementary officials to act on addressing one of the highest geographic concentration of officially named confederate iconography in the United States in the nondescript Plantation neighborhood in South Bakersfield, Ca.
This session will examine the origins of this community, from the developers, to city public works staff that approved street name such as "Rebel, Plantation, Sumter, Pontiac, Merrimac, etc.". The role of school officials had in the founding of Plantation Elementary (1980), South High School (1957) and the selection process for school colors "Blue and Grey"; mascots "Johnny and Jodie Reba"; Dixie as its school song and use of the confederate flag by drill team and seal embossed on diplomas.
Finally, it will also attempt to identify "Other" similar communities in the United States.
FIRST AUTHOR
Jesus Garcia, La Cresta Demographics
SECOND AUTHOR
Danny Morrison, Danny Morrison Media
KEY WORDS
Confederate Monuments; Public Works; public schools,
This urgency has however yet to reached the City of Bakersfield, Kern High School and Greenfield Elementary officials to act on addressing one of the highest geographic concentration of officially named confederate iconography in the United States in the nondescript Plantation neighborhood in South Bakersfield, Ca.
This session will examine the origins of this community, from the developers, to city public works staff that approved street name such as "Rebel, Plantation, Sumter, Pontiac, Merrimac, etc.". The role of school officials had in the founding of Plantation Elementary (1980), South High School (1957) and the selection process for school colors "Blue and Grey"; mascots "Johnny and Jodie Reba"; Dixie as its school song and use of the confederate flag by drill team and seal embossed on diplomas.
Finally, it will also attempt to identify "Other" similar communities in the United States.
FIRST AUTHOR
Jesus Garcia, La Cresta Demographics
SECOND AUTHOR
Danny Morrison, Danny Morrison Media
KEY WORDS
Confederate Monuments; Public Works; public schools,
Unhealthy After School Snacks: Socioeconomic Disparities of Food Environments around Public and Private Schools in the United States
This study aims to compare the Food environments (here after FE) around public and private schools in the United States and explore if socioeconomic factors on the school and county levels affect the FEs around schools. School data was obtained from elementaryschools.org, including 75,055 public and 20,427 private schools. Food store data was obtained from the U.S Department of Agriculture website including convenience stores (65,044), small food stores (44,383) and supermarkets/grocery stores (96,652). LISA maps and t test were applied to compare the FEs around public and private schools. Regression models were run to examine the influences of the socioeconomic factors on school FEs. FE around private schools was of lower quality compared to that of public schools (p<0.01). Both school- and county-level socio-demographic factors had significant influences on school FEs. Schools with higher percentages of minority and low-income students tend to have worst FEs (p<0.001). Schools located in counties with high racial segregation, minority percentage, unemployment, poverty rate and low educational attainment tend to have unhealthy FEs as well (p<0.001). Policy makers should pay attention to FEs around both private and public schools, particularly those schools with high percentages of low SES students and located in disadvantaged counties.
FIRST AUTHOR
Andrea Smith, University of Central Florida
SECOND AUTHOR
Ting Du, University of Central Florida
THIRD AUTHOR
Yingru Lu, University of Central Florida
KEY WORDS
Food environment; public and private schools; socioeconomic disparities
FIRST AUTHOR
Andrea Smith, University of Central Florida
SECOND AUTHOR
Ting Du, University of Central Florida
THIRD AUTHOR
Yingru Lu, University of Central Florida
KEY WORDS
Food environment; public and private schools; socioeconomic disparities
Unmasking Differences: How using the correct unit of analysis in geospatial drinking water research has
the potential to reveal community-level differences
the potential to reveal community-level differences
Due to data limitations, US drinking water analysis is often conducted at the county-level. The lack of readily accessible community water system (CWS) estimated service area boundary (ESAB) data has limited community-level water justice analysis around drinking water quality and affordability from being more accurately measured; thereby limiting evidence to support policy recommendations. By using county-level analysis, nuances caused by social, political, economic, and geological differences are masked. To address this limitation, the Drinking Water Justice Lab at Vanderbilt University has created the most comprehensive national geospatial database of CWS ESABs in the US. The database consists of 23 states' geospatial data of ESABs; this number represents the publicly available datasets. This presentation will focus on the procedures implemented to create a standardized process and output across these data. Several challenges emerged, such as the inconsistency and incompatibility of state data and the time and effort needed to mitigate these discrepancies to create a standardized national database. We discuss the need for the accurate scale of analysis within drinking water research, the challenges around creating a national database of CWS ESABs, recommendations to improve the database construction and quality, and the potential impact to address drinking water injustice.
FIRST AUTHOR
Yolanda McDonald, Ph.D., Vanderbilt University
SECOND AUTHOR
Kayla Anderson, Vanderbilt University
KEY WORDS
Scale; geospatial database; community water systems; service areas
FIRST AUTHOR
Yolanda McDonald, Ph.D., Vanderbilt University
SECOND AUTHOR
Kayla Anderson, Vanderbilt University
KEY WORDS
Scale; geospatial database; community water systems; service areas
Using climate modeling and interdisciplinary theory to analyze climate justice impacts of the
Paris Agreement
Paris Agreement
The science linking anthropogenic greenhouse gas emissions with our changing climate, and the resulting impacts, has been well established for decades. During that time one of the focal points of international negotiations was to establish a common target for action to address climate change. These negotiations culminated in the Paris Agreement at COP21 in 2015 which seeks to limit the global mean surface temperature (GMST) rise to well below 2C above pre-industrial, and to pursue efforts to limit it to 1.5C. This research seeks to assess the climate justice implications of using global mean surface temperature as a metric for climate action by combining data from ice sheet models and fully coupled global climate model simulations in conjunction with a literature review spanning fields including international relations, political economy, critical geography, and history. Considering the political and scientific history of the development of the temperature target alongside global impacts of climate change we gain a new understanding of spatial, temporal, and procedural aspects of climate justice.
FIRST AUTHOR
Shania Sadai, University of Massachusetts-Amherst
KEY WORDS
Climate change; climate modeling; climate justice; social justice
FIRST AUTHOR
Shania Sadai, University of Massachusetts-Amherst
KEY WORDS
Climate change; climate modeling; climate justice; social justice
Well, that's water: Interactive visualization of groundwater data
Groundwater data is a key metric for understanding changes in local aquifers in response to external stresses such as precipitation, drought, and human activities. These responses could have significant impacts on the economy and environment overtime. The Department of Geology & Geography at UNC Pembroke has been conducting groundwater monitoring in Robeson County, NC since the winter of 2017. This data includes continuous water-level measurements from thirteen wells across the county monitored by students involved in the project and water-level measurements at fourteen wells on the UNCP campus. While the project has previously made these data available via a webmap, the growth of digital dashboards has provided a new way to share not only the raw data, but to share the data through interactive graphs and charts in addition to a webmap interface. This paper will discuss the planning and initial implementation of a dashboard for this on-going project which can inform direct stakeholders and the general public using more immersive tools.
FIRST AUTHOR
Jesse Rouse, UNC Pembroke
SECOND AUTHOR
Madan Maharjan, UNC Pembroke
KEY WORDS
Groundwater; dashboard
FIRST AUTHOR
Jesse Rouse, UNC Pembroke
SECOND AUTHOR
Madan Maharjan, UNC Pembroke
KEY WORDS
Groundwater; dashboard
Why do Czech commuters choose train for the transportation?
The mobility of population in the Czech Republic is increasing over the last years. It is supported by growing Czech economy as well as by development and improvement of transportation networks. The Czech commuters broadly prefer individual car transport over public transport modes. To explore the factors that influence the preference of train transportation, a survey on the trains between Prague and Usti nad Labem was conducted. The survey took place in time between October 2018 and September 2019 and almost 300 respondents were questioned. Even though, all the respondents used the train in the time when they were questioned almost one third of them prefer to use car for commuting to work. This situation enables us to compare the factors that are important for decision about preferred transportation mode for train and car users. The two cities Prague and Usti nad Labem should be one of the first in the Czech Republic connected with high speed train. With respect to this intention the respondents were also asked if the reduction of travel time could encourage them to travel by train more often. Surprisingly, the differences in evaluation of importance of selected factors between car and train users are rather small. Factors such as prestige, travel time, time reliability or flexibility were slightly more important for car users. Commuters by train emphasized number of connections, prize, possibility to work on board, safety and habit as crucial factors for the selection of transportation mode. Reduction of travel time between Czech capital and Usti nad Labem was perceived by 60 % of respondents as motivating for more frequent commuting to the other city. The interviewed differ in the foreseen purposes of their journey (work, school, services, culture or sports etc.). The willingness for more frequent travelling was more distinctive among the train users than among car users. Most of the respondents who would not travel more often with the high speed train stated that they have everything they needed in their home town. Nevertheless, the results showed that people are willing to use train more often if it is fast, comfortable and affordable.
FIRST AUTHOR
Kristyna Rybova, Jan Evangelista Purkyne University in Usti nad Labem
KEY WORDS
Mobility; transportation mode; train; car; Czech Republic
FIRST AUTHOR
Kristyna Rybova, Jan Evangelista Purkyne University in Usti nad Labem
KEY WORDS
Mobility; transportation mode; train; car; Czech Republic