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The Role of Catchment Areas on School Segregation by Economic, Social and Cultural Characteristics

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Abstract

This research analyses the socioeconomic and cultural segregation of students across school catchment areas using census data for the students in their second year of secondary education in Andalusia (the most populated region in Spain). The main methodology used is the Mutual Information Index, which satisfies all the desirable properties for measuring segregation. Concretely, we draw upon the additive decomposability property, which decomposes the segregation of students across schools into the different levels in which schools can be grouped, that is, catchment areas and, within catchment areas, by source of funding (public and semiprivate schools). We found that school segregation is greater than catchment areas’ segregation. Additionally, statistically significant correlations are found between the level of segregation within the catchment areas and factors such as size of the catchment area, parental level of education and size of the municipality where the school is located.

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Fig. 1

Source: Authors’ own elaboration

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Notes

  1. Programme for International Student Assessment.

  2. However, these authors indicated that parental level of education was not available at individual level, so they imputed the average level of the census block.

  3. In their analysis they grouped semiprivate and private schools.

  4. Our dataset contains information related to 2nd year secondary education students in the academic year 2011/12, who accessed secondary education in the academic year 2010/11, the reason why we focus on this law, which was applicable at that moment.

  5. The Survey of Financing and Expenditure of Private Education (Encuesta de Financiación y Gastos de la Enseñanza Privada) is conducted every 5 years. In 2009–10, semiprivate schools were publicly funded in 75%, while they were in 69.2% in 2014–15.

  6. These items are: the student has a suitable place to study at home; a desk; computer at home; Internet at home; resource books and education supporting books (dictionaries, encyclopaedia, etc.); books (novels, books of short stories, poems, comics, etc.); specialised magazines; daily press.

  7. The upper bound is the lower value of either the logarithm of the number of groups (4 or 2 groups) or the logarithm of the number of schools (1,297 schools).

  8. For example, in the Hutchens Index, weight is a function which depends on the proportion of students in each group within the social unit (only for two groups, because it is based in a binary distribution of the population) and the proportion of students in each group in the population, while weight is the proportion of students who belong to the social unit in the M index.

  9. In absolute terms, differences between semiprivate schools within the same catchment area are greater than differences between public schools within the same catchment area. For the total level of segregation (Table 1, column 1), the M Index for public schools in the same catchment area (Mc,public) is 0.057 and the M Index for semiprivate schools in the same catchment area (Mc,semiprivate) is 0.095. However, these figures are weighted by the proportion of students attending public and semiprivate schools, respectively (only 28% of students attend semiprivate schools, this is, pc,semiprivate), and this fact explains the higher contribution of public schools to the whole level of segregation.

  10. The decomposition of the Mutual Information Index for the subsample of catchment areas in which there are both types of schools (public and semiprivate schools) is available in the online supplemental material in Tables S1 and S2 (replicating Tables 1 and 2, respectively).

  11. The results of the Mutual Information Index for catchment areas with 1 school are available in the online supplemental material in Table S3 (replicating the first row of Table 1).

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Acknowledgements

The authors acknowledge the training received from the University of Malaga PhD Program in Economics and Business [Programa de Doctorado en Economía y Empresa de la Universidad de Malaga]. This work has been partly supported by FEDER funding (under Research Project UMA18FEDERJA024); Fundación Pública Andaluza Centro de Estudios Andaluces (under Research Project PRY085/19); the Andalusian Regional Government (SEJ-645) and Ministerio de Educación, Cultura y Deporte (scholarship FPU17/00432).

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Correspondence to Claudia Prieto-Latorre.

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Appendix

Appendix

See Fig. 2.

Fig. 2
figure 2

Decomposition of school segregation

See Tables 4, 5, 6, 7, 8, 9.

Table 4 Criteria which regulate the school admission of Andalusian students
Table 5 Descriptive statistics by number of schools within the catchment area (at school level)
Table 6 Descriptive statistics by catchment area
Table 7 Descriptive statistics by type of school (at school level)
Table 8 Academic achievement of poor and rich students (first quartile and fourth quartile of the ESCS distribution, respectively) according to the socioeconomic and cultural composition of the school they attend (schools from the first and fourth quartile of the ESCS distribution)
Table 9 Academic achievement of poor and rich students (first quartile and fourth quartile of the ESCS distribution, respectively) according to the socioeconomic and cultural level of the catchment area (catchment areas from the first and fourth quartile of the ESCS distribution)

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Prieto-Latorre, C., Marcenaro-Gutierrez, O.D. & Lopez-Agudo, L.A. The Role of Catchment Areas on School Segregation by Economic, Social and Cultural Characteristics. Soc Indic Res 158, 1013–1044 (2021). https://doi.org/10.1007/s11205-021-02728-1

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