Female Work Participation in Nadia District, West Bengal: Spatio-Temporal Analysis

 

Pijus Kanti Ghosh

Research Scholar, Department of Geography, University of Kalyani, Kalyani, Nadia

*Corresponding Author Email: moolinti.ganesh@gmail.com

 

ABSTRACT:

The work participation of female is a significant indicator for advancement of society and their economic liberty. But in our country and state, the female workforce participation rate is still low and Nadia district is no exception. In this paper an attempted has been made to assessing the concentration and distribution of female worker, male female work participation disparity, category wise male female main and marginal worker and relationship between literacy rate and female work participation rate. Concentration of female worker is analyzed with the help of location quotient and work participation disparity is assessed by using the shoper’s index method modified by Kundu and Rao. Relationship between literacy rate and female work participation rate is examined with the application of regression analysis. From the result analysis it is revelled that, female work participation rate is highly concentrated in southern part of the district while the rate is quite low in the northern part. A wide gap is found between male female work participation rates. Male work participation rate is too high than female work participation rate in every C.D. block. Disparity between MWPR and FWPR is relatively high in northern C.D. blocks than southern block and female work participation rate is strongly negatively co-related with female literacy rate. So, strengthening of women economic power and development of society women participation in workforce is very important.

 

KEYWORDS: Agricultural laborers, Female work participation, Labour force, Literacy, Marginal Worker.

 

 


INTRODUCTION:

Workforce means total number of people who are actively engaged in any working sector and participation rate refers to the actively involvement of people during an economic session. The proportion of female to total population in Nadia district is 48.2 percent (according to 2011 census) and only 11.47% female engaged in working sector “Women’s employment is a critical factor in their progression towards economic independence and is also considered as an indicator of their overall status in society.”

 

(Mammen and Paxsonm, 2008). Female work participation is very important for development of a nation or a region because national GDP and GNP are calculated with the help of total population. In, western countries, most of the female people are engaged in several working sector while it is still low in our country and state. “Female participation in the workforce assumes much importance in the case of developing countries because of its positive effects on the level of output and adverse effects on population growth ”(Mahata et. al., 2017). Female work participation not only help in economic growth of nation but also helps for establishment of female self dependency and a  crucial element for establishing a well and good society. Women’s participate on in working sector reduces the gender inequality and strengthened their economic power. (Narayan, 2016). Our society feel hesitance in female employment because of their conservative and narrow mind and due to the presence of hesitance and religious insist, most of the women cannot join any working sector. “In the Middle East and North Africa, one can observe vast and persistent gender gaps in employment despite rising female education levels in many countries” (Klasen and Pieters, 2015). Many female are highly educated but they are not employed in any working sector rather they are bounded in housewife or as a house hold worker. In many govt. and corporate sector female workers are get harassment from the male person. Developing countries faced gender inequalities due to the presence of poor status of women in society and low literacy rate. “Therefore, the promotions of gender equality and the women’s empowerment have been included among the Millennium Development Goals by the United Nation” (Deshbandhau et. al., 2017). Hence the women participation and empowerment has become an essential aspect of Society. In this work specially emphasized on block wise female work participation and their concentration, category wise main and marginal female worker and relationship between literacy rate and work participation rate.

 

OBJECTIVES:

The main objectives of this study are

1    To find out the concentration and distribution of the female work participation in Nadia District

2    To reveal the block wise male female work participation disparity

3    To analyze the category wise female main and marginal workers

4    To examine the relationship between female literacy and Female workforce participation rate

 

STUDY AREA:

The study area, Nadia district lies between 22º53' to 24º11' north latitude and 88º9' to 88º48' east    longitude. The district lies on in bank of river Ganga and situated 46 feet above sea level. The district has the international boundary with Bangladesh to east and comprises four district boundaries i.e. Bardhaman to west, Murshidabad in north, South 24 Pargana and Hooghly to the south and southern portion. The district is well connected to the inter district and the state with rail and road transport network. In 2011, total population of the district is 5,167,600 out of which 51.35% male and 48.64% is female. Growth rate of the population is 12.22%.Total literacy rate is 74.97% in which 78.75% male and 70.98% female.


Location of the Study Area:

 

Figure-1: Study area


 

 

MATERIAL AND METHODS:

This paper has been prepared mainly based on secondary data which is collected from the Nadia district census book 2011and various websites and published books, journals etc. To analyze and represent the male and female work participation in different sector and their concentration in Nadia district, different statistical and cartographic tools have been used. For showing the concentration of male female work participation concentration Shopers index, Regression method, location quotient is applied.

 

Location Quotient (LQi)=(ei/e) / (Ei/E) ,

Where,   

LQi- Location Quotient, ei-Female workers of individual C.D. block, e- Total female worker of the district, Ei-Total worker of invidual C. D block E,- Total workers of the District.

 

R= n.∑xy∑x.∑y÷}{n.∑

 

Shoper’s Index modified by Kundu and Rao (1983)=

Log (X2÷X1) + Log {(Q-X1) ÷ (Q-X2)}

Where, X2>X1 and Q- Constant.

 

FINDINGS AND ANALYSIS:

In Nadia district out of total population, 1,842,607 were engaged in work activities. 86.6% of workers describe their work as Main Work (Employment or Earning more than 6 Months) while 13.4% were involved in marginal activity providing livelihood for less than 6 months. Out Of total people 1,842,607 workers engaged in main work, 293,229 were cultivators while 461,580 were agricultural laborers (Figure2, 3).

 

MALE                                                         FEMALE

 

Figure: 2 Sex wise workers category for (a) Male and (b) Female

 

Table: 1Total worker and Female worker

C. D BLOCK

TOTAL WORKER

FEMALE WORKER

LOCATION QUOTIENT (LQ)

KARIMPUR- I

63760

6642

0.7381

KARIMPUR -II

73029

6247

0.6061

TEHATTA -I

81871

9088

0.7865

TEHATTA- II

46638

2703

0.4106

KALIGANJ

103923

8437

0.5752

NAKASHIPARA

125752

15976

0.9001

CHAPRA

98583

8471

0.6088

KRISHNAGAR -II

52618

10665

1.4361

NABADWIP

53111

11837

1.5791

KRISHNAGAR- I

118548

22978

1.3733

KRISHNAGANJ

52608

7440

1.0020

HANSKHALI

104587

15654

1.0605

SANTIPUR

100143

24272

1.7173

RANAGHAT- I

84840

13536

1.1304

RANAGHAT -II

128829

17142

0.9428

CHAKDAH

144632

20297

0.9943

HARINGHATA

86036

13060

1.0755

 

∑-1519463

∑-214445

 

Source: District Census Handbook, 2011, calculated by author*

 

Location Quotient is a valuable way of quantifying how concentrated a particular industry, occupation, or demographic group is in a region as compared to the nation. Here location quotient emphasized on concentration of female worker to total worker in every C.D. block. After calculation of Location Quotient it is found that, female employment is not sufficient to the northern part of the district (Karimpur-I, Karimpur-II, Tehatta-I, Tehatta-II, Kaliganj, Nakashipara and Chapra) because LQ<1. On the other hand, concentration of female workers is more than sufficient to Krishnagar-II, Nabadwip, Krishnagar-I, Santipur and Ranaghat-I as LQ>1.Employment is equal in the Krishnaganj, Hanskhali, Chakdah and Haringhata (LQ=1). After analysis the above data it is found that urban female are engaged in several industrial and other sectors and rural female mainly engaged in primary sector and some are small scale industry (Table-1).

 

 

 

 

 


TABLE: 2 BLOCK WISE URBAN MALE FEMALE WORK PARTICIPATION.        

C.D. BLOCK

TOTAL MALE POPULATION

MALE WORKERS

MWPR

TOTAL FEMALE POPULATION

FEMALE WORKERS

FWPR

KARIMPUR -I

94571

57118

60.39

88985

6642

7.46

KARIMPUR -II

111488

66782

59.90

105648

6247

5.91

TEHATTA -I

125875

72783

57.82

118447

9088

7.67

TEHATTA- II

77299

43935

56.83

73932

2703

3.65

KALIGANJ

171912

95486

55.54

162969

8437

5.17

NAKASHIPARA

198517

109776

55.29

188052

15976

8.49

CHAPRA

159736

90112

56.41

150916

8471

5.61

KRISHNAGAR -II

71614

41953

58.58

67858

10665

15.71

NABADWIP

69696

41274

59.22

65618

11837

18.03

KRISHNAGAR -I

162086

95570

58.96

152747

22978

15.04

KRISHNAGANJ

75573

45168

59.76

71132

7440

10.45

HANSKHALI

151645

88933

58.64

141395

15654

11.07

SANTIPUR

124400

75871

60.98

116680

24272

20.80

RANAGHAT -I

110676

71304

64.42

104461

13536

12.95

RANAGHAT- II

187615

111687

59.52

776790

17142

2.20

CHAKDAH

209513

124335

59.34

196206

20297

10.34

HARINGHATA

118709

72976

61.47

112359

13060

11.62

Source: District Census Handbook, 2011, calculated by the author*

 


Table no: 2 shows block wise male female work participation rate. In every C.D. block, percentage of male workers is high than female workers based on work participation rate. Highest male work participation rate found in Ranaghat-I and followed by Haringhata (61.47%), Santipur (60.98%), and Karimpur-I (60.39%). Lowest amount of MWPR found in Nakashipara block (55.29%). Santipur is the top C.D. block based on female work participation followed by Ranaghat-I, Hanskhali, Krishnagar-I and Nabadwip..Female work participation rate is very low in the northern part of the district the condition of and   Ranaghat-II, in FWPR is very pathetic because only 2.20% female engaged in working sector. Overall it can be said that, female work participation is high to the middle and southern part of the district.

 

Table: 3 Disparities between MWPR and FWPR

CD BLOCK

MWPR(X2)

FWPR(X1)

SHOPERS INDEX

KARIMPUR -I

60.39

7.46

1.04

KARIMPUR- II

59.90

5.91

1.14

TEHATTA -I

57.82

7.67

1.00

TEHATTA -II

56.83

3.65

1.32

KALIGANJ

55.54

5.17

1.16

NAKASHIPARA

55.29

8.49

0.93

CHAPRA

56.41

5.61

1.13

KRISHNAGAR -II

58.58

15.71

0.68

NABADWIP

59.22

18.03

0.62

KRISHNAGAR -I

58.96

15.04

0.711

KRISHNAGANJ

59.76

10.45

0.88

HANSKHALI

58.64

11.07

0.85

SANTIPUR

60.98

20.80

0.57

RANAGHAT- I

64.42

12.95

0.83

RANAGHAT -II

59.52

2.20

1.58

CHAKDAH

59.34

10.34

0.88

HARINGHATA

61.47

11.62

0.85

Source: District Census Handbook, 2011, calculated by author*

 

Table-3 shows the disparity between male work participation rates with female work participation rate. For find out the disparity, Shopers index has been used. Lowest disparity found in Santipur (0.57%). Highest disparity found in the Ranaghat-II C.D. block. So, it is recommended that, Ranaghat-II is the most backward C.D. block based on work participation rate. Possible reason behind backwardness of Ranaghat-II is less literacy; low female work participation and most of the people are lived in rural area (86%). On the other hand Santipur C.D. block is more developed because existence of reputed handloom industry where most of the female workers engaged. Handloom industry is the largest cottage industry providing widest avenues for employment opportunities, next to agriculture. (Das, et.al, 2016). Overall the rate of disparity is high to the northern part of the district low in middle and south part.

 

CATEGORIES OF FEMALE WORKERS:  

In this paper, female workers are classified into two broad categories i.e. main worker and marginal worker. Main worker refer to the, worker who are get 6 moths or greater than 6 month job in an economic year. Marginal workers refer to the, workers who are not get 6 months work in an economic year. Main and marginal worker are also classified into four categories i.e. Cultivator, agricultural labourer, household and other workers. Figure no-2 and 3 shows that, the number of main worker are greater than marginal workers in each C.D. block. Normally household workers and others workers are much higher than cultivator and agricultural labourer. Concentration of marginal workers high in Kaliganj, Nakashipara, Chapra, Krishnagar-I and Krishnagar-II and main workers highest in Santipur followed by Chakdah, Krishnagar-II, Nabadwip (Figure 4 and 5).

 

 

 

Figure: 3 Female main Workers

 

Figure: 4 Female  marginal Workers

 

 

 

RELATION BETWEEN FEMALE LITERACY RATE AND FEMALE WORKFORCE PARTICIPATION:

Literacy is one of the important factors of workforce participation especially in secondary and tertiary sector because in this sector most of the work is education based. Normally, if literacy rate is high in any country, workforce participation should be high than less literate country or region. But sometime this direct relation has been changed and creates inverse relation. Because workforce is not only determined by the literacy but also many other social and cultural factors.

 

Figure no-5: Relationship between literacy rate and FWPR.


TABLE: 4 RELATIONS BETWEEN LITERACY RATE AND FEMALE WORKFORCE PARTICIPATION POPULATION.

CD BLOCK

LITERACY ()

FWPR ()

KARIMPUR- I

46.85

7.46

349.50

 2194.92

55.65

KARIMPUR- II

47.53

5.91

280.90

2259.10

34.92

TEHATTA- I

46.23

7.67

354.58

2137.21

58.82

TEHATTA- II

46.96

3.65

171.40

2205.24

13.32

KALIGANJ

46.32

5.17

239.47

2145.54

26.72

NAKASHIPARA

45.55

8.49

386.71

2074.80

72.08

CHAPRA

46.98

5.61

263.55

2207.12

31.47

KRISHNAGAR -II

45.30

15.71

711.66

2052.09

246.80

NABADWIP

43.82

18.03

790.07

1920.19

325.08

KRISHNAGAR- I

44.75

15.04

673.04

2002.56

226.20

KRISHNAGANJ

45.17

10.45

472.02

2040.32

109.20

HANSKHALI

45.09

11.07

499.14

2033.10

122.54

SANTIPUR

44.73

20.80

930.38

2001.66

432.64

RANAGHAT -I

45.62

12.95

590.77

2081.18

167.70

RANAGHAT -II

45.73

2.20

100.606

2091.23

4.84

CHAKDAH

45.03

10.34

465.61

2027.70

106.91

HARINGHATA

45.47

11.62

528.361

2067.52

135.02

 

∑x-777.13

∑y-172.17

∑xy-7807.767

∑x2-35541.48

∑y2 -2169.91

Source: District Census Handbook, 2011, calculated by author*

Relationship between Female literacy rate and FWPR

 


 

 

In table no-4 a relationship has been made between literacy with FWPR by the help of Karl Pearson product moment correlation coefficient method. Hare, literacy plotted on X axis and FWPR plotted on Y axis. A best fit line is drawn by the help of yc=a+bx method. Hare the value of r is -0.757100. According to the value of ‘r’ there are no relationship between literacy and FWPR. As, literacy is not proportional to workforce participation so it is difficult to create systematic relationship between literacy and FWPR. So, there is no orderly relationship between the two variables. Such as literacy among females in Nabadwip is low but a lot amount of people are engaged in workforce participation. Similarly, Tehatta-I with high literacy but the workforce participation is comparatively low than other C.D. block. This shows that, education may not influence a women’s participation in work force positively but is an important determinant for better quality of women who are in work force and are very much influence by socio-economic variables.

 

MAJOR FINDINGS:

1    Female work participation is highly concentrated in southern part of the district and relatively less concentrated in northern part of the district.

2    Male work participation is high than female work participation to the every block of the district but percentage of female workers high in Nabadwip, Santipur, Krishnagar-I, Krishnagar-II and Ranaghat-I and low in Karimpur-I, Karimpur-II, Chapra, Tehatta-I and Tehatta-II.

3    Disparity between male female work participation rate high in northern part and low southern part.

4    Marginal workers are relatively highly concentrated in middle and northern part of the district.

5    A very negative relationship has been found between female literacy rate and female work participation rate because literacy is not only determinants of work participation rate.

 

CONCLUSION:

The participation of women in Nadia district was less as compared to their male people and it varied from one C.D block to another. The major finding of the paper is that the work participation rate of women is not increasing sufficiently with the rise in level of education and a wide gap is found between male female work participation rates. If the trend continues for some more time, there will be serious or harmful effects on to the society and also the economy of a country or a nation. So, for overall development of our society we should give much more importance to female as we give male, and freedom to move.

 

ACKNOWLEDGEMENT:

The research is supported by University Grant Commission (UGC), New Delhi and University of Kalyani, West Bengal.

 

REFERENCES:

1.     Chakraborty, I. and Chakraborty, A. (2009). Female work participation and gender differential inn earning in West Bengal, Occasional paper No. 18, Institute of Development Studies, Kolkata

2.     Das, C., Roy, M., and Mandal, P. (2016). Handloom cluster of India: A case study of Santipur Handloom Cluster. International Journal of Humanities and Social Science Intervention,5(1),27-35

3.     Deshbandhu, M., Kumar, A., and Rai, A.K. (2017). Female workforce Participation and Women Empowerment in Harayana. International Journal of Humanities and Social Science, 11(4), 1030-1035.

4.     Government of India (2011). District Census Handbook, Primary Census, Abstract, Nadia, New Delhi: Government of India. Retrieved from censusindia.gov.in on 25.02.2018.

5.     Klasen, S., AND Pieters. J, (2015). What explain the stagnation of female labour force participation in urban India? World Bank Economic Review

6.     Mahata, D., Kumara, A., and Rai, A.K. (2017). Female Work Force Participation and Women Empowerment in Haryana. World Academy of Science, Engineering and Technology International Journal of Humanities and Social Sciences, 11(4), 1030-1035

7.     Mammen, K., and C. Paxson. 2000. “Women’s Work and Economic Development.” Journal ofEconomic Perspectives 14 (4): 141–64.

8.     Narayan, L. (2016). Womens labour force participation in Harayana: A Disaggregated Analysis. Impact Journal of Interdisciplinary Research, 2(11), 1076-1085.

 

 

 

 

Received on 17.11.2018       Modified on 28.11.2018

Accepted on 10.12.2018      ©AandV Publications All right reserved

Res.  J. Humanities and Social Sciences. 2019; 10(1): 145-150.

DOI: 10.5958/2321-5828.2019.00024.X