Peer-reviewed article
Spatial analysis of child labour in India
Lokender Prashad, Mili Dutta, Bishnu Mohan Dash ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study uses spatial analysis and census data from 2011 to map the distribution and clustering of child labour across districts in India for children aged 5-14 years. The research identifies that child labour is positively associated with rural location, high fertility rates, and poverty, while negatively associated with female literacy and teacher-to-pupil ratios. The authors suggest that interventions should focus on improving school infrastructure, promoting female education, and reducing fertility rates in high-prevalence areas.
Key points
- Child labour prevalence is geographically clustered across Indian districts, identifiable through spatial analysis
- Rural areas, high total fertility rates, and poverty headcount ratios show positive association with child labour
- Female literacy and lower pupil-teacher ratios are negatively associated with child labour incidence
- High-prevalence areas require increased teacher numbers, promotion of female education, and family planning initiatives
- Comprehensive approaches involving legislation, judiciary, poverty alleviation programmes, and media sensitisation are recommended
Limitations
This is a descriptive spatial analysis using only Census 2011 data, so it cannot establish causation or test whether specific interventions reduce child labour. The study identifies correlations and patterns but provides no evidence of effectiveness for any proposed interventions.
Abstract
Purpose This study on spatial analysis of child labour in India is a macro level analysis on child labour using the census data, 2011 of Government of India. The population census which is conducted once in 10 years only provides district level data on work-force distribution. The study has spatial analysis of child labour in the age group of 5–14 years in India. To assess the magnitude of the children in the labour force, district level data of Census 2011 has been used in the study. The study has made an attempt to identify the districts where there is high level of children in the labour force. This paper aims to estimate the magnitude and trends of children’s workforce participation using the census data as it is the only data base, which is available at the district level since 1961 onwards. The study has made an attempt to identify the clustering of child labour across districts in India and how child labour is clustered by different background characteristics. Design/methodology/approach The study has used ArcGIS software package, GeoDa software and local indicator of spatial association test. Findings The findings of study reveal that the proportion of rural, total fertility rate (TFR) and poverty headcount ratio is positively associated, whereas female literacy and the pupil-teacher ratio are negatively associated with child labour. It suggests that in the hot-spot areas and areas where there is a high prevalence of child labour, there is need to increase the teacher's number at the school level to improve the teacher-pupil ratio and also suggested to promote the female education, promote family planning practices to reduce TFR in those areas for reducing the incidences of child labour. Research limitations/implications The study also recommends that the incidences of child labour can be controlled by a comprehensive holistic action plan with the active participation of social workers. Practical implications The promulgation of effective legislation, active involvement of judiciary and police, political will, effective poverty alleviation and income generation programmes, sensitisation of parents, corporates and media can play effective role in mitigating the incidences of child labour in India. To achieve the sustainable development goals (SDGs) adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025. Social implications The study aims to achieve the SDGs adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025. Originality/value The study is purely original and there are no such studies in Indian context by using the latest software.