Educational Development and Disparities in India: District-Level Analyses

Chatterjee, Sayantani; Mishra, Udaya S.

doi:10.1007/978-981-13-5820-3_5

Cited by 5 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The three-layer cross-tabulation diagram shows the inter-linkages of socioeconomic factors and gender explicitly and adds further nuances to the existing debate. Spatial mapping of educational infrastructure and access has been reported in the existing literature (Chatterjee & Mishra, 2019;Kumar et al, 2011;Saleh & Balakrishnan, 2019), but that of OOS girls from different In the contemporary context, when the country is recovering from the second phase of the COVID-19 pandemic and preparing to safeguard from the third wave, any discussion on education is incomplete without touching upon the impact of the pandemic and the future implications. According to UNESCO (2021), COVID-19 has pushed inequalities in education by disproportionately affecting adolescent girls.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Out-of-school girls in India: a study of socioeconomic-spatial disparities

Mitra¹,

Mishra

Abhay

2022

GeoJournal

View full text Add to dashboard Cite

Despite numerous established benefits of girls' education, globally large numbers of girls are out-of-school (OOS). This poses challenges to achieving quality education (SDG 4) and gender equality (SDG 5) by 2030. In India, there are socioeconomic and spatial disparities also. The latest National Sample Survey data provides an opportunity to explore these issues. We used the unit-level data of 117,115 children (5-17 years). Our multivariate logistic regression analysis shows that the likelihood of OOS girls is at least 16% higher than that of boys. The probability declines at every stage of income quintile from 'poorest' to the 'richest'. The likelihood in urban areas is almost 35% lower than the rural areas. Compared to the upper castes the probability is higher for the backward castes. Compared to Hindus, the likelihood is higher among Muslims but lower among Christian and Sikh children. Our three-layer crosstabulation reveals that poor Scheduled-Tribes girls are the most vulnerable. The spatial plotting shows that the majority of the vulnerable regions belong to a few states viz. Rajasthan, Uttar Pradesh, Madhya Pradesh, Chhattisgarh, and Gujarat. Therefore, we argue for localized solutions for girls of diverse socioeconomic backgrounds in different regions. The relevance of this study also arises from the fact that there might be a further increase in the number of OOS girls due to the COVID-19 pandemic. ANOVA test suggests that there might be a shift of girls from private to government schools also, which calls for strengthening the public education system to prevent the problem from aggravating further.

show abstract

Section: Discussionmentioning

confidence: 99%

“…which varies significantly across the states and districts (Kumar et al, 2011). There have been studies to spatially map and identify the hot spot of supply-side variables (Saleh & Balakrishnan, 2019) or map educational outcomes through indicators at the state level (Chatterjee & Mishra, 2019).…”

Section: Conceptual Frameworkmentioning

confidence: 99%