Bridging the Gap: Mapping U.S County-Level Economic Disadvantage for Targeted Support in Agricultural Education

Authors

DOI:

https://doi.org/10.5032/jae.v67i1.3240

Keywords:

Economic disadvantage, Spatial inequality, Educational disparity, School-based agricultural education

Abstract

Economic factors can greatly impact student learning and achievement outcomes. Determining what students are considered to be “economically disadvantaged” is commonly based on their free and/or reduced lunch status, which neglects other economically related factors. Within the agricultural education profession, limited research exists on Economically Disadvantaged (ED) youth, possibly due to the lack of knowledge and resources available to accurately identify ED youth nationally. This study was designed to develop a spatial scale to identify and map financial hardship across all counties in the 50 U.S. states. Five economic-related data sources were used to determine the ED counties in each state by providing each county with a financial hardship level. Counties placed at levels 4 and 5 were deemed ED. The results included a level distribution overview, a list of ED counties, a list of ED counties with no SBAE program, a percentage of ED population, and an ED map. These results serve as a resource for identifying counties within the U.S. where future research and resources within the agriculture education profession can be channeled to provide more opportunities and support for SBAE programs serving ED youth.

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References

CFR § 124.104. (2023). https://www.govinfo.gov/content/pkg/CFR-2024-title13-vol1/pdf/CFR-2024-title13-vol1-sec124-104.pdf

Anjum, S. (2021). Impact of extracurricular activities on academic performance of students at secondary level. International Journal of Applied Guidance and Counseling, 2(2), 7–14. https://doi.org/10.26486/ijagc.v2i2.1869 DOI: https://doi.org/10.26486/ijagc.v2i2.1869

Ayllón, S., & Fusco, A. (2017). Are income poverty and perceptions of financial difficulties dynamically interrelated? Journal of Economic Psychology, 61, 103-114. http://dx.doi.org/10.2139/ssrn.2791405 DOI: https://doi.org/10.1016/j.joep.2017.03.008

Benson, C., Bishaw, A., & Glassman, B. (2023). Persistent Poverty in Counties and Census Tracts. United States Census Bureau. https://www.census.gov/content/dam/Census/library/publications/2023/acs/acs-51%20persistent%20poverty.pdf

Berman, F., Rutenbar, R., Hailpern, B., Christensen, H., Davidson, S., Estrin, D., Franklin, M., Martonosi, M., Raghavan, P., Stodden, V., & Szalay, A. S. (2018). Realizing the potential of data science. Communications of the ACM, 61(4), 67–72. https://doi.org/10.1145/3188721 DOI: https://doi.org/10.1145/3188721

Centers for Disease Control and Prevention. (2023, September 1). Socioeconomic factors. Division for Heart Disease and Stroke Prevention. https://www.cdc.gov/dhdsp/health_equity/socioeconomic.htm#print

Center on Budget and Policy Priorities. (2022, June 9). The Supplemental Nutrition Assistance Program (SNAP). https://www.cbpp.org/sites/default/files/policybasics-SNAP-6-9-22.pdf

Diamond, J. M., & Ordunio, D. (1999). Guns, germs, and steel (Vol. 521). New York: Books on Tape.

Dobis, E.A., Cromartie, J., Williams, R., & Reed, K. (2023). Characterizing rugged terrain in the United States (Report No. ERR-322). U.S. Department of Agriculture, Economic Research Service. https://doi.org/10.32747/2023.8134137.ers DOI: https://doi.org/10.32747/2023.8134137.ers

Dolean, D., Melby-Lervåg, M., Tincas, I., Damsa, C., & Lervåg, A. (2019). Achievement gap: Socioeconomic status affects reading development beyond language and cognition in children facing poverty. Learning and Instruction, 63, 101218. https://doi.org/10.1016/j.learninstruc.2019.101218 DOI: https://doi.org/10.1016/j.learninstruc.2019.101218

Fayet, Y., Praud, D., Fervers, B., Ray-Coquard, I., Blay, J.-Y., Ducimetiere, F., Fagherazzi, G., & Faure, E. (2020). Beyond the map: Evidencing the spatial dimension of health inequalities. International Journal of Health Geographics, 19(1), 46. https://doi.org/10.1186/s12942-020-00242-0 DOI: https://doi.org/10.1186/s12942-020-00242-0

Hanushek, E. A., Peterson, P. E., Talpey, L., & Woessmann, L. (2019). The unwavering SES achievement gap: Trends in U.S. student performance. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3357905 DOI: https://doi.org/10.2139/ssrn.3357905

Heath, R. D., Anderson, C., Turner, A. C., & Payne, C. M. (2022). Extracurricular activities and disadvantaged youth: A complicated—but promising—story. Urban Education, 57(8), 1415–1449. https://doi.org/10.1177/0042085918805797 DOI: https://doi.org/10.1177/0042085918805797

Jones, R., Seidelin, C. F., Neang, A. B., & Lee, C. P. (2023). Lessons learned from a comparative study of long-term action research with community design of infrastructural systems. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1), 1-35. https://doi.org/10.1145/3579502 DOI: https://doi.org/10.1145/3579502

Keller, S. A., Shipp, S. S., Schroeder, A. D., & Korkmaz, G. (2020). Doing data science: A framework and case study. Harvard Data Science Review, 2(1). https://doi.org/10.1162/99608f92.2d83f7f5 DOI: https://doi.org/10.1162/99608f92.2d83f7f5

Kentucky Department of Education. (n.d.). Glossary. Kentucky Department of Education School Report Card. Retrieved September 9, 2024, from https://www.kyschoolreportcard.com/datasets?year=2023

Lata, L. N. (2021). Negotiating gatekeepers and positionality in building trust for accessing the urban poor in the Global South. Qualitative Research Journal, 21(1), 76-86. http://dx.doi.org/10.1108/QRJ-03-2020-0017 DOI: https://doi.org/10.1108/QRJ-03-2020-0017

Li, C., Yin, X., & Jiang, S. (2020). Effects of multidimensional child poverty on children’s mental health in Mainland China. Journal of Health Psychology, 25(3), 400–415. https://doi.org/10.1177/1359105317718379 DOI: https://doi.org/10.1177/1359105317718379

Lister, R. (2021). Poverty. John Wiley & Sons.

Lobao, L. M., & Hooks, G. (2007). Advancing the sociology of spatial inequality: Spaces, places, and the subnational scale. In L. M. Lobao, G. Hooks, & A. R. Tickamyer (Eds.), The sociology of spatial inequality. State University of New York Press. https://doi.org/10.2307/jj.18253114

Lobao, L. M., Hooks, G., & Tickamyer, A. R. (Eds.). (2007a). Introduction: Advancing the sociology of spatial inequality. In The sociology of spatial inequality. State University of New York Press.

Lobao, L. M., Hooks, G., & Tickamyer, A. R. (Eds.). (2007b). The sociology of spatial inequality. State University of New York Press. DOI: https://doi.org/10.1353/book5206

Martin, M. J., & Henry, A. (2012). Building rural communities through school-based agriculture programs. Journal of Agricultural Education, 53(2), 110–123. https://doi.org/10.5032/jae.2012.02110 DOI: https://doi.org/10.5032/jae.2012.02110

McGee, G. W. (2004). Closing the achievement gap: Lessons from Illinois’ golden spike high-poverty high-performing schools. Journal of Education for Students Placed at Risk, 9(2), 97–125. https://doi.org/10.4324/9781315046099-2 DOI: https://doi.org/10.1207/s15327671espr0902_2

National FFA Organization. (2024). Chapter Locator. https://profile.ffa.org/Pages/Search/ChapterStateProfileSearch.aspx

OECD. (2016). How school characteristics are related to low performance. In Low-performing students: Why they fall behind and how to help them succeed (pp. 135–169). OECD Publishing. https://www.oecd-ilibrary.org/docserver/9789264250246-7-en.pdf?expires=1733845946&id=id&accname=guest&checksum=51B51676C100E5387CBCDD88AF9374E9

Ohio Department of Education. (2021). Economically disadvantaged students: A review of definitions and methods across states. Ohio Department of Education. https://www.lsc.ohio.gov/assets/organizations/legislative-servicecommission/monthly-agency-reports/agency-reports/files/mar-138-economicallydisadvantaged-students-2020.pdf

Owens, A., & Candipan, J. (2019). Social and spatial inequalities of educational opportunity: A portrait of schools serving high-and low-income neighborhoods in US metropolitan areas. Urban Studies, 56(15), 3178-3197. https://doi.org/10.1177/0042098018815049 DOI: https://doi.org/10.1177/0042098018815049

Piachaud, D. (1987). Problems in the definition and measurement of poverty. Journal of Social Policy, 16(2), 147-164. https://doi.org/10.1017/S0047279400020353 DOI: https://doi.org/10.1017/S0047279400020353

Ratcliffe, M., Burd, C., Holder, K., & Fields, A. (2016). Defining rural at the U.S. Census Bureau (ACSGEO-1). U.S. Census Bureau. Washington, DC. https://www.census.gov/content/dam/Census/library/publications/2016/acs/acsgeo-1.pdf

Rothstein, R. (2013). Why children from lower socioeconomic classes, on average, have lower academic achievement than middle-class children. In P. L. Carter & K. G. Welner (Eds.), Closing the opportunity gap: What America must do to give every child an even chance (pp. 61–76). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199982981.003.0005 DOI: https://doi.org/10.1093/acprof:oso/9780199982981.003.0005

Shrider, E. A., & Creamer, J. (2023). Poverty in the United States: 2022. https://www.census.gov/content/dam/Census/library/publications/2023/demo/p60-280.pdf

Satterthwaite, D., & Tacoli, C. (2014). Seeking an understanding of poverty that recognizes rural–urban differences and rural–urban linkages. In Urban livelihoods (pp. 52-70). Routledge.

Staehr, R., Conner, N., Reiling, B., Ruth, T., & Goldfuss, J. (2022). Perceived readiness of first year agriculture teachers to teach low socioeconomic students. Journal of Southern Agricultural Education Research, 73(1), 228–248.

Stearns, E., & Glennie, E. J. (2010). Opportunities to participate: Extracurricular activities’ distribution across and academic correlates in high schools. Social Science Research, 39(2), 296–309. https://doi.org/10.1016/j.ssresearch.2009.08.001 DOI: https://doi.org/10.1016/j.ssresearch.2009.08.001

Texas Education Agency. (2022). 2021–22 School Report Card (SRC) definitions. https://tea.texas.gov/texas-schools/accountability/academic-accountability/performance-reporting/school-report-cards

Tickamyer, A. R. (2000). Space matters! Spatial inequality in future sociology. Contemporary Sociology, 29(6), 805. https://doi.org/10.2307/2654088 DOI: https://doi.org/10.2307/2654088

Toole, R. D., Vincent, S. K., Sprayberry, S. R., Zimmerman, J. N., Brown, Z. R., & Ebelhar, C. M. (2025). Mapping Economic Disadvantage: Identifying Counties in the U.S. for Targeted Support in Agricultural Education. Paper presentation at the National American Association for Agricultural Education Conference, Lubbock, TX.

True, A. C. (1929). A history of agricultural education in the United States, 1785-1925 (Vol. 36). US Government Printing Office. DOI: https://doi.org/10.5962/bhl.title.35031

U.S. Bureau of Labor Statistics. (2023). Labor force data by county, 2022 annual averages. https://www.bls.gov/lau/tables.htm

U.S. Census Bureau. (2022a). Food Stamps/Supplemental Nutrition Assistance Program (SNAP). American Community Survey, ACS 5-Year Estimates Subject Tables, Table S2201. https://data.census.gov/table/ACSST5Y2022.S2201?q=S2201

U.S. Census Bureau. (2022b). Small Area Income and Poverty Estimates (SAIPE). Under Age 18 in Poverty. https://www.census.gov/data-tools/demo/saipe/#/?s_measures=u18

U.S. Census Bureau. (2022c). Small Area Income and Poverty Estimates (SAIPE). Median Household Income. https://www.census.gov/data-tools/demo/saipe/#/?s_measures=mhi

U.S. Census Bureau. (2023a). Counties in Persistent Poverty: 1989 to 2015-2019 [Dataset]. https://www.census.gov/library/publications/2023/acs/acs-51.html?utm_medium=email&utm_source=govdelivery

U.S. Census Bureau. (2023b). Small Area Income and Poverty Estimates (SAIPE) from the U.S. Census Bureau. https://www.census.gov/content/dam/Census/programs-surveys/saipe/brochures/SAIPE_2023.pdf

U.S. Census Bureau. (2024). Annual Estimates of the Resident Population for Counties: April 1, 2020 to July 1, 2023 (CO-EST2023-POP). https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-total.html

U.S. Department of Agriculture. (2017, November). The National School Lunch Program. https://www.fns.usda.gov/nslp/factsheet

Virginia Department of Education. (n.d.). Glossary. Virginia Department of Education School Quality Profiles. Retrieved September 9, 2024, from https://schoolquality.virginia.gov/glossary

Wilcox, S., Sharpe, P. A., Liese, A. D., Dunn, C. G., & Hutto, B. (2020). Socioeconomic factors associated with diet quality and meeting dietary guidelines in disadvantaged neighborhoods in the Southeast United States. Ethnicity & Health, 25(8), 1115–1131. https://doi.org/10.1080/13557858.2018.1493434 DOI: https://doi.org/10.1080/13557858.2018.1493434

Zahl-Thanem, A., & Rye, J. F. (2024). Spatial inequality in higher education: A growing urban–rural educational gap? European Sociological Review, 40(6), 1067–1081. https://doi.org/10.1093/esr/jcae015 DOI: https://doi.org/10.1093/esr/jcae015

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Published

03/31/2026

How to Cite

Toole, R. D., Vincent, S. K., Sprayberry, S. R., & Zimmerman, J. N. (2026). Bridging the Gap: Mapping U.S County-Level Economic Disadvantage for Targeted Support in Agricultural Education. Journal of Agricultural Education, 67(1), Article 23. https://doi.org/10.5032/jae.v67i1.3240

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Section

Journal of Agricultural Education

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