The State of School Infrastructure in the Assembly Constituencies of Rural India: Analysis of 11 Census Indicators from Pre-primary to Higher Education
- Authors
- Swaminathan, Akshay; Narayanan, Menaka; Blossom, Jeff; Venkataramanan, R.; Saunik, Sujata; Kim, Rockli; Subramanian, S. V.
- Issue Date
- 1월-2020
- Publisher
- MDPI
- Keywords
- India; assembly constituencies; geopolitical units; GIS; census; education infrastructures; social determinants of health
- Citation
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, v.17, no.1
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
- Volume
- 17
- Number
- 1
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/58509
- DOI
- 10.3390/ijerph17010296
- ISSN
- 1661-7827
- Abstract
- In India, assembly constituencies (ACs), represented by elected officials, are the primary geopolitical units for state-level policy development. However, data on social indicators are traditionally reported and analyzed at the district level, and are rarely available for ACs. Here, we combine village-level data from the 2011 Indian Census and AC shapefiles to systematically derive AC-level estimates for the first time. We apply this methodology to describe the distribution of 11 education infrastructures-ranging from pre-primary school to senior secondary school-across rural villages in 3773 ACs. We found high variability in access to higher education infrastructures and low variability in access to lower education variables. For 40.3% (25th percentile) to 79.7% (75th percentile) of villages in an AC, the nearest government senior secondary school was >5 km away, whereas the nearest government primary school was >5 km away in just 0% (25th percentile) to 1.9% (75th percentile) of villages in an AC. The states of Manipur, Arunachal Pradesh, and Bihar showed the greatest within-state variation in access to education infrastructures. We present a novel analysis of access to education infrastructures to inform AC-level policy and demonstrate how geospatial and Census data can be leveraged to derive AC-level estimates for any population health and development indicators collected in the Census at the village level.
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