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2021-12-28
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Copyright (c) 2021 Kristin Carlson, Andrew Owen
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How to Cite
Accessibility: Distribution across diverse populations
Kristin Carlson
University of Minnesota
Andrew Owen
University of Minnesota
DOI: https://doi.org/10.5198/jtlu.2021.1963
Keywords: Job Accessibility, Demographics, Transit, Automobile
Abstract
High-resolution data are used to evaluate the distribution of job accessibility among workers at the national, state, regional, and urban scales. Annually updated accessibility datasets produced by the National Accessibility Evaluation are paired with Census data to tie accessibility, jobs, and worker information at the block level. Minnesota is selected as a case study for analyzing accessibility and drawing findings from the spatial datasets. The average accessibility by worker age, monthly earnings, educational attainment, race, and sex are calculated using data for the weekday morning commute by automobile and transit. The greatest variation in average accessibility among demographic groups is found for worker race. Based on home location, non-White workers systematically experience far higher accessibility to jobs by both automobile and transit than White workers as a percent difference from the population average. The finding holds at the national, state, and regional geographies. Additional findings are presented for each demographic group. The analyses presented here can be applied to other states and regions to identify where accessibility is distributed most and least equitably.
Author Biography
Andrew Owen, University of Minnesota
Directory of the Accessibility Observatory at the Center for Transportation Studies, University of Minnesota
References
El-Geneidy, A., R. Buliung, E. Diab, D. van Lierop, M. Langlois, and A. Legrain. 2016a. Non-stop equity: Assessing daily intersections between transit accessibility and social disparity across the Greater Toronto and Hamilton Area (GTHA). Environment and Planning B: Planning and Design, 43(3):540–560. ISSN 14723417. doi: 10.1177/0265813515617659.
El-Geneidy, A., D. Levinson, E. Diab, G. Boisjoly, D. Verbich, and C. Loong. 2016b. The cost of equity: Assessing transit accessibility and social disparity using total travel cost. Transportation Research Part A, 91:302–316. ISSN 0965-8564. doi: 10.1016/j.tra.2016.07.003. URL http://dx.doi.org/10.1016/j.tra.2016.07.003.
Fan, Y., A. Guthrie, and D. Levinson. 2012. Impact of light-rail implementation on labor market accessibility: A transportation equity perspective. Journal of Transport and Land Use, 5(3):28–39. ISSN 19387849. doi: 10.5198/jtlu.v5i3.240.
Foth, N., K. Manaugh, and A. M. El-Geneidy. 2013. Towards equitable transit: Examining transit accessibility and social need in Toronto, Canada, 1996-2006. Journal of Transport Geography, 29:1–10. ISSN 09666923. doi: 10.1016/j.jtrangeo.2012.12.008.
Gobillon, L., H. Selod, and Y. Zenou. 2007. The Mechanisms of Spatial Mismatch. Urban Studies,44(12):2401–2427. doi: 10.1080/00420980701540937.
Grengs, J. 2010. Job accessibility and the modal mismatch in Detroit. Journal of Transport Geography,18:42–54. ISSN 09666923. doi: 10.1016/j.jtrangeo.2009.01.012.
Grengs, J. 2012. Equity and the Social Distribution of Job Accessibility in Detroit. Environment and Planning B: Planning and Design, 39(5):785–800. doi: 10.1068/b36097.
Horner, M. W. 2004. Spatial dimensions of urban commuting: A review of major issues and their implications. The Professional Geographer, 56(2):160–173.
Kain, J. F. 1968. The Spatial Mismatch Hypothesis: Three Decades Later. Housing Policy Debate,3(2):371–392.
Kawabata, M. 2003. Job access and employment among low-skilled autoless workers in US metropolitan areas. Environment and Planning A, 35:1651–1668. doi: 10.1068/a35209.Lee, R. J. and I. N. Sener. 2016. Transportation planning and quality of life: Where do they intersect? Transport Policy, 48:146–155. ISSN 1879310X. doi: 10.1016/j.tranpol.2016.03.004.
Lucas, K., G. Mattioli, and A. Guzman. 2016. Transport poverty and its adverse social consequences. Transport, 169(TR6):353–365. doi: 10.1680/jtran.15.00073. URL http://dx.doi.org/10.1680/jtran.15.00073.
Owen, A. and B. Murphy. 2018a. Access Across America: Auto 2017. Technical Report CTS 18-16, University of Minnesota, Minneapolis, Minnesota.
Owen, A. and B. Murphy. 2018b. Access Across America: Auto 2017 Methodology. Technical Report CTS 18-17, University of Minnesota, Minneapolis, Minnesota.
Owen, A. and B. Murphy. 2018c. Access Across America: Transit 2017. Technical report, University of Minnesota, Minneapolis, Minnesota.
Owen, A. and B. Murphy. 2018d. Access Across America: Transit 2017 Methodology. Technical Report CTS 18-13, University of Minnesota, Minneapolis, Minnesota.
Pyrialakou, V. D., K. Gkritza, and J. D. Fricker. 2016. Accessibility, mobility, and realized travel behavior: Assessing transport disadvantage from a policy perspective. Journal of Transport Geography,
:252–269. ISSN 09666923. doi: 10.1016/j.jtrangeo.2016.02.001.
Schneider, I. E., T. Guo, and S. Schroeder. 2013. Quality of Life: Assessment for Transportation Performance Measures. Technical report, University of Minnesota, Minneapolis, Minnesota. URL http://www.lrrb.org/pdf/201305.pdf.
