{"title":"印度童工的空间分析","authors":"Lokender Prashad, M. Dutta, B. Dash","doi":"10.1108/JCS-06-2019-0032","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis 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.\n\n\nDesign/methodology/approach\nThe study has used ArcGIS software package, GeoDa software and local indicator of spatial association test.\n\n\nFindings\nThe 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.\n\n\nResearch limitations/implications\nThe 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.\n\n\nPractical implications\nThe 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.\n\n\nSocial implications\nThe study aims to achieve the SDGs adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025.\n\n\nOriginality/value\nThe study is purely original and there are no such studies in Indian context by using the latest software.\n","PeriodicalId":45244,"journal":{"name":"Journal of Childrens Services","volume":" ","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Spatial analysis of child labour in India\",\"authors\":\"Lokender Prashad, M. Dutta, B. Dash\",\"doi\":\"10.1108/JCS-06-2019-0032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis 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.\\n\\n\\nDesign/methodology/approach\\nThe study has used ArcGIS software package, GeoDa software and local indicator of spatial association test.\\n\\n\\nFindings\\nThe 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.\\n\\n\\nResearch limitations/implications\\nThe 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.\\n\\n\\nPractical implications\\nThe 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.\\n\\n\\nSocial implications\\nThe study aims to achieve the SDGs adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025.\\n\\n\\nOriginality/value\\nThe study is purely original and there are no such studies in Indian context by using the latest software.\\n\",\"PeriodicalId\":45244,\"journal\":{\"name\":\"Journal of Childrens Services\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2021-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Childrens Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/JCS-06-2019-0032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL WORK\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Childrens Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/JCS-06-2019-0032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL WORK","Score":null,"Total":0}
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.