Figure - available from: Population Research and Policy Review
This content is subject to copyright. Terms and conditions apply.
Spatial distribution of population decline/growth. a Tiny towns in counties not-adjacent to metro areas. b Tiny towns in metro-adjacent counties. Background Layers: Esri, HERE, Garmin, c OpenStreetMap contributors, and the GIS user community, IPUMS NHGIS, University of Minnesota, www.nhgis.org
Source publication
The county scale has thus far dominated rural demographic research—this descriptive profile of small town America is unique with its place-based lens. Another important extension is the nationwide application of the Community Capitals Framework which builds on the body of research examining capitals within case studies focused on one or more commun...
Similar publications
This publication, in two parts, provides an overview of the methodology and results from the Mobility Survey undertaken for the Population Mobility and Labour Markets Project, Cooperative Research Centre for Remote Economic Participation. The survey investigated temporary mobility patterns of Aboriginal and Torres Strait Islander People living in 2...
This publication, in two parts, provides an overview of the methodology and results from the Mobility Survey undertaken for the Population Mobility and Labour Markets Project, Cooperative Research Centre for Remote Economic Participation. The survey investigated temporary mobility patterns of Aboriginal and Torres Strait Islander People living in 2...
Citations
... In both urban and rural intergenerational mobility research, there is a tendency to take a cross-sectional perspective on locational data, rather than considering the dynamic nature of neighbourhoods, communities and regions (for exceptions, see: Chetty et al., 2017;Connor & Storper, 2020). Relying solely on cross-sectional analyses can lead to bias by overemphasising the significance of a place's characteristics at a specific moment while neglecting ongoing processes of change such as rising poverty, depopulation, or deindustrialisation. 1 Additionally, our focus on rural places departs from conventional rural demographic analysis, which often prioritises counties as the dominant unit of analysis (Hunter et al., 2020). While there are, of course, challenges irrespective of whether we use counties or places, we contend that dynamic and finer-scale analyses have the potential to enrich our understanding of the process of rural community change. ...
... First, we apply these methods from GIScience for the first time to places in rural America. Our dynamic approach to rural places could prove to be particularly valuable given the emphasis in rural demography on recent patterns of change at the county-scale (Hunter et al., 2020;Lichter & Brown, 2011;Lichter & Johnson, 2021;Slack & Jensen, 2020;Weber et al., 2018). Second, the current literature has largely relied on these methods as tools of description and has only begun to leverage these approaches toward inference (Connor, Berg, et al., 2023;Houlden et al., 2022). ...
... We rely on a longitudinal data set of all places in the lower 48 states, observed from 1980 to 2018 (Hunter et al., 2020). This data set includes place-level attributes from a combination of the decennial census and the 5-year estimates of the American Community Survey (ACS) over five time periods: 1980, 1990, 2000, 2010 and 2014-2018. ...
Rural America is often depicted as a distressed and left-behind place, with limited opportunities for the children growing up there. This paper addresses this topic by examining the dynamics of rural places over the past four decades and how these changes impact the economic mobility of children raised in poor rural households. Employing a place-based framework, we utilise sequence analysis to identify dominant trajectories of change for more than 8000 rural communities. Our analysis reveals highly diverse community trajectories that connect deindustrialisation and racial inequality to elevated and rising poverty rates in certain places, while also documenting more favourable poverty trends elsewhere. These diverging local outcomes shed new light on the conflicting narratives surrounding rural America. We then demonstrate that, among children from poorer households, exposure to community poverty is predictive of adult economic mobility, patterns which are partly mediated by family stability and child poverty. Our finding that poor children face additional disadvantages when they also grow up in poor places suggests a potential role for place-based policies and redistribution to help ameliorate these disparities.
... The seven CCs were used as a central theme to frame the discussion and probe participants' experiences during the Great Recession. The CCF offers an approach for analysing the effects of economic development on various socio-economic outcomes, including institutions (Hunter et al., 2020). Anecdotes about individual perspectives were discussed in the context of the overarching economic recessionary situation. ...
... We study rural places by augmenting an earlier constructed longitudinal dataset that covers all places in the lower 48 states, observed from 1980 to 2018 (Hunter et al., 2020). This dataset includes place-level attributes from a combination of the decennial census and the five-year estimates of the American Community Survey over five time periods: 1980, 1990, 2000, 2010 and 2014-2018. ...
... RUC codes 0-3 are designated as metropolitan, and codes 4-9 are nonmetropolitan. Codes 4, 5 and 6 may be considered as somewhat transitional categories (Hunter et al., 2020). 5 Table 1 also demonstrates the value of the PLURAL index in distinguishing rural from non-rural places in the middling RUC categories. ...
Children born into poverty in rural America achieve higher average income levels as adults than their urban peers. As economic opportunity tends to be more abundant in cities, this "rural advantage" in income mobility seems paradoxical. This article resolves this puzzle by applying multilevel analysis to new spatial measures of rurality and place-level data on intergenerational income mobility. We show that the high level of rural income mobility is principally driven by boys of rural-origin, who are more likely than their urban peers to grow up in communities with a predominance of two-parent households. The rural advantage is most pronounced among Whites and Hispanics, as well as those who were raised in the middle of the country. However, these dynamics are more nuanced for girls. In fact, girls from lower-income rural households exhibit a disadvantage in their personal income attainment, partly due to the persistence of traditional gender norms. These findings underscore the importance of communities with strong household and community supports in facilitating later-life income mobility, particularly for boys. They also challenge the emerging consensus that attributes the rural income mobility advantage to migration from poorer rural areas to wealthier towns and cities.
... The share of the US population living outside of urban areas fell from roughly 60 percent in 1900 to less than 20 percent today (Ratcliffe, 2015), and many communities that were once rural were absorbed into cities through urban expansion. Data constraints have, however, limited our understanding of how this process has unfolded at fine spatial scales and also what is known about the current conditions of rural communities, particularly those with smaller populations (Hunter et al., 2020). ...
Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural–urban continuum. Most existing classifications are, however, only available at relatively aggregated spatial scales, such as at the county scale in the United States. The absence of rurality or urbanness measures at fine spatial resolution poses significant problems when the process of interest is highly localized, as with the incorporation of rural towns and villages into encroaching metropolitan areas. Moreover, existing rural–urban classifications are often inconsistent over time, or require complex, multi-source input data (e.g., remote sensing observations or road network data), thus, impeding the longitudinal analysis of rural–urban dynamics. In order to address this gap, we compare existing rural–urban classifications in the US, and we develop a set of distance- and spatial-network-based methods for consistently estimating the remoteness and rurality of places at fine spatial resolution, over long periods of time, aiming to provide and evaluate temporally consistent rural–urban classifications at fine spatial granularity, but scalable to arbitrary, coarser spatial units. We demonstrate the utility of our approach by constructing indices of urbanness for over 28,000 places in the United States from 1930 to 2018 and further test the plausibility of our results against a variety of evaluation datasets. We call these indices the place-level urban–rural indices (PLURAL) and make the resulting code and datasets publicly available so that other researchers can conduct long-term, fine--grained analyses of urban and rural change. In addition, due to the simplistic nature of the input data, these methods can be generalized to other time periods or regions of the world, particularly to data-scarce environments.
... Our longitudinal database of places is constructed using place-level census data drawn from the National Historical Geographic Information System (NHGIS) and the American Community Survey. The rural components of this dataset were prepared in earlier work (Connor et al., 2022;Hunter et al., 2020;Uhl et al., 2023), which has set the stage for our integrated analysis of urban and rural places. This dataset contains information across a range of place-level demographic and socioeconomic variables in 1980, 1990, 2000, 2010, and 2018 for over 20,000 places in the United States. ...
... Places have recently re-emerged as an insightful scale of analysis. This is because, as compared with other common units of analysis like counties or census tracts, places better cohere with the scales of rural and urban contexts around which individuals immediately live their lives (Hunter et al., 2020). Moreover, in a recent study of rural places, Connor et al. (2022) document that a large share of the variation in intergenerational mobility is between places within the same county. ...
We document that children growing up in places left behind by today’s economy experience lower levels of social mobility as adults. Using a longitudinal database that tracks over 20,000 places in the United States from 1980 to 2018, we identify two kinds of left behind places: the ‘long-term left behind’ that have struggled over long periods of history; and ‘recently left-behind’ places where conditions have deteriorated. Compared to children of similar baseline household income levels, we find that exposure to left behind places is associated with a 4-percentile reduction in adult income rank. Children fare considerably better when exposed to places where conditions are improving. These outcomes vary across prominent social and spatial categories, and are compounded when nearby places are also experiencing hardship. Based on these findings, we argue that left behind places are having “scarring effects” on children that could manifest long into the future, exacerbating the intergenerational challenges faced by low-income households and communities. Improvements in local economic conditions and outmigration to more prosperous places are, therefore, unlikely to be full remedies for the problems created by left behind places.
... STEM related skills currently account for upwards of 69% of U.S. GDP (AAAS, 2020), and jobs in STEM fields are estimated to account for 37% of the workforce over the next decade (Lund et al., 2019). Despite evidenced challenges compared to non-rural areas (Bhaduri et al., 2022;Hunter et al., 2020), rural communities are in a unique position to help address these recent national demands for renewed STEM emphasis in schools (Saw & Agger, 2021). This research adds to recent efforts that focus on providing more quality STEM learning experiences to rural students to increase their interests and aspirations for increasingly important STEM careers. ...
... Unique challenges impacting rural communities include lower average socioeconomic metrics (Darrah et al. 2022), less money and resources (Hunter et al., 2020), more pronounced teacher shortages in STEM areas (Biddle & Azano, 2016;Dee & Goldhaber, 2017), and limited access to outside support (Player, 2015). Rural students experience lower average rates of college enrollment and graduation (Wells et al., 2019) and fewer job opportunities (Saw & Agger, 2021). ...
... Given these pressures for STEM teachers, which is likely even more pronounced for teachers in rural schools (Hunter et al., 2020), research has called for greater exploration of nuances that help educators effectively utilize PD (Banilower et al., 2018;Desimone & Garet, 2015). Recent metaanalysis of STEM PD efforts found that the most effective PD for improving student learning focused on providing new instructional materials, improving pedagogical practices related to student learning, or extending PD efforts to include troubleshooting sessions, larger learning community collaborations, and extra learning opportunities -like a summer workshop (Hill et al., 2020). ...
Despite evidenced challenges compared to non-rural areas,
rural communities are in a unique position to help address
recent national demands for renewed STEM emphasis in
schools (Saw & Agger, 2021). This study utilizes interviews
from five rural educators who participated in a three-week
STEM learning camp to discuss: 1) how teachers perceive the
effectiveness of STEM learning opportunities at increasing
student aspirations in STEM fields, and 2) what support and
resources teachers need to provide more quality STEM learning
opportunities. Learning experiences focused on aerospace engineering, artificial intelligence, and computer science.
Camp participants included 310 students, 40 teachers, 33
schools and 27 school districts across one midwestern state.
Findings suggest teachers perceive that quality STEM learning
opportunities increase many students’ self-efficacy using
STEM technologies and aspiration for future STEM careers.
Perceptions indicated rural teachers demand more effective
PD that emphasizes hands-on experiences, troubleshooting,
student-friendly vocabulary, and pedagogy. Teachers advocated
for more hands-on and peer-to-peer learning opportunities
while avoiding longer lectures and technological issues
to better engage students. Lastly, teachers perceived that outside
funding, resources, and support are the only realistic way
rural teachers can provide more quality STEM learning experiences
to students in rural communities.
Keywords: Rural education, rural teachers, STEM careers,
STEM learning, Research Practice Partnership (RPP), professional
development (PD)
... Our analysis relies on a newly constructed database that tracks the economic and demographic profiles of roughly 8,500 places from 1980 to 2018. This community-centered strategy is an advance in the existing literature, which usually characterizes rural communities in coarse terms, at the scale of counties (Hunter et al., 2020). We rely on spatial sequencing methods (e.g., Delmelle, 2016Delmelle, , 2017 to identify the dominant economic and demographic trajectories exhibited by communities, and then incorporate these trajectories within a multilevel model to assess how local change has impacted later-life outcomes for rural children. ...
... In the urban literature, the interest in how children acquire the skills, orientations and resources that facilitate upward mobility has lead researchers to focus on the contexts most relevant to personal development, usually neighborhoods (Loury, 2019;Sampson, 2019). While the scale at which rural children interact and live their lives may be best characterized by small towns or villages (Fuguitt, 1971;Hunter et al., 2020), almost all recent work has focused on coarser county divisions. Secondly, existing work usually focuses on the attributes of communities at on one point in time rather than characterizing places longitudinally. ...
... While there are roughly 3,000 counties in the United States, there are more than 20,000 places. Due to their finer granularity, places are easily mischaracterized when represented by the average attributes of coarser counties (Hunter et al., 2020). ...
Rural America is often portrayed as a distressed and left-behind place, where the outlook for rural children is stagnant. This view of rural hardship is supported by the fact that since 1980, almost one in three rural communities have seen increases in poverty of 50 percent or more. But are such worsening conditions a typical feature of rural communities? And what do these dynamics mean for the life chances of children? We address these questions through a framework that uses sequence analysis and multilevel modelling to determine how community changes are shaping the life chances of rural children. By revealing a series of highly distinctive community trajectories linking deindustrialization and long-term racial inequality to poverty, we confirm that the fortunes of rural America are far from monolithic. We then show particularly harmful effects of chronic or worsening community poverty on the life chances of rural children. These effects are evident for children from white and non-white households, and even among those who moved away from their home areas. We conclude that rural economic hardship is leaving a lasting mark on families and further fine-scale analysis is needed to understand the contribution of community change to social and spatial inequality.
We document that children growing up in places left behind by today’s economy experience lower levels of social mobility as adults. Using a longitudinal database that tracks over 20,000 places in the USA from 1980 to 2018, we identify two kinds of left behind places: the ‘long-term left behind’ that have struggled over long periods of history; and ‘recently left-behind’ places where conditions have deteriorated. Compared to children of similar baseline household income levels, we find that exposure to left behind places is associated with a 4-percentile reduction in adult income rank. Children fare considerably better when exposed to places where conditions are improving. These outcomes vary across prominent social and spatial categories and are compounded when nearby places are also experiencing hardship. Based on these findings, we argue that left behind places are having ‘scarring effects’ on children that could manifest long into the future, exacerbating the intergenerational challenges faced by low-income households and communities. Improvements in local economic conditions and outmigration to more prosperous places are, therefore, unlikely to be full remedies for the problems created by left behind places.
Using the nationally representative High School Longitudinal Study of 2009 (HSLS:09), this study documents that rural and small-town students were significantly less likely to enroll in postsecondary STEM (science, technology, engineering, and mathematics) degree programs, compared with their suburban peers. This study also shows that schools attended by rural and small-town students offered limited access to advanced coursework and extracurricular programs in STEM and had lower STEM teaching capacity. Those opportunities to learn in STEM were linked to the widening geographic gaps in STEM academic preparation. Overall, our findings suggest that during high school rural and small-town students shifted away from STEM fields and that geographic disparities in postsecondary STEM participation were largely explained by students’ demographics and precollege STEM career aspirations and academic preparation.
