Empowerment: A Myth for Informal Workers – A Study of Female Domestic Workers of South 24 Parganas, West Bengal

This paper considers a few indicators and uses the principal component analysis to explain the unknown indicators in assessing empowerment of 334 female domestic workers in South 24 Parganas district in West Bengal. Household autonomy, social interaction, economic decision, activity domain and protest against domestic violence are the principal components that have a positive and significant effect on empowerment. Fair wages and access to financial support and reasonable health facilities can be a great key to improving the physical and mental well-being of domestic workers.

Women empowerment has been a much-debated problem till date. Attention to women empowerment appears to have been pronounced more in the context of developing countries than developed countries. Economic development and gender-promotional activities give women more prominence and speaking capacity than they had a few years ago. But in India, bias against girls exists even today in investments in education, skills training, health problems, and so on. Women’s empowerment is necessary for not just ensuring their personal or household welfare, but also the well-being of the entire society. It is defined as the ability of women to effectively participate in all sociopolitical and economic activities which enable them to manifest and convert choices into attainments (Helling et al 2005).

While there is a developing consensus on the importance of women’s empowerment, there is no unique set of indicators that can be used to judge improvements or deterioration in women’s empowerment.  But women’s participation in paid jobs can be viewed as an important determinant of individual choices (Joekes 1987).  The present study takes the female workforce participation rates in the informal sector as a case study and based on survey data examines the standing of female domestic workers (FDWs), especially part-time domestic workers concerning the following objectives: (i) exploring the factors affecting the nature and magnitude of empowerment of the FDWs, and (ii) suggesting strategies for gender promotional activities to protect and accelerate empowerment level of FDWs.

FDWs are found to be most susceptible among the various kinds of workers in the informal sector and generally lack skills as well as means of skill enhancement. They have nearly no option to acquire decent employment that would reduce vulnerability and poverty, but their employment is considered necessary for sustaining livelihood. The number of women employed as domestic workers had a fourfold increase over the 10 years from 1999–2000 to 2009–2010 (Neetha 2013). FDWs are engaged in household oriented services like cooking, cleaning and mopping, washing utensils and clothing, and as caregivers for the elderly and children. Their earnings are the lowest and work conditions insecure. They work for six to seven hours daily and are the invisible force—the cogs that run the machine of the everyday existence for the majority of households. However, in real life, they face extreme challenges and their voices remain unheard. The empowerment of FDWs is necessary for their personal and household welfare.

Survey Area and the Sample

The selection of the district was encouraged by the growth and expansion of the southern part of the city of Kolkata; the existence of a large number of Bangladeshi migrants in South 24 Parganas (Kumar 2010) and evidence of large-scale commuting of unorganised workers (Roy 2003). South 24 Parganas district is the largest district in terms of area (9,960 sq km) with the second largest population (18.17%) in West Bengal. Once dismissed as non-lucrative, the south suburban areas of the district and its population has gained momentum in the last 15 years as developers acquired land for the construction of real estate.

A micro-level survey was conducted for one year in 2016. Systematic random sampling was used to sample 334 part-time FDWs staying in South 24 Parganas. The respondent women were listed under rural, suburban and urban and could further be categorised into locals (75.4%), slum dwellers and commuters (12.5% travel in local trains, 6.9% travel in busses and 5.2% travel in bicycles or auto-rickshaws) according to their place of stay.

Conceptual Issue

The study was structured to take into account a set of personal and socio-economic dimensions that shape women's empowerment. Such dimensions are both dynamic and interlinked, with a strong effect on women’s involvement in the labour market. It is believed that enhanced participation in the labour force gives women an opportunity to earn along with exposure to the outside world.

Personal dimensions include women’s participatory role in making household decisions. This helps to enhance self-determination, self-esteem and autonomy within households and results in their well-being as well as that of their children. They educate their children, thereby encouraging the process of capital accumulation. The expenditure on schooling for children increases when transfers are made to women (Doepke and Tertilt 2019). This facilitates the accumulation of human capital, which in turn contributes to economic growth.

Socio-economic dimensions include women’s contribution to family income and participation in the household economy, access to socio-economic resources and ownership of assets. With increased earnings, women’s participation in households’ economic decisions gets enhanced, thereby improving their self-reliance and bargaining power and decreasing financial subordination.

Various factors encourage women’s participation in the household economy. Improved self-confidence, control over resources and freedom of choice are some of them. These factors get boosted with education, age (experience) and higher income. Domestic workers are mostly illiterate or just literate. The lack of education is negatively associated with household decision-making. This holds back their bargaining power within households. Education can be linked with women’s autonomy, empowerment and gender equality through their participation in household decision making (El-Halawany and El-Deen 2009).

Empowerment Indicators

Women’s household work and agricultural activities in family farms are often not recognised as economic, although they are important. Women are regarded as free labour that deprives them of economic empowerment. In comparison, participation in some form of wage activities helps them provide financial help to the families. It is important to note that the remittances generated by a poor working woman are used for consumption, education of children, well-being, upgrading household nutrition, etc. That way the income of the FDW is an important source of survival strategy for the receiving households. The opportunity to support their family enhances their participation in taking household decisions.

In our study, individual empowerment is designed as a composite of 12empowerment indicators in Table 1. These indicators collectively measure the extent of workers’ involvement in household and personal decisions.

Table 1: Female Domestic Workers’ Response across Indicators

                                                                                                            (%)

Sl No

Dimensions/Variables

Response

Yes

No

1

Visiting friends/relatives without permission

57

43

2

Ownership of assets

39

61

3

Operating bank account

72

28

4

Decision in family expenditure

69

31

5

Sending daughter to school

68

32

6

Husband seeking money

85

15

7

Ownership of house

3

97

8

Primary insurance holder

5

95

9

Hiring domestic workers

7

93

10

Member of local body

7

93

11

Autonomy regarding household decisions related to health and resource Utilisation

33

67

12

Protest against physical assault by husband

31

69

 

    Source: Computed from 2016 data.

Empowerment in one or more indicators leads to empowerment in another. The overall value for each indicator is obtained by adding the response values of the items (Rai and Ravi 2011). The weights attached for each indicator is calculated by multiplying the loadings of each variable with the Eigenvalues identified in the principal component analysis. The indicators are binary, where “1” stands for empowerment and “0” for no empowerment. Thereby, individual empowerment for each FDW in the sample can be assessed separately. For an absolute comparison of women empowerment, the values have been classified into four categories, namely low (0-0.25), moderate (0.25-0.5), average (0.5-0.75) and high (0.75-1) empowerment.

Findings across empowerment indicators:

It is observed that mobility is associated with domestic work. This is in line with the literature which points out that free mobility is high for the poorest women who work to sustain a living. Mobility helps them to develop social networks that act as insurance against the crisis. These networks help poor women to gain access to goods and services, which they might otherwise find difficult to obtain (Raghuram 2001). Women, by developing and maintaining these networks, underwrite the security of the households. Although there are no restrictions in the movement for work in our sample of domestic workers, 43% of the workers have to seek approval from their spouse or family head to go out for social visits. The percentage is calculated from the outcomes that are assigned a value one if the woman admitted of no such permission and zero if she did.

Opposite views on poor labour market outcomes of Jordanian young women has been observed by Miles (2002). She found that cultural and family influences greatly restrict the mobility of women, which in effect limit their work quest and employment opportunities in turn. She also stated that family opposition stemmed from lengthy commutes that extend the working hours in private sector jobs.

Most of the female domestic workers in our sample are illiterate. Many workers work from a young age and attending school acts as a barrier in their years of work. It is observed from Pearson’s correlation in Table 2 which also shows a negative relation between years of schooling and years of work of a FDW in our study area.

Table 2: Pearson’s Correlation

Items

Correlations

YOSC

YOW

YOSC

 

Pearson correlation

1

-.096

Sig (2-tailed)

-

.081

N

334

334

YOW

 

Pearson Correlation

-.096

1

Sig (2-tailed)

.081

-

N

334

334

 

             YOSC = Years of schooling; YOW= years of work.

 Source: Computed from 2016 data.

However, some of the domestic do not want their daughters to pursue the same career path as them and recognise the necessity of educating girls. The negative responses of 32% in the fifth indicator in Table 1 apply to two types of workers: those who have daughters over the age of 15 and those who have children who have not yet reached school age.

2 % of the local domestic workers hire domestic workers for household work. This indicator is directly related to their economic independence. Despite women's considerable contribution to family income and survival, social control remains with the head of household. Even when husbands are unemployed, violence against women is noticeable. 69% of female domestic workers report incidences of physical assault at home. There is evidence of husbands seeking money (85%), and for many, this is true against physical violence. The empowerment scenario becomes alarming when women try to rationalise/justify violence against them. Accepting, experiencing and allowing violence on themselves is an expression of low self-confidence in women (Table 1).

Roy et al (2017) estimated the amount of empowerment of 300 rural-based self-help group members in West Bengal based on “access to resources,” “decision-making capability,” and “ability to make a stand.” However, the majority of the workers in our sample are suburban or urban settlers, with only 23 FDWs belonging to self-help groups.

Of the respondents, 66.9% have a bank account. Only 3% of respondents own a house whereas 53% possess durable assets such as TV, mobile, refrigerator, and so on. Only 17 workers have insurance. In all of the indicators evaluated, the study finds that local FDWs had a better situation than those living in slums and squatter camps. The largest number of women without ownership of assets or those who are physically assaulted are also found among the commuters and the squatter settlers.

Specification and Measurement of Variables in Principal Component Analysis

A principal component analysis is used to explain the unknown indicators in assessing empowerment. The results show that the correlation matrix is not an identity matrix and can be factorised (as shown in Table 3). Its test value is significant at 0.00. The Kaiser–Meyer–Olkin measure of sampling adequacy is 0.575.

Table 3: Communalities

Dimensions/Variables

Initial

Extraction

Visiting Friends/Relatives without permission

1.000

.809

Ownership of Assets

1.000

.824

Operating Bank Account

1.000

.663

Decision in Family Expenditure

1.000

.589

Sending Daughter to School

1.000

.484

Husband seeking Money

1.000

.517

Ownership of  House

1.000

.507

Insurance Holder

1.000

.568

Hiring Domestic Workers

1.000

.260

Member of Local Body

1.000

.629

Autonomy regarding household decisions related to health and resource utilisation

1.000

.736

Protest against Physical Assault by husband

1.000

.608

Extraction Method: Principal Component Analysis.

Source: Computed from 2016 data.

 

The values in the extraction column in Table 3 indicate the proportion of each variable’s variance that can be explained by the principal components. Hiring services of the FDW and sending daughters to school have low values indicating that these variables are not explained well by the analysis and are therefore dropped. However, it is observed in Table 4 that the first five components have an Eigenvalue greater than 1 explaining a 69% variance of the data.

Table 4: Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative %

Total

% of

 Variance

Cumulative %

Total

% of

Variance

Cumulative

 %

1

1.878

18.775

18.775

1.878

18.775

18.775

1.795

17.953

17.953

2

1.654

16.539

35.314

1.654

16.539

35.314

1.703

17.025

34.978

3

1.250

12.503

47.818

1.250

12.503

47.818

1.205

12.054

47.032

4

1.086

10.860

58.678

1.086

10.860

58.678

1.105

11.045

58.077

5

1.014

10.138

68.816

1.014

10.138

68.816

1.074

10.739

68.816

6

.840

8.401

77.217

 

 

 

 

 

 

7

.796

7.959

85.175

 

 

 

 

 

 

8

.663

6.635

91.810

 

 

 

 

 

 

9

.519

5.194

97.004

 

 

 

 

 

 

10

.300

2.996

100.000

 

 

 

 

 

 

Extraction Method: Principal Component Analysis

Source: Computed from 2016 data.

 Table 5 contains component loadings, which are the correlations between the variable and the component (possible values range from -1 to +1). The output is easier to read as we remove the clutter of low correlations (< 0.40) that are probably not considered meaningful. The first component is most highly correlated with OPBAC, decision-making in family expenditure and husband seeking money. The first component seems to measure the dependence of the husband on the wage of his spouse, a domestic worker. It measures the household autonomy of the FDW. 

Table 5: Rotated Component Matrix

 

Dimensions/Variables

Component

1

2

3

4

5

Operating Bank Account

.807

 

 

 

 

Decision in Family Expenditure

.777

 

 

 

 

Husband seeking Money

.715

 

 

 

 

Visiting Friends/Relatives without permission

 

.920

 

 

 

Ownership of Assets

 

.915

 

 

 

Ownership of House

 

 

.774

 

 

Insurance Holder

 

 

.770

 

 

Autonomy regarding household decisions related to health and resource utilisation

 

 

 

.844

 

Member of Local Body

 

 

 

.606

-.486

Protest against Physical Assault by husband

 

 

 

 

.874

Extraction Method: Principal Component Analysis,

Rotation Method: Varimax with Kaiser normalization.

Source: Computed from 2016 data.

There is a clear link between the second dimension of visiting friends and relatives and ownership of properties. The second part, therefore, explains the FDW's social interaction. The third aspect is closely associated with insurance and homeownership. While only 3% of FDWs own a house and 5% are primary insurance holders, these two factors are directly linked to their economic independence. The fourth component is highly correlated with autonomy health-related decision-making and the membership of local bodies. This measures the activity domain. The fifth component measures the power to restrain physical assault and the membership of local bodies. However, since the correlation between membership of local bodies and the component is less than 0.5, we consider explaining this variable in the fourth component. The aspect has an inverse connection with the membership of local bodies.

The Rotated Component Matrix and the Eigenvalues are presented together in Table 6. The 1st Eigenvalue (1.878) is multiplied with the 1st extracted column (0.807, 0.777, and 0.715); the 2nd Eigenvalue (1.654) is multiplied with the 2nd extracted column (0.920 and 0.915); the 3rd Eigenvalue (1.250) is multiplied with the 3rd extracted column (0.774 and 0.770); the 4th Eigenvalue (1.086) is multiplied with the 4th extracted column (0.844 and 0.606) and the 5th Eigenvalue (1.014) is multiplied with the 5th extracted column (-0.486 and 0.874). Now we add up the values obtained in the case of each variable.

Table 6: Rotated Component Matrix, Eigenvalues and Weights

Items

Components

Eigenvalues

Weights

1

2

3

4

5

1

2

3

4

5

Initial Eigenvalues

 

 

 

 

 

1.878

1.654

1.250

1.086

1.014

Operating Bank Account

.807

 

 

 

 

1.516

 

 

 

 

1.516

Decision in Family Exp

.777

 

 

 

 

1.459

 

 

 

 

1.459

HSM

.715

 

 

 

 

1.343

 

 

 

 

1.343

VFR

 

.920

 

 

 

 

1.522

 

 

 

1.522

Ownership of Assets

 

.915

 

 

 

 

1.513

 

 

 

1.513

Ownership of House

 

 

.774

 

 

 

 

0.968

 

 

0.968

Insurance Holder

 

 

.770

 

 

 

 

0.963

 

 

0.963

AHR

 

 

 

.844

 

 

 

 

0.917

 

0.917

Member of Local Body

 

 

 

.606

-.486

 

 

 

0.658

-0.493

0.165

PPA

 

 

 

 

.874

 

 

 

 

0.886

0.886

Total

11.252

 

 

AHR= Autonomy regarding household decisions related to health and resource utilisation; HSM = Husband seeking Money; PPA= Protest against physical assault by husband; VFR = Visiting Friends/Relatives without permission

Note (i) Extraction Method L Principal Component Analysis       

(ii) Rotation Method: Varimax with Kaiser Normalisation

Source: Computed from 2016 data

 

 

After calculating the weights for each indicator, as extracted by the Principal Component analysis, we can calculate the Individual Empowerment Index of the 334 FDWs by applying the formula:

 

Where EI = Empowerment Index

            Xi = ith indicator

            Ej= Eigenvalue of the jth indicator

            Lj= Factor loadings of the jth indicator

                                                                 Table 7:       

Weights to be Attached to the Empowerment Index of Female Domestic Worker

 

Weights

1.522

1.513

1.516

1.459

1.343

0.968

0.963

0.165

0.917

0.886

FDW 1

0

0

1

1

1

1

1

0

0

1

Source: Computed from 2016 data

For FDW 1, the calculation is carried on the following way (Table 7): (0 × 1.522 + 0 × 1.513 +1 × 1.156 + 1 × 1.459 + 1 × 1.343 + 1 × 0.968 + 1 × 0.963 + 0 × 0.165 + 0 × 0.917 + 1 × 0.886) ÷ 11.25 = 7.135 ÷ 11.25 = 0.63. This calculation gives us the Empowerment Index for FDW 1. Likewise, the same procedure is carried out for 334 FDWs and we get a value of Empowerment Index for each worker. Higher scores indicate higher empowerment and vice versa.

Magnitude of empowerment:

Classification of FDWs based on empowerment indicators in Table 8 reveals that 9% of the respondents have low empowerment, 47% have moderate empowerment, 40% have average empowerment and 4% of the FDWs are highly empowered. It is clear however that 56% of female domestic workers in our sample are concentrated in the low to moderate end of empowerment distribution, thus revealing their vulnerability and subjection within the household and society (Table1).

 

Table 8:

Classifying Domestic Workers on the Basis of Individual Empowerment Index

Classification

Number

Frequency

High empowerment (0.75-1.00)

13

4

Average empowerment (0.50-0.75-9)

134

40

Moderate empowerment (0.25-0.50)

158

147

Low empowerment (0-0.25)

29

9

Total

334

100

        Source: Computed from 2016 data

The dimensions or principal components that have been derived indicate Household Autonomy, Social Interaction, Economic Decision, Activity Domain and Defying Domestic Violence. Household autonomy involves operating a bank account, taking decisions on family expenditure and husband seeking monetary help from wife. Social Interaction includes the decision to visit friends and relatives without permission and possession or ownership of assets. Economic decisions include the ownership of a house, the decision on the recruiting service and the holder of primary insurance. Activity domains include domestic autonomy regarding household decisions related to the health and resources as well as the members of a local body. The principal components are regressed to identify the predictors of empowerment (Table 9).

Table 9: Principal Component Regression

Items

Coefficients

Std Error

t Stat

P-value

Constant

.474

.002

204.287

.000

Household  Autonomy

.110

.002

47.342

.000

Social Interaction

.110

.002

47.190

.000

Economic Dimension

.030

.002

12.934

.000

Activity Domain

.036

.002

15.522

.000

Defy Domestic Violence

.027

.002

11.457

.000

N

334

Adjusted R Square

.938

Durbin-Watson

2.370

F

1001.51 significant at 0.00

      Dependent Variable: Empowerment Index

      Source: Computed from 2016 data

A female domestic worker has a role in the decision making of family expenditure, if she has a bank account and also lends cash to her husband. The decision-making factor measures her household autonomy and is an important indicator of empowerment. Social interaction includes visiting friends and relatives without having to seek permission and asset ownership. Female domestic workers with social interaction have decision-making autonomy that manifests empowerment.

Ownership of property as well as holding an insurance coverage is directly connected to her economic independence, and economic independence is directly related to empowerment. An improved economic situation encourages the education of children, thereby encouraging human capital accumulation.

Activity domain includes autonomy over household decisions related to health and resource utilisation and membership of local bodies and this has a positive relation with empowerment.

Most of the workers in our sample are victims of physical abuse. It is a negative indicator of empowerment and is even more disturbing when women justify violence against them. Therefore, defying domestic violence or physical assault is an important factor that demonstrates the extent of empowerment. 31% of the workers who reject husbands’ rights to use violence are among those who are in their middle age, have minimum education or earn a higher wage (Table 1).

Concluding Remarks

Domestic work is a predominantly female-dominated sector. This type of informal work is poorly regulated and not protected by labour laws. Their vulnerability as workers becomes more complicated as they work in isolation in private households and depend on the generosity of their employers. Based on the results and discussion, the unsatisfactory level of empowerment of domestic workers is highlighted. Though a fair contributor to household income, they do not have access to resources and a very small percentage claim to have ownership of assets. Social control is found largely to rest with the male, even when husbands are unemployed. The entrenchment of traditional beliefs and practices and patriarchal relations are visible in terms of restrictions in social life, lack of ownership of assets and violence against women. Hiring services of a domestic worker, which seems to be an important indicator of economic independence, had to be dropped from the analysis because of the negligible percentage of positive response. 69% of female domestic workers report incidences of physical assault at home (Table 1).

Empowering domestic workers is essential as they seldom have an organised mechanism for collective bargaining and therefore the following propositions are suggested. 

Domestic workers are susceptible to unlawful working hours and low wages. Judicious working hours and fair wages improve quality of life. Execution of the ‘Minimum Wages Act’ and the provision of Social Security Support are essential to improve their well-being.

Low wages damage the saving prospects of workers. For sustainability in old age, long-term planning in savings and access and information on financial support is essential. They must get opportunities and avenues for self-development and training leading to wage enhancement, and career progression needs to be promoted through appropriate policies.

Physically, domestic work is exhausting. There is no healthcare for them and all costs of sickness, self and family hospitalisation are out of pocket costs. A key to improving the physical and mental well-being of domestic workers is access to free or fair healthcare facilities.

They need to have social protection and social security support. The need for applying all-inclusive strategies must be taken by the government and NGOs to ascertain the level of empowerment for female domestic workers.

In raising awareness and educating both employers and employees about the rights of domestic workers, national and regional campaigns can be instrumental. This will reduce exploitation and safeguard the vulnerable population of society.

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