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Optimizing the spatial assignment of schools to reduce both inequality of educational opportunity and potential opposition rate through introducing random mechanism into proximity-based system

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  • Liao, Cong
  • Scheuer, Bronte
  • Dai, Teqi
  • Tian, Yuan

Abstract

A serious spatial inequality of educational opportunity was revealed worldwide, for wealthy families can access good schools by buying real estate with good school' enrollment quota. Although the existing studies had revealed that random-based school assignment can significantly improve equality of opportunity allocation, random mechanism was adopted only in few places. Two major resistances of introducing random mechanism exist: the possibility of increased commuting distance to schools and the effected relative beneficiaries. In order to make the random-based allocation more feasible, this study proposes a spatial optimization model to take these two factors into account into proximity-based school assignment system. The proposed multi-objective allocation model, with the constraint conditions of assigning students to 3 closest schools and school capacities, was developed in this study to minimize the spatial disparity of educational opportunity and the potential opposition rate of introducing random mechanism into proximity-based assignment system. The model will be solved by a heuristic algorithm and applied to a case study area of Shijingshan District, Beijing. The results showed that the proposed model could improve spatial equality of educational opportunity significantly, but along with a minor increase on commuting distance to schools. In addition, potential opponents of introducing random mechanism decrease as the weight of parameters related to opposition rate increases in the model, reducing nearly 10% in the best case. Therefore, the solutions provided by proposed model may encounter less resistance in a democratic voting system. However, the results also indicated that there would be some relative beneficiaries who may oppose introducing random mechanism into proximity-based school system even in the best case. This implies that, to achieve equal educational opportunity in the context of proximity-based school system, optimized allocation is needed along with a more even distribution of educational resources.

Suggested Citation

  • Liao, Cong & Scheuer, Bronte & Dai, Teqi & Tian, Yuan, 2020. "Optimizing the spatial assignment of schools to reduce both inequality of educational opportunity and potential opposition rate through introducing random mechanism into proximity-based system," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
  • Handle: RePEc:eee:soceps:v:72:y:2020:i:c:s0038012119304343
    DOI: 10.1016/j.seps.2020.100893
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    1. Gordon F. Mulligan, 1991. "Equality Measures And Facility Location," Papers in Regional Science, Wiley Blackwell, vol. 70(4), pages 345-365, October.
    2. William Clark & Regan Maas, 2012. "Schools, Neighborhoods and Selection: Outcomes Across Metropolitan Los Angeles," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 31(3), pages 339-360, June.
    3. Eric Delmelle & Jean-Claude Thill & Dominique Peeters & Isabelle Thomas, 2014. "A multi-period capacitated school location problem with modular equipment and closest assignment considerations," Journal of Geographical Systems, Springer, vol. 16(3), pages 263-286, July.
    4. Harris, Douglas N. & Sass, Tim R., 2011. "Teacher training, teacher quality and student achievement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 798-812, August.
    5. Clarke, S. & Surkis, J., 1968. "An operations research approach to racial desegregation of school systems," Socio-Economic Planning Sciences, Elsevier, vol. 1(3), pages 259-272, July.
    6. Parag A. Pathak, 2011. "The Mechanism Design Approach to Student Assignment," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 513-536, September.
    7. Goeverden, C.D. van & Boer, E. de, 2013. "School travel behaviour in the Netherlands and Flanders," Transport Policy, Elsevier, vol. 26(C), pages 73-84.
    8. Haase, Knut & Müller, Sven, 2013. "Management of school locations allowing for free school choice," Omega, Elsevier, vol. 41(5), pages 847-855.
    9. João Teixeira & António Antunes & Dominique Peeters, 2007. "An Optimization-Based Study on the Redeployment of a Secondary School Network," Environment and Planning B, , vol. 34(2), pages 296-315, April.
    10. Kesten, Onur & Unver, Utku, 2015. "A theory of school choice lotteries," Theoretical Economics, Econometric Society, vol. 10(2), May.
    11. Richard Arneson, 2018. "Four Conceptions of Equal Opportunity," Economic Journal, Royal Economic Society, vol. 128(612), pages 152-173.
    12. Tim Butler & Chris Hamnett, 2007. "The Geography of Education: Introduction," Urban Studies, Urban Studies Journal Limited, vol. 44(7), pages 1161-1174, June.
    13. Bouzarth, Elizabeth L. & Forrester, Richard & Hutson, Kevin R. & Reddoch, Lattie, 2018. "Assigning students to schools to minimize both transportation costs and socioeconomic variation between schools," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 1-8.
    14. Malczewski, Jacek & Jackson, Marlene, 2000. "Multicriteria spatial allocation of educational resources: an overview," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 219-235, September.
    15. Teixeira, Joao C. & Antunes, Antonio P., 2008. "A hierarchical location model for public facility planning," European Journal of Operational Research, Elsevier, vol. 185(1), pages 92-104, February.
    16. Richard Arneson, 2018. "Four Conceptions of Equal Opportunity," Economic Journal, Royal Economic Society, vol. 128(612), pages 152-173, July.
    17. Marsh, Michael T. & Schilling, David A., 1994. "Equity measurement in facility location analysis: A review and framework," European Journal of Operational Research, Elsevier, vol. 74(1), pages 1-17, April.
    18. Eric Budish & Yeon-Koo Che & Fuhito Kojima & Paul Milgrom, 2013. "Designing Random Allocation Mechanisms: Theory and Applications," American Economic Review, American Economic Association, vol. 103(2), pages 585-623, April.
    19. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    20. Lemberg, David S. & Church, Richard L., 2000. "The school boundary stability problem over time," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 159-176, September.
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