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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, AkshayNarayanan, MenakaBlossom, JeffVenkataramanan, R.Saunik, SujataKim, RockliSubramanian, 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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