The Study of Personal-Family and Socio-Economic Profile of the Migrant Child Labours

INTRODUCTION

Though inter-state migration of labour is practiced in many parts of Orissa, but as per the official statistics of labour commission, the district of Ganjam encounters maximum number of out-migrants particularly working in Surat Textile Mills. Jan Breman notes that the army of Oriyas is particularly impressive, Nine out of 10 are migrants from the Ganjam district of Orissa. In recent years, there has been a heavy out migration of child labours of this district of textile mills operating in Surat. It has been observed that child labour working in Surat textile mills sufficiently supplements the family income with constant periodic remittances. A qualitative research with the aid of Participatory Rural Appraisal (PRA) technique amply suggests that the emerging middle class families mainly turn their children into labour. Present money cost of imparting education to a child, future cost of probable educated unemployment , benefits of present skill formation, enhancing financial liquidity due to the constant periodic remittances of their children etc. influence the parents to determine the level and volume of out migration of child labours. Besides, very often these parents with the objective of further strengthening their resource entitlements like land, pucca house, etc. and to demonstrate others about their financial strength often instigate their children to be manifested as labour in far off places, particularly Surat. Though, the children working in adverse conditions in the far off places like Surat are denied of parental love and affection, still the amount of present earning provides them some degree of compensation and relief so that

they carry out this process of regular cyclical migration.[1]

A lack of education, a lack of knowledge, and poverty all play a role in causing child labour. Because of this, parents are forced to put their children to work rather than school in the hopes that they will earn some money and help support the family. Because child labour has been so pervasive and so deeply ingrained in Indian society for so long, it is not something that can be quickly eradicated. As a result, low-income children miss out on important developmental opportunities like as schooling, play, health, and well-being. They may also be denied their constitutional right to an early childhood. During childhood, an individual's destiny is formed by formal education and interactions with others. Thus, children under the age of 14 who work in factories or other workplaces are considered to be engaged in child labour. According to the International Labour Organisation (ILO) "Working long hours for low pay in unhealthy conditions that harm children's physical and mental development while also separating them from their families and depriving them of meaningful educational and training opportunities that could pave the way for a better future are all examples of child labour.". Innocent youngsters are forced to labour in appalling conditions by businesses or individuals. Both primary (agricultural) and secondary (industry) sectors in India are rife with

cheap salaries. As a result, the government has taken a number of aggressive initiatives to address the issue of child labour in the country.[2]

Aligarh is famous for the Aligarh University and the lock industries. Since its a criminal offence to employ children below the age of 14yrs in India, the employers give it off as job works to agents and families who do the work from their homes employing children from their neighbour-hood and most times their own children as well. Things could get really bad if anyone is found talking to the children or taking photographs of these children working. None of the children in the industry ever gets to go to school and do not know what they were going to do in the future. It is sad to realize that these children had lost the ability to dream or never had the time to dream because they worked minimum 10 hours a day and mostly all 7 days a week. They work there from the time they don‘t remember They are paid Rs. 40 a day (80 cents) and while they work from morning till sunset and sometimes if the work is more till 10pm. Large families with as many as 12 children are a common sight. While the father and sons go to the city in search of work, the daughters and mothers stay at home and do different kinds of jobs to contribute to the family income - Painting on shawls, jari work on sarees (sewing glitter or semi-precious stones), adding small aluminium pellets to the bulb holders etc.[3]

An overview of the theory of demand, supply and persistence of child labour cites Barman, Subhash (2011), for a study of the wage elasticity of child labour supply. Several studies seem to support the view that, though some child work can help in acquiring human capital, by etching individuals the skills and attitudes.[4] Dutta, Progya (2016),examined the interaction between credit markets, trade sanctions and the incidence of child labour in a two goods, two period model with unequally wealthy households. While both poverty and poor education quality, interalia, are important determinants of child labour, they find that the incidence of child labour decreases with the easing of borrowing constraints. They also found that trade sanctions can increase child labour, especially among poor households, a possibility that decreases as their access to credit improves.[5] Max Roser (2016) study reinforces this nexus that poverty and the absence of reliable legal and financial systems through which the poor can secure loans to safeguard against hunger or unexpected consumption

markets.[6]

Khare, Shirish (2013), shows that poverty is apparently not the main culprit in determining child labour in urban areas. It is suggested that future child labour surveys collected is aggregated data on urban rural differences as examining urban and rural child labour data separately enables a scrutiny of the validity and applicability of the luxury axiom. Although most of the studies on child labour are covered in review of literature, yet, there may be some studies which might not have come to the notice of the researcher. After observing the sector wise analysis of studies reviewed on child labour, it is learnt that so far few studies have dealt the child labour and their work involvement in various activities in organized and unorganized sectors, that too in rural and urban areas in a drought prone regions in India. The present study makes an attempt on the above aspects which also highlights the problems and prospects of child labour.[7] UNICEF (2019) find that opening up the Vietnamese economy resulted in the rice price to rise and this caused child labour to decline. Hence, while there is scope for coordinated action among developing countries to raise labour standards, so as to discourage international capital from fleeing from one country to another, one must be wary of policies that use punitive action, like trade sanctions, to enforce labour standards. It is not surprising that there is no one simple policy measure to eradicate child labour. Its persistence through two centuries is strong testimony that there is no easy solution. Yet, an improved understanding of the causes underlying child labour may provide the opportunity to craft polices that can sharply reduce and ultimately eradicate it. While the different studies have explored the links between child labour, health and education, and while different have been employed to measure health or education status, there seems to be a degree of consensus on many of the issues raised. While poverty is generally accepted as being one of the determinants of child labour, there are empirical studies which critique the poverty based explanations of child labour. These studies have failed to find a positive relation between poverty and child labour.[8] The paper by P K, Navya (2019), which surveys the large and rapidly growing literature on the subject of child labour, but focuses primarily on the new literature which uses the best of modern economic theory and econometrics is reviewed. It is argued in this paper that in crafting policy for mitigating the enormous problem of child labour, it is important to acquire a proper theoretical and empirical understanding of the phenomenon. What gives rise to child labour and what are its consequences? What are the interventions that we can think of in order to end child labour without harming children? A well-

starvation. The authors discuss them in a policy implications of these new findings and hope that this will contribute to better informed discussion and policy design in this area.[9] Sule, B. M. and A. J. Barakade (2011), attempts to answer the question whether there exists a threshold of weekly hours of work for 12-14 year old below which school attendance and performance are not adversely affected. This is a relevant policy question to examine as the authors pointed out that Article 7 of ILO‘s Minimum Age Convention, 1973 (No.138), stipulates that light work may be permitted for children from the age of 12 or 13 provided it does not prejudice their attendance at school or their capacity to benefit from the instruction received.[10] Census (2011), examined the relationship between the intensity of children‘s working., children‘s weekly working hours and their health outcomes, making use of household survey data from Bangladesh, Brazil and Cambodia. Since the effect of the number of hours worked on health outcomes depends on the nature of the work, the sector of work is included in the analysis. The findings are interesting in terms of shedding light on the correlations between work and ill health. With respect to child age, it is found that work-related ill health decreases with age for all countries except Bangladesh where only marginal differences exist among older children.[11] Wanmali, Sudhir Vyankatesh. and Sitanshu Mookerjee (2020) studied the effects of child work on adult health in Guatemalan siblings while accounting for non-observable family characteristics. In spite of this, their policy continues to consider child work and the prospective consequences for education and income as exogenous. In addition, because only people who are still living at home with their parents are included in the study, the sample is highly skewed toward children. This means that the sample will be biassed towards persons who have health issues because the decision to live with parents is dependent on health outcomes, such as if healthy kids are more likely to live on their own and children with disease or disability are more likely to stay with parents.[12]

• To study the personal-family profile of the migrant child labours. • To study the socio-economic profile of the migrant child labours. The design of the present study is Partially Diagnostic and Partially Analytical research design for analysis and it explains the Socio-Economic Background and Condition of Migratory Child Labour as well as it diagnoses their socio-economic, occupational and livelihood problems. The purpose of adopting partially Analytical and Partially Diagnostic research is to elaborate the socio-economic, occupational status and condition as well as their livelihood and their problems faced by migratory child labour on day to day basis and diagnose it for the social work intervention as well as solution and suggestion-recommendation for the Civil Society, Working NGO/GO and Government to for the proper social advocacy and program to eradicate their problems. Sample Design of the Study The sample size for the survey comprise of 300 respondents from each selected industry irrespective of the gender and experience of work. The demographic profile of the respondent is provided in the analysis. The child labour was selected from different employment sector like construction, daily needs, hotel, farm work, and vehicles and miscellaneous. The units were selected on the basis of the child labour force engaged in it. The various research studies conducted too reveal the inhuman treatment given to the child workers. The units are both manufacturing and labour oriented.

In this research study Area random sample method and Systematic Stratified random sample method with Lottery Technique from Simple Random Sample Method has been used of Probability Random Sample.

Initially there are 3310 migrant child labours in the universe and they are supposed to be selected but due to limitation of time and effectiveness of the present research, only 300 migrant child labours were selected as samples of the study, out of the total universe. study following stages of sampling were used. √ Contacting the office of Labour Commissioner, to ascertain the tentative numbers of migrant child labour. √ Block Officers having relevant information and facts related with migrant child labours were selected. √ Industries were contacted to find out migrant child labour only. √ Panchayats at village level were contracted to ascertain the number of child labour who migrate to place for the purpose of research of study but only those children were contacted who fulfill the necessary criteria Data Collection To study the effectiveness of human rights in prevention of child labour, researcher has collected data from Primary and secondary sources. • Primary Data For collecting primary data well-structured questionnaire was formulated. Children involved in child labour, employees and officials of Human rights were interviewed. Children and employees involved in child labour were interviewed by close ended questions in their local language. The primary data is also collected through observation techniques as children employed in informal sector are illiterate.

Under Primary source Interview Schedule and Structured Interview guide is used for research study of Migrant child labour. In beginning, Interview Schedule for employer was also supposed to be used but due to peculiarity of time neither the interview schedule for employer was used nor the interview guide was used. • Secondary Data The secondary data are those, which have already been collected by others. Therefore, they are also known to be historical data already collected and recorded by people. The data often prove to be of great value in exploratory research. And at the same time, they have been passed through statistical process. It comprises of sources like – internet, books, newspapers, brochures, journal, magazines, corporate directories, audited annual statements and accounts. The researcher has used secondary data from various published and unpublished reports, books, newspapers and journals etc. 1. Study of Official Documents. 2. Survey reports/committee reviews 3. Existing Literature

Approximately one in every eight people on the planet are migrants. International migrants account for around 214 million of these, whereas domestic migrants account for 740 million of these. About a third of the migrants from underdeveloped nations are between the ages of 12 and 24. Millions of minors under the age of eighteen are affected by this, whether they are travelling inside or between countries, with or without their parents. Young people are expected to follow this mass exodus in the coming years at a rate that has never been seen before and further alter population dynamics as a result of demographic shifts as well as economic disparity, violent conflict, state failure, natural disaster and resource and environmental pressures, in particular climate change. In many cases, child migrants are subjected to abuse, such as being kept in isolation, subjected to assault, working in substandard circumstances, and being threatened with reporting to the authorities. Among child labourers, evidence shows that migrant children earn less, work longer hours, are less likely to go to school, and are more likely to die on the job than their native counterparts. Although there are many children engaged, the needs and interests of migrants are usually absent from mainstream debates on child protection, labour and migration for minors (especially children). There are no effective policies for helping and safeguarding the children of migrants because of this. The UN Convention on the Rights of the Child mandates governments to protect children regardless of their race, colour, sex, language, religion, political or other opinion, national or ethnic or social origin, property, disability, birth, or other status, because "every child without discrimination of any kind" is born with the same rights. For both native and migrant children, this includes the right to be free of child labour. Respondents' personal and familial profiles may be seen through their responses to the survey.

The above table shows that of all the respondents, 267means 89% are Male and 33means. 11% are Female. Thus it is clear from the above data that there are more respondents, who are male child labour. Thus it is clear from the above data that 267% respondents are male. Thus, it is found that more respondents are male.

The above table shows that of all the total respondents, 03 means 01% respondents are in the age group of 5 to 10 years, 297 means 99% are in the age group of 11 to 15 years. Thus, it is clear from the above data that maximum respondents 297 means 99% are above the age of 10 years.

The above table shows that of all the total respondents, 42 means 14% live in the 1 to 3 Family Member Group, 177 means59% live in the 4 to 6 Family Member Group and 81 means27% live in the 7 to 9 Family Member Group.

The above table shows that of all the total 300 respondents, 177 means 59% respondents live in joint families and 123 means 41% live in nuclear families. Thus it is clear from the above data that 177 means59% live in joint families and 123 means 41% live in nuclear families.

The above table shows that of all the total 300 respondents, 62 means 22% live in Very Small Village less than 50 houses and 79 means 29% live in Moderate Village 50 to 100 houses, 91 means 31% live in Big Village more than 100 houses, 68 means 18% live in Tehsil Place. Thus maximum percentage of the child labour lived in big village with more than 100 houses. Thus it is clear from the above data that 91 means 31% live in Big Village more than 100 houses, 68 means 18% live in Tehsil Place.

The above table shows that of all the total 300 respondents, 65 means 21.7% belonged to Below Poverty Line (Very Poor) and 89 means 29.7% had Sufficient Income for Survival, 83 means 27.6% were Rich, whereas 63 means 21% were Well To-Do. Thus it is clear from the above data that 89 means 29.7% had Sufficient Income for Survival and 63 means 21% were Well To-Do.

The above table shows that of all the total 300 respondents, 165 means 55% villagers were Farmer Labour, 36 means 12% villagers were Traditional Workers, 66 means 22% villagers worked in Nearby District or Town, 33 means 11% were Trading, whereas 0% carried out or Small Business or Any Other Work. Thus it is clear from the above data that 165 means 55% villagers were Farmer Labour and 33 means 11% were trading, whereas 0% carried out or Small Business or Any Other Work.

The tabular representation above clarifies that there are 300 answers pondering over the condition of the parents. The percentage of parents who are percentage of parents with Primary level Education is 72 means 24%. The percentage of parents who have Higher Primary level Education is 12 means 4%. This explains that parents who are Uneducated & Illiterate but Contemplative is maximum 126 means 42% and the minimum percentage of parents who have Higher Primary level Education is 12 means 4%.

The above table shows that of all the total 300 respondents, there are126 means 42% accommodating in pecuniary sources. There are 78 means 26% not being able to complete minimum needs of children. There are 72 means 24% unable to complete minimum family needs. The percentage of parents who are far off from fundamental needs is 24 means 8%. This explains that maximum parents being able to accommodate in pecuniary sources is 126 means 42% and the percentage of minimum parents who are far off from fundamental needs is 24 means 8%.

As far as the economic condition of the parents of Child Labours is concerned, there are 230 means 76.67% who are very poor. There are 58 means 19.33% who had bare income for survival. There are 12 means 4% had sufficient means. Thus, most of the child labour was very poor with their higher percentage of 76.67%.

all they have any land of agriculture, it is not more 1.5 acres which is insufficient for their dally nourishment and expenses. According to the poor socio-economic condition of the migrant child labours, they are compelled to the work as a seasonal or permanent migrant child labour, where ever work is available for them. Migrant child labours belongs from poor socio-economic and neglected large families. Almost all of the migrant child labour comes from below poverty line condition deprived and neglected by society and family. Due to most of the migrant child labour are extremely weak in their socio-economic conditions and deprived by society, they are unhealthy or they are average in health and are deprived from education. The migrant child labours are neglected by their families and relatives, excluded from social gatherings because of their poor socio-economic status. An occupation of the migrant child labours is extremely worst and they must have to work in dangerous working condition. Most of the migrant child labour are exploited and ill-treated by their respective owners by underpaying them, involving them in extra working hours in dangerous conditions.

1. The Problem of Child Labour Needs More than One Solutions, EPW Engage, 2019. 2. Maharashtra, Wikipedia, 2020. 3. Trade Unions and Child Labour a Tool for Action, Slide Share, 2020. 4. Barman, Subhash (2011). Socio-Economic and Demographic Impact on Child Labour in India, West Bengal. 5. Dutta, Progya (2016). Maharashtra Among Top Four Child Labour States, Finds NGO Survey, The Hindu. 6. Ospina, Esteban Ortiz. and Max Roser (2016). Child Labour, Our World in Data. 7. Khare, Shirish (2013). Small Hands, Hard Labour in Surat Textile Industry, India Together. 8. Child Labour, UNICEF For Every Child, 2019. 9. P K, Navya (2019). For Almost 15 Million Migrant Children, Education remains a Luxury, Citizen Matters. 10. Sule, B. M. and A. J. Barakade (2011). Growth of Population Change in Maharashtra (India), Bioinfo, Vol. 2, No. 2. 12. Wanmali, Sudhir Vyankatesh and Sitanshu Mookerjee (2020). Maharashtra State, India, Encyclopedia Britannica.

PhD Student, Kalinga University, Raipur, Chhattisgarh