A Reflection on Slums in Select Municipal Corporation Areas

Journal of Xi'an University of Architecture & Technology Issn No : 1006-7930

Determinants to the stalling of urbanization: a reflection on slums in select Municipal Corporation Areas

Dr. Pradeep P1. Dr. Prasanth C B.2 1 . Assistant Professor, PG Department of Economics, Sree Kerala Varma College Thrissur. [email protected] 2. Assistant Professor, Department of Statistics, Sree Kerala Varma College Thrissur. [email protected]

Abstract –Though Kerala state has achieved an outstanding progress in Human Development map in India, it is not free from the trap of urban slum areas. The sprouting of slums in urban areas is the direct outcome of greater economic opportunities available in cities and towns. But the studies show that Slums are the products of failed policies, bad governance, corruption, inappropriate regulation, dysfunctional land markets, unresponsive financial systems and a fundamental lack of political will (Das. B, 1997). In recent past the urban expansion took place in Kerala in an astonishing manner. One of the main reasons for retarding the urban development process is the ever expanding slums in cities. It is a tiresome task of the policy makers and planners to resettle the slum dwellers to somewhere else. It might have various reasons such as internal - concern of slum dwellers about their livelihood activities, proximities to basic amenities, easy accessibility to the job opportunities; external – unaffordable price of land and building, informal local political support and so on. This paper tries to examine how far the slum settlements affect the urban development and what really happen to be the determinant factors for that. The empirical study conducted in slums situated in the Municipal corporation area Thrissur District in Kerala. The main objective of the study is to identify the factors that compel them to remain in the same location and how it obstruct the urban development process in the Municipal Corporation area.

Keywords –Urbanization, planning, stalling, development.

INTRODUCTION The term Urbanization is often used in the planning and development spectrum across the world. The United Nations deﬁne settlements with over 20,000 population as urban and those with more than 1,00,000 population as cities. Being a growing nation, India faces a precocious development pattern wherein India is doing what other countries did at a much later stage of development, when they were much richer (Aravind Subramanian, 2018). Since the inception of New Economic Policy of 1991, India has been experiencing a paradox of development in its various sectors of the economy. A low skilled rural labour blended with obsolete technology is still pervasively seen across the nation. As a result, a significant number of people lives in slums and their conditions are vulnerable day by day. The planners and policy makers have set targets and programmes from time to time for rejuvenating and resettling them to get rid of the worse conditions, however some factors pull them back to the place. This study tries to identify the factors that lead to pull them back in the same location and how it reckons with the urban development process in the Municipal Corporation area.

OBJECTIVES OF THE STUDY

The objectives of the study are the following 1. To examine the socio-economic status of the slum dwellers in Thrissur corporation. 2. To identify the factors underlying the stalling of urbanization in the study area

URBANISATION AND DEVELOPMENT Increasing migration from the countryside towards the cities is one of the profound determinants of ever increasing urban population. The gross migration of people from rural parts of the country to urban centres are due to the lack of return to the rural mass from agriculture as far as the livelihood means are concerned. As a

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result there is exodus of migration to urban centres. These distressed immigrants are usually sidelined from the benefits of urban development process.

Ghuncha Firdaus (2012) explained, in order to bridge the gap between the urban and rural centres emphasis needs to be given on policies regarding the creation of employment opportunities in agriculture itself through a mechanism of vertical diversification which involves development of downstream activities such as sorting, processing of produce and packing at farm level. Innovation in farming and value addition in farm products keep unemployed youth stay back in their native place.

Giok Ling Ooi and Kai Hong Phua, (2007) analysed that the development experiences in Hong Kong and Singapore have shown that urban slums and squatter settlement are not inevitable in cities. It is evident that those cities provide importance to urban housing provisions with planned economic development and anticipated urban growth. It implies that the urban administration needs to identify the connection among economic development, urban growth and housing then establish a linkage among them. For instance, the cities such as Jakarta or Manila despite having a high urban population do not have linkage between economic development or urban growth in provision of housing.

Lawrence RJ.,(2006) and Vlahov D, Galea S.(2002 ) studied that Urbanisation is a process in which more people move from rural areas to urban centres. These people anticipate better physical infrastructure and enhanced quality of life in urban areas. In a broad sense, urban life is meant to provide gleaming standard of living and easy accessibility to the modern life style. However, some of them are plunged into slum due to the adversities. They struggle to survive during their entire life and it is to extended to their next generations. The social determinant in formation of urban places makes sense here. Though the social determinant and multilevel approaches are not uniquely urban, they provide unique insights into formation of urban attributes such as size, density, diversity, and complexity.

David Vlahov et.al., (2007) The social-determinants perspective highlights the role of factors that operate at multiple levels, such as neighbourhood levels, municipal, national and global level in shaping health of slum dwellers. This approach emphasises better living conditions in areas such as housing, employment, education, equality, quality of living environment, social support, and health services that are central to improve the living standards of urban population.

Sundar Burra (2005) studied about some public projects that provided small apartments free for each family that has to be resettled. There is an argument in which the slum development has been supported by central and state governments programmes through various schemes such as the Valmiki Ambedkar Awas Yojana (VAMBAY) ,- subsidy scheme for the urban poor in India, the National Slum Development Programme, which offers a modest grant to states to provide basic amenities in slums, and the Swarn Jayanti Swayam Rojgar Yojana, which is a bank-loan-related self-employment programme for the urban poor, with a subsidy component; AMRUT (Atal Mission For Rejuvination and Urban Transformation) – provides water supply programmes, sewage projects, capacity building projects, recharge trench in urban slum locations. However, in a study conducted in Mumbai titled towards pro-poor framework for slum upgrading and redevelopment, described how the government of Maharashtra introduced legislation that protects slum dwellers from demolition but has no proactive provision to support resettlement.

Prasanth & Praseeja (2016), assumed that the city can spread out uniformly and entire land is available for residential buildings.. That is, no estuaries, mountains, national parks or lakes are there considerably large to affect our assumption. The population density of the city is negatively related with the distance from the centre. The city population and the rank of the city are closely related and such a relation is represented by rank size rule. For establishing these facts and relations these model are fitted to the Salem city population data (1991 and 2001) and tested the goodness of fit.

Archana & Prasanth(2018) ,explained City Expansion and Urbanization of Kerala has marked unique features. Due to the sea shore on the one side of Cochin, Thiruvananthapuram and Calicut, the size of the city expansion is like a half circle where as at Thrissur, Palakkad and Coimbatore is almost in a circular manner. Towards the centre of the city it is seen that the population density has an increasing tendency.In other words we can say that all the cities have an outer expanding nature and this expansion is circular.

Prasanth & Praseeja (2017), compared the nature of urbanization in Kerala and Tamil Nadu empirically using Markove chain model & projected the urban population for the next five decades by Markove chain. They also explained that the Markove Model is suitable for the study of city size distribution & the real data analysis by

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using the data from Kerala urban population and Tamil Nadu urban population in different decades shows the suitability of the model.

METHODOLOGY The study has been conducted at Thrissur Corporation area, in Kerala. The empirical data have been collected from two prominent locations in the city where roughly 900 household (families) resided. About 120 households were selected for a detailed interview through a structured questions schedule. In the sample survey 120 individuals were interviewed and each one of them represented each household. For analysis, some basic statistical tools such as z test, percentages, averages, diagrams, tables, etc have been used.

ANALYSIS

Table 1. Frequency table: of slum dwellers with respect to age, religion

Age Category Hindu Muslim Christian Table Below 18 4 4 18 -25 12 2 14 25-40 22 4 6 32 40 – 60 50 2 8 60 60 above 10 10 Total 98 6 16 120

Table 1 clearly implies that the age category 40-60 covers 50 per cent of the total population in the study area which resembles the demographic pattern of India wherein the nation gets demographic dividend. Even the age composition of the state of Kerala reflects the concentration of population in the same category. It is evident that a sizable number of income earning members of the family may fall into a dependent class in a decade or two. It signifies a forthcoming financial stringency and a socio-physiological insecurity among slum dwellers.

40 HINDU 30 MUSLIM

20 CHRISTIAN

0 Below 18 18 -25 25-40 40 – 60 60 above

Figure 1. Distribution of slum dwellers with respect to age & religion

Figure 1 depicts a steady increase in the number of Hindu respondents from the age wise category below 18 to the category 40-60. The second and third age wise categories (25-40 and 40-50) represent all three religions. The same two age wise categories have shown the respondents from Muslim religion. The respondent from Hindu religion includes all the five age wise categories in the sample.

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Table 2. Frequency table: of slum dwellers with respect to education & religion

- OBC SC/ST GEN MUSLIM CHRISTIAN TOTAL Upto 9th Std. 10 42 0 4 1 57 SSLC(matriculation) 2 22 0 0 9 33 +2 0 2 0 0 2 4 ITI/Diploma 0 0 0 2 2 4 Degree 0 6 2 0 2 10 Professional Course 0 0 0 0 0 0 Illiterate 4 8 0 0 0 12 Total 16 80 2 6 16 120

Table 2 has shown that nearly 50 per cent of the sample size belongs to an education category of up to 9th standard and more than one fourth of the sample size represents the category of matriculation (33 respondents). The population includes three religions such as Hindu, Muslim and Christian in which Hindu religion is subdivided into to Other Backward Caste (OBC), Scheduled Caste and Scheduled Tribes (SC&ST) and General Category (GEN). The categories OBC and SC/ST subsume the entire illiterate group wherein 10 per cent of the sample cannot read and write in their mother tongue. The same two categories could not even reach the matriculation level of education (together 54 per cent). By comparing the state average and the formal standard of education of the state of Kerala, the priorities given for education by the slum dwellers are far away.

From the data given above an analysis has been made in which the assumption is that only 10 percentage of the population is going for higher studies after their matriculation. That is the null hypothesis is Ho :P = 0.1, which means 10 percentage of the population going for higher education. Against H1: P > 0.1, Test Statistics Z = (p – P)/ Root (PQ/n) ~ N (0, 1). Here sample proportion p = 0.15. That is calculated Z = 0.58 and from standard normal table tab Zα = 1.645 for α= 0.05, P value is 0.28 for single tailed test with α = 0.05 which implies p > α. Hence, there is no reason to reject H0. Therefore, only 10 per cent are going for any higher studies after their matriculation.

45 40 35 30 25 OBC 20 15 SC/ST 10 5 0 GEN MUSLIM CHRISTIAN

Figure2. Distribution of slum dwellers with respect to education & religion

Figure 2 has shown about 75 percent of the respondents are from the first two categories of education. Hardly anyone represents professional course from three religions in the category of education. It is noted that only non-Hindus studies vocational courses such as ITI and Diploma. In SC/ST category above 50 per cent comes in

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the educational category of up to 9th standard. The only two respondents from the General Category acquired the degree level education.

Table 3 Distribution of the of Social establishment components among different religions.

Components of Hindu Muslim Christian Others Total Social establishment OBC SC/ST GEN house number 14 66 2 6 14 0 102 Electricity connection 10 64 2 4 14 0 94 Aadhar 16 80 2 6 16 0 120 voter’s ID 16 76 2 6 16 0 116 ration card 16 80 2 6 16 0 120 Health insurance 0 0 0 0 0 0 0

The term ‘social establishment’ refers the respondents have a permanent association with residing locality by acquiring house number, electricity connection, Aadhar card voter’s ID, ration card etc. All respondents acquired Aadhar card and ration card. Almost all belong to the category of BPL (Below Poverty Line) in terms of ration card. None of the respondents are covered with health insurance which implies they are grappling with livelihood earnings. All components of social establishment except health insurance are strong enough to reinforce the slum dwellers to reside in their own house.

90 80 70 60 house number 50 electricity 40 Aadhar 30 voter’s ID 20 ration card 10 0 OBC SC/ST GEN Muslim Christian

Figure3. Distribution of the Social establishment components among different religions. In figure 3 Five social establishment components are shown corresponding to their weightage in religion and separate bars have shown for Hindus as OBC, SC/ST and GEN. It is explicitly seen that the SC/ST category had some shortage in three components such as house number, electricity connection and voter’s ID. However, they become 100 per cent in Aadhar and ration card possession. The Muslim category is 100 per cent in all components except electricity connection.

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Table 4 Distribution of the Category of social establishment components in percentage. Total GEN Muslim Christian Social Establishment OBC SC/ST (Percentage) 92 house number 87 83 100 100 88 80 63 80 100 67 88 Electricity connection 100 Aadhar 100 100 100 100 100 99 voter’s ID 100 95 100 100 100 100 ration card 100 100 100 100 100 90 92 100 93 95 94 Mean

Table 4 explains the category wise distribution of the social establishment components in percentages. The General category in Hindu religion covers all the components with 100 percentages. As far as the mean is concerned Christians are better with respect to other two religions. The component electricity connection is relatively low for all the categories and the average is only 80 percentage which is quite below from the overall averages.

Table 5 Distribution of Employment Category in percentage

Own Employment Construction At House Coolie Factories Marketing small Offices Driver Others Total Category Work shops Keeping business Employees% 1.6 45 5 0 1.6 1.6 1.6 1.6 37 5 100

In table 5, All the categories of employment except Coolie and Driver jobs are meagre in numbers. However, more than 80 per cent of the employment categories belong to two employments which are mentioned before. No one has worked in factories and the employment such as marketing, self employment, at offices, housekeeping together cover less than one fifth of the total population.

Figure4. Distribution of slum dwellers with respect to the employment

Construction work Coolie At shops factories Marketing Own small bussinesss offices House keeping

The figure 4 describes the distribution of the total respondents among various employments. It is seen that the two prominent colours in the pie chart are the two categories – Coolie and Driver. These are the two jobs that provide earnings daily and it is needed to understand that these two jobs involve less risk and more chance of

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getting it daily. Both these jobs require less skill and there is very chance for them to slip over to unemployment.

Table 5. Distribution of employment in number of working days in a year

Number of days of job in a year(days) Employment Category Total Below Above 120 - 180 180 - 240 120 240 Construction work 2 2 Coolie 10 4 40 54 At shops 6 6 factories Marketing 2 2 Own small bussinesss 2 2 offices 2 2 House keeping 2 2 driver 2 4 38 54 others 6 6 Total 14 10 96 120

Table 5 explains almost 90 percent of the respondents get a minimum of 183 and above days of work in a year. Under usual status unemployment, more than 90 percent of the slum dwellers are employed regularly. About 38 of 54 respondents in drivers category of employment gets job above 240 days in a year which means eight months per annum. From the data given above an analysis has been made in which the assumption is that minimum 75 percentage of the population gets job not less than 240 days in a year. That is, the null hypothesis is Ho :P = 0.75, which means 75 percentage of the population gets job not less than 240 days in a year. Against H1: P < 0.75, Test Statistics Z = (p – P)/ Root (PQ/n) ~ N (0, 1). Here sample proportion p = 0.80. That is calculated Z = 1.25 and from standard normal table Zα = 1.645 for α= 0.05, P value is 0.1057 for single tailed test with α = 0.05 which implies p > α. Hence, there is no reason to reject H0. Therefore, only 75 percentage of the population gets job not less than 240 days in a year..

CONCLUSION

In conclusion, slum dwellers give less emphasis on human capital such as education, health insurance and at the same time they are keen on building social establishment components. It is evidently shown in the analysis that the slum dwellers are not moving towards higher ladder in education but they persistently thrive to get an employment and mostly gets unskilled low paid job. From the, is seen that a strong social establishment and a weak build up in human capital among the slum dwellers have an association turning out to be a determinant factor for stalling of urbanisation. Therefore, the empirical analysis of the study clearly shows that the slum dwellers are reluctant to go away from their settlement even when they offered a better life by the government.

REFERENCE

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8. Prasanth C B & Praseeja C B (2016), A Study On Urbanization: Distribution Fitting On City Size And Urban Population Characteristics Analysis, International Journal of Informative & Futuristic Research (IJIFR), 1780-1793, http://ijifr.com/searchjournal.aspx. 9. Prasanth C B & Praseeja C B (2017),A Markov Chain Model for the Demographic Study: A Case Study on Urbanization, International Journal of Mathematics & Computation, Volume 28, Issue Number 4 10. Sundar Burra Towards a pro-poor framework for slum upgrading in Mumbai, India Environment&Urbanization Vol 17 No 1 April 2005 11. UN, Department of Economic and Social Affairs, Population Division (2014): World Urbanization Prospects. 12. Vlahov D, Galea S. Urbanization, urbanicity, and health. J Urban Health. 2002;79 (4 Suppl 1):S1–S12.

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