Embed Size (px)
Citation preview
CHAPTER – 4
PARTICIPATION OF WOMEN WORKFORCE AND SOCIO-ECONOMIC PROFILE OF
RESPONDENTS
114
CHAPTER – 4
PARTICIPATION OF WOMEN WORKFORCE AND SOCIO-ECONOMIC PROFILE OF RESPONDENTS
This chapter focuses on an analysis of economic participation of women
workforce in different sectors, with particular reference to manufacturing and service;
and socio-economic profile of 300 women workers covered through field
investigation as sample respondents. The participation of women workforce, covered
sectoral distribution and participation of male and female workforce from 1993-94 to
2009-10 based on NSSO data of various rounds, by status of employment as self
employment, as self employed, regular employees and casual labour, women workers,
role in tobacco processing industries, and factors affecting female labour force in
India. Analysis is also made of female employment based on Annual survey of
Industries date from 2010-11 and 2011-12. The socio-economic profile of 300 women
respondents covered various aspects relating to age, education, income, experience
etc. Out of 300 respondents 271 are women workers and 29 are women supervisors.
This chapter divided into two sections.
SECTION – I: PARTICIPATION OF WOMEN WORKFORCE IN INDIA
4.1 Introduction
Only about one-third of India’s workforce consists of women, but a large
majority of them, about 67 per cent are engaged in agriculture. Out of them male
workers were only 55 per cent who were in that sector in the year 2009-10 (Table
4.1). Utilities, the sector that meets the criteria of good quality of employment most
often, employ only 0.08 per cent of women workers while 0.35 per cent of total male
workers work in this sector. Similar is the situation in transport and communication,
another sector providing reasonably good quality of employment, whereas only 0.43
per cent of women workers work in, the corresponding proportion of male workers is
6.04 per cent. Only about one per cent of women workers but over 2 per cent of male
workers were in financial services. Women workers are, however, more likely than
men to be in the community, social and personal services: over 10 per cent of them
are in this sector, as against 8 per cent of male workers. The share of agriculture in
115
employment has been declining over the years but the rate of decline has been slower
in the case of women workers than of men. Share of community social and personal
services, on the other hand, has been declining in male employment, while it has
shown an increase among female workers.
Table 4.1Sectoral distribution of Male and Female Workers during 1993-2010
(UPSS) (%)Sector Male Female
1993-94 1999-00 2004-05 2009-10 1993-94 1999-00 2004-05 2009-101 2 3 4 5 6 7 8 9
Primary Sector 57.43 53.53 48.64 45.27 77.52 75.36 72.26 66.99Mining & Quarrying
0.85 0.68 0.69 0.77 0.34 0.31 0.28 0.30
Manufacturing 11.22 11.46 12.51 11.51 9.41 10.01 11.75 11.34Utilities 0.53 0.37 0.38 0.35 0.13 0.03 0.03 0.08Construction 4.15 5.66 7.51 11.33 1.35 1.64 1.89 5.11Secondary Sector 16.76 18.16 21.09 24.02 11.24 12.00 13.96 16.82Trade, Hotelling etc.
9.70 13.02 14.13 14.00 3.22 4.19 4.14 4.55
Transport & Communication etc.
4.12 5.11 5.84 6.04 0.27 0.35 0.40 0.43
Financing, Insurance, Real estate& business services
1.27 1.60 2.24 2.71 0.35 0.45 0.63 1.05
Community, social and personal services
10.72 8.57 8.07 7.96 7.41 7.65 8.61 10.16
Tertiary Sector 25.81 28.31 30.27 30.71 11.25 12.64 13.78 16.19All Non‐Agricultural
42.57 46.47 51.36 54.73 22.48 24.64 27.74 33.01
Total 100 100 100 100 100 100 100 100Note: UPSS: Usual Principal and Subsidiary Activity StatusSource: prepared on the basis of various rounds of NSS data on employment and unemployment.
Taking regular wage and salary jobs as the best quality of employment,
women were at a large disadvantage as compared to men. While 19 per cent of male
workers belong to this category, the corresponding figure for women was only 11 per
cent in the year 2009-10 (Table 4.2). Thus, the likelihood of a woman worker finding
a regular wage or salaried job is much smaller than that of a male worker. The relative
position of women, however, seems to be improving over the years, in so far as the
proportion of regular workers has been increasing faster among female than among
male workers. Thus the proportion of regular employees rose from 6.4 per cent in the
year 1993-94 to 10.97 per cent in the year 2009-10, among the women workers, the
increase was much less from 16.95 to 18.81 per cent in the case of male workers.
116
Women are more often than men in the category of casual labour, though the share of
this category has been increasing in case of men, while it has seen some decline in the
case of women workers. Overall, there appears to be an improvement in the quantity
of employment among women, though they continue to be distinctly disadvantaged as
compared to men.
Table 4.2Distribution of Workers (UPSS) by Their Status of Employment:
Male, Female and Total during 1993-2010 (%)
Gender Year Self‐EmployedRegular Employees
Casual Labour
1 2 3 4 5
Male
1993‐94 53.75 16.95 29.29
1999‐00 51.28 17.86 30.86
2004‐05 54.17 18.34 27.49
2009‐10 49.57 18.81 31.52
Female
1993‐94 56.65 6.44 36.91
1999‐00 55.53 7.54 36.92
2004‐05 60.99 9.10 29.91
2009‐10 52.95 10.97 36.08
Total
1993‐94 54.70 13.53 31.77
1999‐00 52.61 17.65 32.75
2004‐05 56.38 15.35 28.27
2009‐10 50.58 16.68 32.79
Note: UPSS: Usual Principal and Subsidiary Activity StatusSource: prepared on the basis of various rounds of NSS data on employment and unemployment.
Of the estimated 136 million women workers in India in the year 2007-08
about 5.3 million or about 4 per cent were in the organized sectors. The corresponding
percentage for all, male and female workers work out to be around 6 per cent. Thus
the likelihood of a woman worker finding a job in the organized sector, which is
expected to fulfill the criteria of good employment, is about 67 per cent of a male
worker.
This is corroborated by the fact that while women accounted for about 30 per
cent of total workforce, their share in organized sector employment was 20 per cent
117
only. The share of women in the organized sector workforce has, however, been
increasing over the years; it was 15.4 per cent in 1995, increased to 17.6 per cent in
the year 2000, further to 18.6 per cent in the year 2004 and 19.5 per cent in the year
2007 (See GOI-MoF, Economic Survey, 2010-11).
Where do women workers find jobs in the organized sector? Over half of them
(56 per cent) were in community, social and personal services. And within that
division, a woman worker is likely to find job three times out of four in the public
sector. Manufacturing also employs about 18 per cent of organized sector women
workers. In this division, it is the private sector that is likely to employ a woman
worker eleven times more often than the public sector. It is a positive point in favour
of quality of women’s employment that is about 8 per cent of women in the organized
sector work in financial services, both in public and private sectors; the latter almost
three times more often than the former, employ women workers.
What is the proportion of women workers in different sectors of economic
activity? As pointed out earlier, women make up about 20 per cent of the organized
sector employment. They constitute large proportion (about 34 per cent) in agriculture
related establishments, mostly in the private sector.
Communities, social and personal services, which employ more than half of all
organized sector women workers, employ women in 27 per cent of their positions.
Manufacturing, especially in the private sector, also has a significant share of women
among its workers. Particularly notable is the relatively large proportion of women in
the employees in financial services, especially in the private sector. About 18 per cent
of workers in this division are women; the proportion is higher at 36 per cent in the
private sector.
4.2 Tobacco Employment
In India out of 10 million workers employed in the tobacco industry,
approximately 60 per cent are women, and 12 per cent to 15 per cent are children,
mainly young girls1 .The women Workers are involved in a whole range of jobs
1Rahul S., Vijay L., Grover S. and Chaturved A., Tobacco Use among Adolesent Student and the Influence of Role Models. New Delhi: Department of Community Medicine, UCMS and GTB Hospital, India (2009)
118
associated with tobacco like planting, weeding, marketing and maintaining beds,
picking tobacco leaves, tying leaves, and removing leaves after drying, grading of
tobacco and rolling of bidis2. Nearly 10 million workers are employed in the bidi
industry (6 million in rolling bidi and 4 million in collecting leaves. For instance, in
some families, everyone includes children-help in making bidis.
4.2.1 Women Workers’ role in Tobacco Processing Industries
Tobacco processing is the continuous job performed by female Tobacco
workers throughout the year. Hopper machine and Cutter machines cut tobacco into
different sizes, and separates tobacco into various sizes. The separated tobacco is
collected manually by female Tobacco workers. Fan machine separates mud and
small stone from tobacco. Climbing the machines and pouring the tobacco is done by
female Tobacco workers. The processed tobacco is then filled in bags and stored in
storage godowns. Pouring raw tobacco into machines and transporting tobacco filled
heavy bales is manually done by female Tobacco workers. Unhealthy workplace,
dusty work environment, and occupational stress affect workers’ health and
respiratory system.
The female workers were usually found to start their work at the time when a
woman in the society usually runs her family with children with financial support
from her husband. However, most of the women workers are forced to join such
hazardous jobs against social customs only because of poverty. Their earnings are
substantially low in relation to the work turned out by them, and also in relation to
wages paid to male workers. Their daily income is very meager, which was not
sufficient for them to bear the cost of their daily food and other requirements. As a
result they were being pushed towards a fatal nutritional problem, and various
malnutrition related diseases will develop. Health hazards of female labour in tobacco
processing are high; and their social status is low.
4.3 Women Employment
Women are almost half of the world’s population having enormous potential
but being under-utilised or unutilised for the economic development of the nation.
2 Sen U. (2002), Tobacco Use in Kolkata, Lifeline Newsletter 8, pp.7-9.
119
Half of the Indian population constitutes women and only half of them are literate.
Women’s work participation is about one-third. Majority of them are involved in
unorganised and domestic sector. Women’s work sustains the society economically.
They run households, rear children and perform economic and non-economic
activities within the families. We see them working in offices, farms and factories, but
all their time, their works/ contributions remain invisible. Their work is taken for
granted and their contribution to the survival/betterment of the family and the society
is regarded a natural outcome of their caring, nurturing and self-effecting nature. The
established notions on women’s work and their economic contribution to the society
and the state has been strengthened by old traditions and nurtured by cultural values.
We often hear that women’s work in the private sphere can’t be accepted as a
contribution to the nation’s economy, as it is not paid for, that “women are neither
producers; nor capable of hard physical labour,” that “women’s economic status is
linked to their family’s economic status” and that “men are earners, so they are heads
of the households.” But the fallacies in these statements have already been exposed.
UN Commission on Status of Women says “women constitute half of the world’s
population, accomplish about two-thirds of its work hours, receive one-tenth of the
world’s income.” Report of the Committee on the Status of Women in India, 1974,
known as ‘Towards Equality’ highlighted that neglect of women’s contribution to
economic activities, especially in the unorganized sector. It clearly stated that the
transition to a modern economy had meant the exclusion of an increasing number of
women from active participation in the productive process and continuation of women
working in the productive process and working for no returns and no recognition.
However, there is a need to strengthen and streamline the role of women in the
development of various sectors by harnessing their power towards nation building,
and to attain accelerated economic growth. The trends of globalisation and
liberalization are still altering the pattern of work making it difficult to measure its
impact. It is feared that small, casual and non-mechanised jobs will be wiped out, and
on the other hand, there will always be a need to do hard meticulous and handpicked
jobs for which women are good at. There is also need for qualified and skilled
workers for new areas of technology and computers, offering well paid opportunities
for urban educated women. With the change of the economic scenario, women’s lives
120
are changing. When they are thrown into the competitive world, they discover their
way to earn, to survive and to develop self-esteem.
Women’s employment scenario has thrown up new challenges at the
beginning of the 21st century. On the one hand, working women in the urban areas are
visible and vocal, and on the other hand, women in the unorganised sector are being
constantly engaged in the battle of daily survival. The women’s work is very
important to the family, the society and the nation. Though men are supposed to be
bread earners, women bear that major burden, especially in poor families, and their
income is certainly not supplementary. The poorest families are the most dependent
on women’s economic productivity. Nearly 30 to 35 percent of rural households are
estimated to be headed by women, and thus the families are most exclusively
dependent on their income. Even when there is a male earner, women’s earnings form
a major part of the income of the poor households. Women, especially from poor
households spend a major part of their income on the needs of their children and
family, while men do not hesitate to spend on their personal needs such as tobacco
and liquor.
The time has come now for women to come forward to utilize their potential
in a productive way. Plenty of less risk oriented and less skilled jobs are activities
available for which there is demand in the service sector which can be carried out at
the household level on full time or part time basis. Women’s presence is very small in
the service sector. At present, their involvement is merely as temporary labourers both
in rural and urban areas. Population growth is one of the reasons for the increasing
unemployment in our country, though it is not the only or main cause. At the same
time human resource and talent and skills available among women of different age
groups, and of different backgrounds, need to be harnessed for directing them for
productive work in areas considered relevant for them. With the transformation taking
place in terms of education and skill development, movement should be faster for
involving women in productive role in periods of their convenience in the near future.
4.4 Activity wise Distribution of Women Workers
Agriculture is the most important activity of the women workforce (79.4%) in
rural areas, with the highest number of women workers engaged as agricultural
121
labourers (Table 4.3). However, the percentage of women workforce in agriculture is
declining over years. Manufacturing and services are the other two sectors where
women are employed in large numbers, and these sectors present an increasing trend.
Table 4.3Percentage of Female Workers in Various Sectors during 2009-10
Activity % of Female Workers
Rural Urban
Agriculture 79.4 13.9
Mining and Quarrying 0.3 0.3
Manufacturing 7.5 27.9
Electricity, Water etc. 0 0.4
Construction 5.2 4.7
Trade, Hotels and Restaurants 2.8 12.1
Transport, storage & communication 0.2 1.4
Services 4.6 39.3
Total 100 100Source: NSSO Unit Level Data, 66th Round (2009-10).
In rural areas, the pattern of changes regarding distribution of workers by
employment status categories during the last fifteen years has generally been similar
for men and women workers. There has been a fall in self-employment and an
increase in casual labour for both the categories. In the urban sector, employment
status distribution for women workers has undergone a substantial change, with
regular employment having recorded an increase, while casual labour has decreased
correspondingly.
Table 4.4Labour Force Participation Rate3 for male and female in India during 2009-10
(Participation rate for 1000 males, females, and total persons, respectively)
Indictor Rural Urban Overall
Male Female Male Female Male Female PersonLFPR 539 176 537 129 538 163 359
Source: NSSO 66th Round GoI (2011), Key Indicators of Employment and Unemployment in India during 2009-10, National Statistical Organisation.
LFPR: labour Force participation Rate.
Table 4.4, reveals that at the overall level, 359 persons out of 1000 population
are participating in the labour force. Distribution among males and females reveals
3 Labour force participation rate (LFPR) is defined as the number of persons in the labour force per 1000 persons. LFPR= [(no. of employed + no. of unemployed persons)/Total Population] x 1000.
122
that LFPR in rural areas is 539 for males and 176 for females; and in urban areas 537
for males and 129 for females. In the overall picture, it is 538 for males and 163 for
females. Female work participation is, thus, very low in comparison to males in rural
and urban areas. As per the usual participation status of females (Table 4.5), among
females between the age group of 15-59 during 2009-10, female participation rate is
52.75 per cent, compared to non-participation rate of 47.25 per cent.
Table 4.5Usual participation status of Females in between the age of 15-59 in India,
during 2009-10
FLFPR 52.75%
NFLFPR 47.25%
Source: NSSO 66th round.Note: FLFPR (Female labour force participation Rate); NFLFPR4 (Not in Female Labour
force Participation Rate)
Women’s labour force participation in developing countries is low in
comparison to developed countries, as presented in Table 4.6; 29 percent in India is
low when compared to a number of other developing countries as well as revealed by
the figures for year 2010; 68 percent in China, 59 per cent in Brazil, 58 percent in US,
56 percent in UK, 51 percent in Indonesia, 50 percent in Japan, and 44 percent in
South Africa.
Table 4.6Female Labour Participation Rate
(% of female population aged 15 and older)Sl. No
Country 2007 2008 2009 2010
1 India 34 32 31 292 Indonesia 51 51 51 513 Japan 49 49 49 504 UK 55 56 55 565 US 58 58 58 586 China 69 68 68 687 Brazil 58 59 59 598 South Africa 46 47 45 44
Source: World Development Indicators 2012, World Bank, Washington D.C.
4 Persons who are neither ‘working’ and at the same time nor ‘seeking or available for work’ for various reasons during the reference period are considered to be ‘out of labour force’. The persons under this category are students; those engaged in domestic duties, renters, pensioners, recipients of remittances, those living on alms, infirm or disabled persons, too young or too old persons, prostitutes, etc.
123
4.5 Factors Affecting Female Labour Force in India – Analysis based on NSSO data
The level and pattern of labour force participation depend on employment
opportunities and demand for income, which may differ from one category of persons
to another. Labour force participation rates of women differ at any given age, with
their marital and education status. There are also important differences in the
participation rates of urban and rural populations, and among different socio-
economic groups. Female Labour force participation in India responds to economic,
social, cultural and demographic mechanisms. The impact of economic and non-
economic, socio-cultural factors may also be expected to differ widely across different
regions in the continental country characterised by enormous socio-cultural, agro-
climatic and caste-based diversities.
4.5.1 Demographic Variables: demographic variables such as age, marital status and
childcare responsibilities have a significant effect on labour force participation of
females.
4.5.2 Age wise Participation of Women Workforce
Labour force participation is generally lower for females than for males in
each age category. At the prime working age, the female rates are not only lower than
the corresponding male values, but often exhibit a somewhat different pattern. During
this period of their life-cycle, women tend to leave the labour force to give birth to
and raise children, returning-but at a lower rate-to economically active life when the
children are older. In India, as elsewhere, people face a conflict over time spent on
housework, and childcare versus time spent on paid work.
In order to find out the labour force participation among different age group
people, here, “Age” variable is disaggregated into nine categories. Table 4.7 indicates
that lowest participation of women is solely in the younger age group 15-19.
Enrolment of young people for education has been the main reason for this decline in
LFPR; similar is the case in two female age groups of beyond 50 years. 40-44 years is
another category where low labour force participation is recorded. In all the other age
groups, females are in the range of 15 to 17 percent for participation.
124
Table 4.7Labour force participation of females in India on the basis of
Age during 2009-10Sl. No Age In LFP (%) Not In LFP (%)
1 15-19 4.85 25.13
2 20-24 15.23 13.98
3 25-29 13.38 9.52
4 30-34 12.33 8.17
5 35-39 15.60 15.35
6 40-44 9.00 7.53
7 45-49 17.05 9.78
8 50-54 5.56 6.14
9 55-59 7.00 4.41Source: NSSO 66th round.
4.5.3 Marital Status
Labour force participation rate of married women is an important issue, and in
order to find out how marital status is influencing the female labour force
participation in India, “marital status” variable is disaggregated into four categories as
never married, currently married, widowed, and divorced/separated. Table 4.8 reveals
that LFP among widows is 63.36 per cent, in divorced/separated is 61.36 per cent,
never married 54.37 per cent, and among currently married 48.94 per cent. The table
indicates that labour force participation is high for widowed and divorced/separated
women, and it is low for currently married women. Widows or divorcees might,
however, face fewer cultural or social barriers that prevent them from working outside
the home, and are sometimes more free to migrate seasonally since there is no
husband or family to prevent them from doing so.
Table 4.8Labour Force Participation of Females in between the age group of15-59 according to Marital Status during 2009-10 (in percentage)
Marital Status, LFP NLFP
Never married 54.37 45.63
Currently married 48.94 51.06
Widowed 63.36 36.64
Divorced/separated 61.36 38.64
Total 52.46 47.54
Source: NSSO 66th round.
125
4.5.4 Social Group
The benefit of economic growth has not really trickled down to all sections of
the society. Indian society has historically been stratified into different social groups,
and there are certain groups, viz., Schedule Castes (SC) and Scheduled Tribes (ST)
social groups, which have primarily remained outside the mainstream of the society,
and are characterised by socio-economic backwardness. Caste has historically been
the major axis of inequality in labour force participation. Economic deprivation has
historically been much more pronounced among these social groups. The incidence of
unemployment was higher among these social groups. But in the case of women,
labour force participation has been low among general category. In India, while
schedule castes (SC) and scheduled tribes (ST) are generally disadvantaged in the
social structure, restrictions on women of these groups are less marked than on upper
castes women. According to NSSO 66th round (table 4.9) 55.48 per cent of other
backward classes’ females are occupied, 54.66 per cent are of scheduled tribe, 51.16
per cent are from others, and 47.25 per cent of scheduled caste females are occupied.
The proportion of ST women in the labour force participation is higher in the labour
force. High poverty rate and lower restrictions on mobility may be the main drives for
higher labour force participation of ST women than other women. Among the general
category, keeping women within the confines of the home is an assertion of status and
honor.
Table 4.9Labour Force participation of Females in between the age group
of 15-59 on the basis of Social group (in percentage)Social group LFP NLFP
ST 54.66 45.34
SC 47.25 52.75
OBC 55.48 44.52
Other 51.16 48.84
Source: NSSO 66th round.
4.5.5 Religion
The Table 4.10 reveals Labour force participation of females on the basis of
religion as categorised into three types. They are of Hindu, Islam and Christianity
religions. LFPR is 65.96 per cent in Islam, 57.99 per cent among Christians, and
126
50.22 per cent among Hindus. Labour force participation rate of females is low
among Hindus.
Table 4.10Labour Force Participation of Females in between the age group of
15-59 on the basis of Religion during 2009-10 (in percentage)
Religion LFP NLFP
Hindu 50.22 49.78
Islam 65.96 34.04
Christianity 57.99 42.01
Source: NSSO 66th round.
4.5.6 Region
Female labour participation is calculated region-wise, for six regions as shown
in Table 4.11. The regions in the country considered are: North, East, West, South,
North-East and Central. 57.69 per cent is the participation rate for the Southern
region, followed by 56.88, 52.82, 52.03, 52.02, 46.46 per cent in the Northern,
Eastern, Western, Central and North-Eastern regions, respectively. In the North-East
the female participation rate is the lowest, with South standing first. Except the North
East, in all other regions, participation rate ranges from 52 to 58 per cent.
Table 4.11Labour Force Participation of Females in between the age group of
15-59 on the basis of region (in percentage)Region LFP NLFP
North 56.88 43.12
East 52.82 47.18
West 52.03 47.97
South 57.69 42.31
North-East 46.46 53.54
Central 52.02 47.98
Source: NSSO 66th round.LFP: Female labour force participationNLFP: Not in female labour force participation
127
Female participation in the organised manufacturing sector is one of the
indicators of measurement. Table 4.12, presents the female participation rate in the
organized manufacturing sector in India during the years 2000-01 to 2009-10. From
the table, it is observed that on an average, 20 percent of the participating workers in
the organised manufacturing sector are females. The remaining 80 percent are male
workers. From this analysis, it is clear that the organized manufacturing sector in
India is dominated by male workers. Even when there are lots of changes taking place
with respect to female literacy, female empowerment, female employment, etc. during
this ten year period 2000-10, there has been no significant change in the proportion of
female participation in the organized manufacturing sector. In spite of the
implementation of many welfare policies for the protection and safety of female
workers for improving the female labour force participation in the manufacturing
sector, female participation rate in the organised manufacturing sector has not shown
improvement.
4.6 Female Work Force Participation in Indian Industry
Bivas Chaudhuri and A. K. Panigrahi (2013)5 in their paper examined the
female workforce participation and wage differentials in the organised manufacturing
sector in India, using the data available from Annual Survey of Industries publications
for the period during the years 2000-01 to 2009-10. Only female workers directly
employed by the industry and engaged directly in the production process are covered
in the study. From the analysis, it is found that around 20 per cent of female workers
are directly contributing to the production process in the organised manufacturing
sector. However, there are significant variations observed with respect to female work
participation and significant wages differentiation across different industry divisions
and across states.
5Bivas Chaudhuri and A.K. Panigrahi (2013), “Gender Bias in Indian Industry”, The Journal of Industrial Statistics, Vol.2 No.1, January-March, pp. 108-127.
128
Table 4.12Percentage of Female Participation in
Manufacturing Sector in India during the year 2000-10
Year Female
Participation (%)
2000-01 18.05
2001-02 19.08
2002-03 19.62
2003-04 19.49
2004-05 20.36
2005-06 19.81
2006-07 20.36
2007-08 19.78
2008-09 20.05
2009-10 19.81
Source: Annual Survey of Industries 2005, and 2010 - Factory Sector,Central Statistical Organisation, New Delhi.
It is found in the analysis of all India data that in a few industry groups,
significant proportion of female workers is found, in a few others female participation
is very low; and in the remaining groups, in between, but relatively very low (Table
4.13) Industries where female participation is good, along with percentage to total
workers in the industry during the year 2009-10 given in parentheses are as follows:
tobacco products (58.8%), wearing apparel (50.4%), leather and related products
(31.6%), food products (31.4%), and post-harvest crop and seed processing activities
(28.1%). A few product groups where the percentage ranges between 10 and 24 are
as follows: computer, electronic and optical products (23.3%), chemical and chemical
products (23%), other manufacturing activities (21.4%), textiles (19.3%),
pharmaceuticals and related products (15.3%), wood and wood products (11.7%),
beverages (11.2%), printing and reproduction of recorded media (10.8%), and paper
and paper products (10.5%).
129
Table 4.13Percentage distribution of Female Workers in labour-intensive
Industries (NIC-2008) during 2008-09 and 2009-10
NIC-08 DescriptionFemale Workers (%)
2008-09 2009-10
12 Tobacco products 50.70 58.79
14 Wearing apparel 52.56 50.36
15 Leather and related products 33.08 31.58
10 Food products 32.57 31.35
01Post harvest crop and seed processing activities
34.19 28.06
26Computer, electronic and optical products
23.17 23.26
20 Chemicals and chemical products 23.69 22.92
32 Other manufacturing 20.31 21.43
13 Textiles 19.54 19.28
Source: Annual Survey of Industries, 2009, and 2010 - Factory Sector,Central Statistical Organisation, New Delhi.
Under tobacco products group employing (58.8%) of female workers, (Table
4.14), industries like manufacture of bidi, and cigars and cheroots employ 67 to 69 per
cent of female workers. In other tobacco products, stemming and redrying of tobacco,
it ranges from 47 to 54 per cent. Snuff engages (31.4%), and in other products, the
proportion is as follows: zarda (11%), panmasala and related products (6.3%), katha
and chewing lime (2.8%) and cigarettes and cigarette tobacco (0.5%). In other product
groups where female workers’ participation is above (30-50%) also, there are product
lines where the percentage is in the range of 50 to 70. These are all typically labour
intensive industries offering opportunities for women workers. Some of the women
workers have a few years of experience in similar industries; and many may be
employed in industrial enterprises for the first time; and hence trained on the job in
the first few months of their service.
Female workforce participation in industry across states during the year 2009-
10 reveals that a few are leading, and many others are at a low level. The seven
leading states with the percentage in relation to total workers in the state are as
follows: Kerala (65%), Manipur (43%), Karnataka (41%), Tamil Nadu (41%), Sikkim
(31%), Andhra Pradesh (23%), and Puducherry (20%). In a number of states, female
130
participation is below 5 per cent. It is observed that the states with higher female
literacy rate are showing a trend of higher female participation in the organised
manufacturing sector. The perception that female labour force comes from the poorer
sections of the population may not be true in the case of the organised manufacturing
sector.
Wage differentials between female and male workers have been observed
across industry groups and across states. At the aggregate level, the female workers
are getting on an average 48 per cent lesser wage than that of male. The industries
such as food products, pharmaceuticals, textiles, paper and products with higher
female workforce participation also exhibit higher wage differentials. Similarly, in
states where female workforce participation is higher, the wage differentials are also
comparatively higher. The gender bias as revealed in the study requires to be removed
through proper policy planning and serious institutional corrections.
Table 4.14Percentage of female workers in Tobacco Industries during the year 2009-10
NIC2008
Description Male Workers(no.)
Female Workers (no.)
Total Workers (no.)
Female Workers (%)
1 2 3 4 5 612002 Manufacture of bidi 30670 67402 98072 68.7312004 Manufacture of cigars and
cheroots46 92 138 66.67
12009 Manufacture of other tobacco products including chewing tobacco n.e.c.
2363 2754 5117 53.82
12001 Stemming and redrying of tobacco
4742 4295 9037 47.53
12005 Manufacture of snuff 475 217 692 31.3612006 Manufacture of zarda 2478 305 2783 10.9612008 Manufacture of pan masala and
related products4585 307 4892 6.28
12007 Manufacture of catechu (katha) and chewing lime
1765 51 1816 2.81
12003 Manufacture of cigarettes, cigarette tobacco
5774 26 5800 0.45
Total 52898 75449 128347 58.79Source: Annual Survey of Industries, 2010 - Factory Sector, Central Statistical
Organisation, New Delhi.
131
SECTION-II: SOCIO-ECONOMIC PROFILE OF THE RESPONDENTS
4.7 Introduction
The Socio-economic background of a person covers a number of factors which
influence the quality of work life of the respondents. For this purpose, there is a need
to understand the socio-economic background of employees in Green Leaf Tobacco
Threshers Limited. (GLTTL) and Maddi Lakshmaiah & Co (ML&Co) organisations.
The objective of this section is to analyze the socio-economic characteristics of
employees in terms of their job category, occupation, length of service, age, religion,
educational background, income patterns, etc. Total man power in GLTTL is 690 and
in ML&Co 752 employees at the end of March 2012. Among them, 150 women
employees from each organization were selected for the study. The work force of the
organization has been classified into Supervisors and workers. Out of the total 300
women respondents, 29 are supervisors and the remaining 271 are workers. The
socio-economic variables of women workers covered in the analysis for both the
factories, as arranged in 14 tables in this chapter are as follows: nature of the job,
occupation of employment, length of service, age, religion, community, dwelling
background, status of literacy, educational qualification, family size, type of
residence, health condition, monthly income, and earning members in the family.
4.8 Job Category
Based on the nature of job, the respondents are classified into workmen and
supervisors; the job-wise distribution of the sample respondents is shown in Table
4.15 It can be seen that in GLTTL, 136 respondents (91%) are workers, and 14 (9%)
are supervisors, and that in ML&Co 135 respondents (90%) are workers and 15
(10%) are supervisors. In the aggregate, out of 300 respondents from two tobacco
processing factories, 90.3 per cent are in the worker category, and supervisors
constitute close to 10 per cent (9.7%).
132
Table 4.15Classification of Respondents by Job Category
Category GLTTL ML& Co TotalWorkers 136
(90.66)135
(90.00)271
(90.33)Supervisors 14
(9.33)15
(10.00)29
(9.66)Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.9 Occupational Status
Occupation in terms of gainful employment is a crucial factor in deciding
one’s position and status in society. A study of the occupational status of the
respondents explains their power, position and income. Table 4.16 presenting the
occupational status of the respondents shows that in GLTTL out of 150 respondents,
97 (65%) are permanent employees, 24 (16%) are daily wage employees, and the
remaining 29 (19%) are temporary employees. In the ML&Co, out of 150
respondents, 100 (67%) are permanent employees, 22 (15%) are on daily wage, and
the remaining 28 (18%) are temporary employees. In the aggregate, 66 per cent of
employees are of permanent category, 15 per cent daily wage earners, and 19 per cent
are temporary employees.
Table 4.16Classification of Respondents by Occupation of Employment
Category GLTTL ML & Co TotalPermanent 97
(64.66)100
(66.66)197
(65.66)Daily Wage 24
(16.00)22
(14.66)46
(15.33)Temporary 29
(19.33)28
(18.66)57
(19.00)Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.10 Length of Service
Length of service in a job reveals the incumbent’s amount of service, salary,
promotion, etc. In the table 4.17, presents the position of respondents is given by the
133
length of service in five categories. In GLTTL, 27 per cent of the respondents have
service between 4 - 6 years, 24 per cent is in between 2 - 4 years, 23 per cent in
between 6 - 8 years, 16 per cent have work experience of less than 2 years, and 10 per
cent have service of more than 8 years. In ML&Co, 35 per cent of the respondents
have service of 4 - 6 years, 21 per cent are in between 2 - 4 years, 17 per cent between
6 - 8 years, 15 per cent have less than 2 years, and the remaining 12 per cent have
more than 8 years. In the aggregate, 38 per cent of the respondents have experience up
to 4 years, and 62 per cent have experience beyond 4 years going up to 8 years and
more. 31 per cent of respondents have more than 6 years of work experience.
Table 4.17Classification of Respondents by Length of Service
Period of service (years)
GLTTL ML&Co Total
< 2 25(16.66)
23(15.33)
48(16.00)
2 - 4 36(24.00)
31(20.66)
67(22.33)
4 -6 40(26.66)
52(34.66)
92(30.66)
6 - 8 34(22.66)
26(17.33)
60(20.00)
> 8 15(10.00)
18(12.00)
33(11.00)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
4.11 Age of the Respondents
Age is an important factor in understanding one’s mental ability, and the
consequent awareness about the nature of duties associated with the job. Indisputably,
productivity of a worker is influenced by his age, and hence the age factor influences
the quality and quantity of work performed in the organization. Age factor has to be
studied in view of its influence on the job performance of employees.
The age-wise distribution of respondents is presented in Table 4.18; the
respondents are divided into 5 groups based on their age. In GLTTL, 27 per cent of
the respondents have their age group in between 45 - 55 years, 26 per cent are in
134
between 35 - 45 years, 22 per cent are in between 25 - 35 years, 14 per cent are in up
to 25 years, and the remaining 11 per cent are above 55 years. In ML&Co, 29 per cent
of the respondents are in the age group of 35 - 45 years, 23 per cent are in between 25
- 35 years, 22 per cent are in between 45 - 55 years, 16 percent are up to 25 years, and
the remaining 10 per cent are above 55 years. The above figures indicate that a
majority of the sample respondents are in the middle age group. In the aggregate, 33%
are up to 35 years age, and 67 per cent are of above 35 years. Those between 35-55
years account for 52 per cent and 11 per cent are of beyond 55 years.
Table 4.18Classification of Respondents by Age
Age group (years)
GLTTL ML&Co Total
< 25 21(14.00)
24(16.00)
45(15.00)
25 - 35 32(21.33)
35(23.33)
67( 22.33)
35 - 45 39(26.00)
44(29.33)
83(27.66)
45 - 55 41(27.33)
32(21.33)
73(24.33)
> 55 17(11.33)
15(10.00)
32(10.66)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
4.12 Religious Background
Religion plays a crucial role in human civilization and culture. India is a
country of diversity of religions. Hindus constitute the majority of population in the
country, and people of all other religions, such as, Muslims, Christians, Buddhists,
Sikhs and Jains are considered minorities. Each and every religion has its own
customs, traditions and practices. Religion can influence the people’s intellectual,
emotional and attitudinal behavior; which in turn makes its impact felt on their life.
Religion is one of the socio-cultural factors influencing the attitude and behavior, and
facilitates interaction with other people. People of each religion exhibit group
solidarity. The organization has to honor the practices of each and every religion, and
maintain religious harmony among all employees. Let us examine the religious
composition of respondents in the selected organizations.
135
Table 4.19 reveals the religious status of the respondents. In GLTTL, out of
150 respondents, 87 (58%) are Hindus, 44 (29 %) are Christians, and 19 (13%) are
Muslims. In ML&Co, the major segment of 92 respondents (61%) are Hindus, 36
(24%) are Christians, and the remaining 22 (15 %) are Muslims. In the aggregate,
Hindus account for 60 per cent, followed by Christians (26%), and Muslims (14%).
Table 4.19Classification of Respondents by Religion
Category GLTTL ML&Co TotalHindu 87
(58.00)92
(61.33)179
( 59.66)Christian 44
(29.33)36
(24.00)80
( 26.66)Muslim 19
(12.66)22
(14.66)41
(13.66)Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.13 Community Particulars
In India, diversified culture has developed because of the existence of different
religions. This situation led to the emergence of several castes. These castes are
grouped into four categories, viz. Open Category, Backward Class, Scheduled Caste
and Scheduled Tribe. Table 4.20 indicates that in GLTTL 37 per cent of the
respondents belonging to the open category, 32 per cent to backward class, 28 per
cent to schedule caste, and the remaining 3 per cent to scheduled tribes.
In ML&Co 57 per cent of the respondents belonging to the open category, 19
per cent to scheduled caste, 18 per cent to backward class, and the remaining 6 per
cent to scheduled tribes. The majority of the respondents in both the factories put
together are of open category (47%). Backward class comes next with 25 per cent,
and scheduled caste 24 per cent, with scheduled tribe as 4 per cent. ST population is
thus very low, and BC and SC categories are of about the same level.
136
Table 4.20Classification of Respondents Community wise
Community GLTTL ML&Co TotalOpen Category 55
(36.66)86
(57.33)141
(47.00)Backward class 49
(32.66)26
(17.33)75
( 25.00)Scheduled Caste 42
(28.00)29
(19.33)71
(23.66)Scheduled Tribe 4
(2.66)9
(6.00)13
(4.33)Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.14 Dwelling Background
An attempt is made in this study to know whether the respondents are born
and brought up in Rural, Urban, or Semi-Urban background. Table 4.21 shows the
dwelling background of the respondents by indicating whether they belong to rural,
urban or semi-urban area. In GLTTL, out of 150 respondents, 82 (54.66%) are from
urban areas, 22 (14.66%) are from semi-urban areas, and the remaining 46 (30.66%)
are from rural areas. In comparison, in ML&Co out of 150 respondents, 5 (3.33%) are
from urban, 30 (20%) per cent are from semi- urban, and the remaining 115 (76.66%)
are from rural areas. Because of the location of GLTTL in Guntur, 55 per cent are
from urban area, and similarly as ML&Co is near Chilakaluripet in a rural area, 77 per
cent of the respondents are from rural areas. In the aggregate, rural areas account for
54% of the respondents, followed by urban 29 per cent, and semi-urban 17 per cent.
Table 4.21Classification of Respondents by Dwelling Background
Dwelling Background
GLTTL ML & Co Total
Urban 82(54.66)
5(3.33)
87(29.00)
Semi-Urban 22(14.66)
30(20.00)
52(17.33)
Rural 46(30.66)
115(76.66)
161(53.66)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
137
4.15 Literacy Background
Education is an important factor in indicating the employee’s status in any
organisation. The job is assigned on the basis of educational qualification, and the role
of the employee is also determined accordingly. Table 4.22 indicates the literacy
status of the respondents. In GLTTL, 42 respondents (28%) are literate and 108 (72%)
are illiterate. In ML&Co, 82 respondents (55%) are literate, and the remaining 68
(45%) are illiterate. In ML&Co, the majority (55%) are literate, whereas in GLTTL
the majority (72%) are illiterate. When the two factors are taken together, only 41 per
cent of the respondents are literate, and 5.9 per cent have yet to become literate.
Table 4.22Classification of Respondents by Status of Literacy
Category GLTTL ML&Co TotalLiterate 42
(28.00)82
(54.66)124
( 41.33)Illiterate 108
(72.00)68
(45.33)176
(58.66 )Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.16 Educational Qualifications
Education is a vital element in the development of a human being. It is also an
instrument for boosting and strengthening socially useful skills, habits, and attitudes;
it creates bonds of common citizenship. Education is an essential ingredient in
achieving rapid economic development and technical progress, and in creating a
social order established on the values of freedom, social justice and equality of
opportunities.
Table 4.23 explains the distribution of literate respondents by educational
qualification. In GLTTL, 15 respondents (36%) are of below SSC qualification, 21
(50%) are of SSC qualification and 4 (9%) are of diploma/ intermediate, and the
remaining 2 (5%) are of having degree qualification. In ML&Co, out of 82
respondents, 59 (72%) are of below SSC qualification, 16 (19%) are of SSC
qualification, 4 (5%) are of diploma/ intermediate, and the remaining 3 (4%) are of
degree qualification. In ML&Co, there are a large number of below SSC; and those
138
with SSC is a smaller number compared to GLTTL. In GLTTL only 28 per cent are
literates, compared to 55 per cent in ML&Co. Among literates in GLTTL, those with
SSC are more, compared to those below SSC. In diploma/Intermediate, and Degree
qualification also, GLTTL’s score is slightly higher than ML&Co. The low level of
educational background in ML&Co can be attributed to the rural location of the
factory. GLTTL has the advantage of the urban location. In spite of it, it has the
disadvantage of low level of literacy.
Table 4.23Classification of Respondents by Educational Qualification
Education qualification
GLTTL ML&Co Total
Below SSC15
(35.72)59
(71.95)74
(59.68)
SSC21
(50.00)16
(19.51)37
(29.84)Diploma/ Intermediate
4(9.52)
4(4.88)
8(6.45)
Degree2
(4.76)3
(3.66)5
(4.03)
Total42
(100)82
(100)124
(100)Note: Figures given in parentheses indicate percentage to column total.
4.17 Size of the Family
The family is a social group, and is the strongest source of influence on the
individual’s attitude and behavior. Children learn from the family traditions, customs
and behavioral pattern, both consciously and unconsciously. Family members
influence the behavioral modification of any individual, and purchases in a family. A
reciprocal influence operates among the family members in all aspects of human life.
In India, traditionally joint family and extended family were in existence. In the
modern days, joint family system is fast disintegrating giving rise to the nuclear
family system. In urban India, nuclear families are quite common while in rural India,
joint families and extended families continue to operate. The size of the family has
been reduced in recent years when compared to earlier periods. People are made
aware of the importance of family planning, and the adverse effects of population
explosion.
139
Table 4.24, presents the distribution of the sample by size of the family. Based
on the size of the family, the respondents are classified into four groups. In GLTTL,
45 per cent of the respondents have the family size of 3 - 4 members, 27 per cent of
five and more members, whereas 23 per cent of the respondents have family size of 2
- 3 members, and only 5 per cent of the respondents have a single member.
In ML&Co, 36 per cent of the respondents have families of more than five and
above members, 32 per cent of 3 - 4 members, 23 per cent of 2 - 3 members, the
remaining 9 per cent have single member each. In ML&Co, families with 5 and above
members are more, while those with 3 - 4 members stand next. In case of GLTTL,
those with 3 – 4 members are more compared to those with 5 and above members
which stand next. In the aggregate position, the families with 3 - 4 members stand at
39 per cent, followed those with 5 and above persons at 31 per cent.
Table 4.24Classification of Respondents by Family Size
Size of family (members)
GLTTL ML&Co Total
Single 7
(4.66)13
(8.66)20
(6.66)
2 - 3 35
(23.33)35
(23.33)70
(23.33)
3 - 4 68
(45.33)48
(32.00)116
(38.66)
5 & above40
(26.66)54
(36.00)94
(31.33)
Total150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4.18 Residential Status
Housing is one of the basic human necessities. It is ‘an extension of human
personality’. Housing is one of the most important requirements for the employees.
Lack of proper housing creates discontent among the employees. Housing does not
mean simply shelter; it means modern housing which provides adequate rooms and
certain minimum amenities of everyday life. Table 4.25 reveals that in GLTTL, nearly
57 per cent of the respondents have own house and 43 per cent a rented house, while
in ML&Co 51 per cent of the respondents have own house and the remaining 49 per
140
cent a rented house. In the overall picture, nearly 46 per cent of the respondents have
a rental house. They should plan to acquire own house in the near future.
Table 4.25Classification of Respondents by type of Residence
Housing type GLTTL ML&Co TotalOwn 85
(56.70)77
(51.30)162
(54.00)Rented 65
(43.30)73
(48.70)138
(46.00)Total 150
(100)150
(100)300
(100)Note: Figures given in parentheses indicate percentage to column total.
4. 19 Health Conditions
Table 4.26 explored the health conditions of the sample employees in the two
factories by categorizing the state as excellent, good, average, and poor. Out of 150
sample respondents in GLTTL, 72 (48%) feel they have good health, 47 (31.3%) feel
it is average, 28 (18.7%) feel it is excellent, and the remaining 3 (2%) feel their
health condition is in a poor situation.
In ML&Co, out of 150 sample respondents, 97 (64.7%) feel that they have
good health, 26 (17.3%) feel it is excellent, 22 (14.7%) feel it as average, and the
remaining 5 (3.3%) feel that their health is in a poor position. The overall picture of
health conditions reveals as follows: 56 per cent feel it is good, 23 per cent feel as
average, and 18% feel as excellent. Only 3 per cent consider it as poor. It can be
stated that the health condition of all the sample respondents is quite good, with
nearly 18 per cent in both of them stating excellent.
141
Table 4.26Classification of Respondents by Health Conditions
Health condition
GLTTL ML&Co Total
Excellent 28(18.66)
26(17.33)
54(18.00)
Good 72(48.00)
97(64.66)
169(56.33)
Average 47(31.33)
22(14.66)
69(23.00)
Poor 3(2.00)
5(3.33)
8(2.66)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
4.20 Monthly Income
One of the main sources of income of the industrial employees is salary/wage.
The amount of salary or wage of the respondents would influence their standard of
living. Based on the standard of living, the employees can be categorized as of low-
income group, middle-income group, and high- income group. The distribution of
sample respondents based on their monthly income slabs is presented in Table 4.27. It
clearly shows that in GLTTL, 45 per cent of the respondents are drawing Rs 4000 -
5000 per month, 27 per cent Rs 3000 - 4000, 19 per cent Rs 5000 - 6000, 9 per cent -
more than Rs 6000, and the remaining 2 per cent drawing less than Rs 3000 per
month. The majority of the respondents are drawing in the range of Rs.3000 – 5000;
72 per cent in GLTTL and 70 per cent in ML&Co. In Rs. 4000 – 5000 slab, greater
percentage is in ML&Co (52) compared to GLTTL (45).
In ML&Co (52%) of the respondents are drawing Rs 4000 - 5000, (18%) each
in Rs 5000 - 6000 and Rs 3000 - 4000 ranges, (9%) more than Rs 6000, and the
remaining (3%) drawing less than Rs 3000 only; and the majority of the respondents
(70%) are drawing in the range of Rs 4000 to 6000. In both the factories, those
drawing above Rs 6000, account for nearly (9%). Those drawing up to Rs 3000 form
as low a percentage as 2 - 3.
142
Table 4.27Classification of the Respondents by Monthly Income
Monthly Income GLTTL ML&Co Total
< Rs.3000 3(2.00)
4(2.66)
7(2.33)
Rs.3000 - 4000 41(27.33)
27(18.00)
68(22.66)
Rs.4000 - 5000 64(44.66)
78(52.00)
142(47.33)
Rs.5000 - 6000 29(19.33)
27(18.00)
56(18.66)
>Rs.6000 13(8.66)
14(9.33)
27(9.00)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
4.21 Earning Members in the Family
Income is an important socio-economic variable because it indicates the
family’s ability or capabilities to purchase a product or service. A family’s economic
position consists of his or her spendable income, saving and assets, ability to borrow,
and attitude towards spending versus saving among, high-income group, middle
income group and low-income group members. It is assumed that each group has its
own consumption pattern.
Table 4.28, reveals the classification of respondents on the basis of the number
of earning members in the family. Based on the earning members in the family, the
respondents are classified into two groups, viz. those with one earning member, and
those with two or more earning members. It is clear that in GLTTL, (77%) of the
respondents, have two or more earning members in the family, and the remaining
(23%) have one earning member only. In ML&Co, (65%) of the respondents have
two or more earning members in the family; and the remaining (35%) have only one
earning member. Therefore, it can be stated that in the aggregate, most of the families
(71%) are depending on the income of two or more earning members. The table
reveals that in both the factories, (65%) in case of ML&Co, and (77%) in case of
GLTTL, families have two or more earning members, which indicates the
comfortable position of the families in the regard to monthly income, and ability to
spend on monthly basis.
143
Table 4.28Classification of Respondents by Earning members in the FamilyEarners in the Family
GLTTL ML&Co Total
One 34(22.66)
52(34.66)
86(28.66)
Two or more 116(77.33)
98(65.33)
214(71.33)
Total 150(100)
150(100)
300(100)
Note: Figures given in parentheses indicate percentage to column total.
4.22 Summing up
Economic Participation of Women Workers in India has been analysed based
on data available from a few sources. The sources covered are NSSO data on
employment and unemployment of various rounds, Annual Survey of Industries (ASI)
data, and prominent research studies in the country which covered different industry
groups. Sectoral distributions, industry group-wise distribution, tobacco based in
particular are covered in greater depth. Labour force participation of females is
covered for different demographic variables such as age, marital status, social group,
religion, and region. ASI data throws light of a female workers’ participation for
different industry groups, including different product lines based on tobacco crop.
Some of the striking features of analysis are as follows: (a) continuing dominance of
agriculture in employment, (b) predominance of informal employment, (c) dominance
of self employed of and casual labour categories.
Women workers’ participation is dominant in agriculture, industry and service
sectors, sector wise position in the public and sectors is as follows: 20 per cent in
organised sector employment in manufacturing and services; in community, social
and personal services 27 per cent; in manufacturing in the private sector, and in
financial services in the private sector. Proportion of women workers is dominant in
agriculture in rural areas, and high in manufacturing activity in urban areas. Service
sector plays an important role for women employment in urban areas.
Factors affecting women labour force are age, marital status, social group,
religion and region. In organised manufacturing sector, nearly 20 per cent of
participating workers are females. In spite of many welfare programmes, including
144
literacy campaigns, female participation rate has not shown much improvement.
Industries where female participation is good are: tobacco products, wearing apparels,
leather and related products, food products, post-harvest crop and seed processing
activities.
Under tobacco and tobacco products groups, product lines where women’s
involvement is high are: bidi, cigars and cheroots, stemming and redrying of tobacco,
sunuff, zarda, panmasala and related products, and others. Women participation is
high in labour-intensive activities.
The state with higher female literacy rate has shown a trend of higher female
participation in the organised manufacturing sector. Where female workforce
participation is higher, the wage differentials between male and female workers are
also comparatively high.
Regarding the social-economic profile of 300 sample women respondents,
from both the factories, a few observations are presented here. Out of 300 women
respondents, 271 are workmen, 29 are supervisors. Permanent employees are 66 per
cent, daily wage earners 15 per cent, and temporary workers 19 per cent. In terms of
length of service, 62 per cent of the respondents have experience beyond 4 years,
going up to 8 years and more; and 31 per cent have more than 6 years work
experience. The majority of the respondents (67%) are in the middle age group of
above 35 years. Religious back ground-wise, 60 per cent are in Hindus, 27 per cent
Christians, and 14 per cent Muslims. Community wise categorization reveals that
open category workers account for 47 per cent; backward classes and SCs 25 per cent,
each, and STs 4 per cent. Categorisation into Urban, Semi-urban and rural reveals the
proportion as 29 per cent, 17 per cent, and 54 per cent, respectively. Among the
respondents, only 41 per cent are literates, and the result 59 per cent illiterate.
Qualification wise among the literates, 60 per cent are below SSC, 30 per cent SSC, 6
per cent diploma/intermediate, and only 4 per cent are graduates. Educational level is
thus low among literates. Literacy itself is low. Size of the family is distributed
between 2-3, 3-4, and 5 and above members. 54 per cent have own house, and the rest
are in a rented house. 74 per cent are in good health; 23 per cent are in average health,
another 3 per cent are in poor health; this is a healthy sign.
145
Monthly income-wise, Rs.4000 and above income level, accounts for 75 per
cent, and between Rs.3000-4000 is of 23 per cent. Earning members in the family are
two or more. These indicate a healthy sign. Between the two factories, GLTTL being
urban-based has an edge in some indicators. ML&Co being located in a rural area is
disadvantaged in certain directions. In both the factories, the women employees have
shown encouraging socio-economic background.
