Block-wise Developmental Scenario of Bankura District, West Bengal

 

Papiya Manna*, Dr. Tapas Mistri

Department of Geography, The University of Burdwan, Burdwan, West Bengal, India

 

ABSTRACT:

Development is a dynamic concept and it changes through time and over spaces. It is mostly inegalitarian and all spaces are not properly equipped for development. Regional disparity is inevitable and it’s part and parcel of developmental studies of developing countries. Identification of developed or backward region within a spatial unit is one of the most important issues of targated development. It aims to reduce regional imbalance and helps to achieve regional development. Spatial variation in terms of socio-cultural, economic, health or infrastructural aspects are perpetual pheneomena of Indian history whether it’s from colonial rules or to the present context. Present paper tries to identify regional variation in various aspects at the block level. Bankura district which is quite distinct physiographically and culturally and also one of the western district of West Bengal has been chosen as study area. Block level analysis of developmental parameters will help planners to endow resourses for further development of the less developed blocks. Analysing various aspects of development, Kotulpur, Bankura-I, Khatra, Barjora have been identified as developed blocks whereas blocks like Saltora, Ranibandh, Indpur, Gangajalghati are considered as less developed.

 

 

 

INTRODUCTION:

Development is a complex and multidimentional (Das, 2017)¹ as well as dynamic process. It changes through times and over spaces. It is the reflection of any region’s well being. But all places are not always suceptible to development as it’s depends on the sustainability and required acceptability of the place. Variation in those aspects will lead to regional disparity. Regional variation differentiate each place from other and make the difference among spaces. This phenomena helps to add uniqueness to a region. Famous French geographer Vidal d La Blache once termed them as ‘pays’(Dikshit, 2006)². Every place is not equipped with all best chateristics like physical, social, economic and cultural.

 

Some attributes sometimes come out prominently with positive input while those become negative in other places and creates regional variations. At the same time it is not possible to provide all facilities and services to all places as it may be due to ability or inability to accept or faulty governmental planning or may be other causes. In developmental studies, regional development is a very important section of academic arena that deals with consensual and hidden factors of development and non-development. But the main aims of developmental studies are to formulate way out to reduce regional imbalances.

 

The present study is focusing on the block wise developemntal vatiations of Bankura District, one of the developmentally lagging district of West Bengal. Bankura district with its distinct physiographical subdivision, economically and infrastrucutrally is not sound. More or less soil is unproductive and economy is predominantly dependant on small scale industries and agro based industries. So, from developmental perspective it is very important to identify the blocks which are developed and which are lagging based on some parameters because it will helps government and planners to focus into the lacking sides of the district. Developmental conditions have been shown mainly through socio-economic parameters like demography, economy, educational facilities, infrastructural facilities and health facilities. Composite indices have been calculated to present conditions of development. PCA has been calculated to highlight on the factors to be needed immediate attention.

 

LITERATURE REVIEW:

Development is must be inegalitarian as its very hard to develop every place simultaneously (Raychaudhuri & Haldar, 2009)³. Spatial vatiation must exists in all spheres. Regional disparity are is and parcel of developmental studies of developing countries. Identification of developed or backward region within a spatial unit is one of the most important issues of planned development (Dinda & Ghosh, 2015)⁴. It aims to reduce regional imbalance and helps to achieve regional development. Spatial variation in terms of sociao-cultural, economic, health or infrastructural aspects are perpetual pheneomena of Indian history since colonial rules or to the present context.

 

Development is not a simple process rather it’s a mixture of various complex facts and pheneomenon. Thus development is amulgation of numerous attributes like economy, infrastructure, society, people, well being of people, choices of people, freedom the people enjoys irrespective of class, caste, sex and many more issues do come under the shade of development. These attributes create space-wise variation of development. Das (2017) for example focusd on district-wise variation in social infrastructure in Assam. He also stresses on the fact that in many cases we generally define development by development of economy (Shah 2003)⁵ totally neglecting the human and wellbeing development. If we look at the developmental scenerio of India, unhelathy, unequal and lopsided developmental will be seen all over the space. There are widespread inter-regional disparities prevailing in our country (Nair, 2004)⁶. Sam and Chakma (2016)⁷ focused on blocked wise regional disparity of newly formed district of West Bengal, Alipurduar. (Development for sure is human centric and it’s the richness of people rather richness of economics only (Human Development Report, 2016)⁸. Many scholars and researchers have taken the matter of regional diversities very seriously and many great works have come out from their writings.

 

The study Area: Bankura (23º14' 00"N and 87º 04' 00"E) the land of “Malla” kingdom; terracota, baluchari, swarnachari is one of the 23^rd districts of West Bengal.

 

 

Figure 1: Location Map of the study area

It is a part of Rarh Bengal. Bankura acts as a ‘connecting link between the plains of Bengal in the east and Chhotanagpur plateau in the west’ (District Census Handbook, 2011)⁹. This district historically and culturally and in tradition, quite rich. Bankura has three sub-divisions with distinct features: they are Bankura Sadar Sub-division, Bishnupur Sub-division and Khatra Sub-division.

 

OBJECTIVES:

The present study aims to unravel the following objectives:

·         To identify developed and less developed blocks based on existing demographic, economic, educational, infrastructural and health facilities .

·         To analyse the factors responsible for block wise inequalities in Bankura district.

 

METHODOLOGY:

Development is dependent on various aspects. It is reflected through demographic, educational, infrastructural, health and economic conditions of any space. In this paper mentioned parameters are furthur divided into numerous sub-parameter to get the real scenerio of the concerned area.

 

 

The raw data in sub-variables form have mentioned in respective tables, are converted in to unit free normalised form to get relative position of each block in respect to development. The following formula is used to makes normalization of variables into a unit free form.

Xt-Xmin

Li=-------------------

Xamx - Xmin

Where 0 ≤ L_i ≤ 1

L_i is standard normalised variable or index of i^th variable.

 

Principal Componant Analysis (PCA):

PCA is a method to convert a large number of possibly interrelated variables into a set of values of linearly uncorrelated variables (Kothari & Garg 2016)¹⁰.

Z_j = a_j1X₁ + aj₂X₂+ + aj₃X_3…. + + aj_nX_n (Where X represents 1, 2, 3,…..n)

 

Social Condition:

Development is multi-disciplinery concept. In developmental economics we very often discuss about social development and this total pheneomena is dependent on human being. Human being’s own level of development is many a times is dependent on which region they are living. Thus space value always matters. To focus on social development of Bankura the following parameters have been selected (Table: 1).

Table 1: List of Variables to focus on Social Condition

Variables	Sub-variables	Data Source
Social	X1. Population density	Primary Census Abstract (PCA), 2011
	X2. Sex ratio
	X3. 0-6 Sex ratio
	X4. Literacy rate (%)
	X5. Female literacy rate (%)
	X6. Male female literacy gap

Composite index has been calculated from the sub-variables as mentioned in table: 1 and result is shown in figure 2. The figure shows that in terms of social conditions, blocks like Kotulpur, Indus of Bishnupur sub-divison has achieved very high status and value of composite index is above 0.713, shading of colour is very much darker. In Bankura-I, Bankura-II of Bankura Sadar and Bishnupur, Joypur of Bishnupur sub-division and Sarenga block of Khatra sub-division, value of composite index are highly developoed. Mejia, Saltora, Gangajalghati of sadar sub-division and Ranibandh, Hirabandh and Indpur of Khatra sub-division are underdeveloped blocks in terms of social condition. Thus block of Bishnpur sub-division are quite developed. Population density is high in Bankura-I, Bankura-II, Kotulpur, Indus, Joypur, Bishnupur, Patrasayer blocks whereas Ranibandh, Taldangra, Saltora, Chhatna, Hirabandh, Simlapal are blocks where population density is quite low. In Sarenga, Bishnupur, Khatra, Chhatna, Kotulpur sex ratio is highest exceeding national and state average (940 and 950 females/ 1000 males). Mejia, Ranibandh blocks have sex ratio below the national average whereas sex ration of Gangajalghati, Taldangra, Sonamukhi, Barjora blocks are near about national average. 0-6 sex ratio is high in Taldangra, kotulpur, Bishnupur but Gangajalghati, Raipur, Bakura-II are lagging behind in this aspect. Literacy rate is very important attribute that determine the level of social development. Again most blocks of Bishnupur sub-divison have shown highest literacy Figure 2: Social

 

Condition, Bankura:

 rate as well as female literacy too and Kotulpur has achieved leading position in literacy rate (78 %) and female literacy (70.70 %). Analysis of various variables are done with PCA to get idea about dominating variables among multi variables selected.

 

Table 2: Correlation Matrix on Social Condition

Variables	X1	X2	X3	X4	X5	X6
X1	1	0.356	0.009	0.542	0.632	-0.538
X2		1	0.173	0.219	0.284	-0.337
X3			1	0.036	0.129	-0.348
X4				1	0.959	-0.487
X5					1	-0.707
X6						1

 

From the selected sub-variables of social condition, correaltion matrix has been derived from SPSS software (Table 2).

 

 

Table 3: Factors Dominating the Block-wise Nature of Development of Social Condition by PCA

Variance Explained                                    Variables	X1	X2	X3	X4	X5	X6
PC-1 (52.66%)	0.772	0.484	0.243	0.849	0.946	-0.808
PC-2 (19.00 %)	-0.175	0.367	0.869	-0.329	-0.195	-0.259

Calculation by PCA

 

 

Figure 3: Quadrantal Position of Blocks (Social Conditions)

 

First Principal Componant (PC-1) is the linear combination of variables (X) and that has mamimum variance. Here the variance explained in PC-1 is 52.66% (Table 3) where all most all variables except X₆ (Male female literacy gap). Female literacy rate, population density are showing sontrongly positive loadings where as attention must focus on the issue of male female litercy rate. The gap is very wide at the blocks like Khatra, Indpur, Saltora and Ranibandh where as Bishnupur subidivision is quite developed in this aspect. 19% varianc is explained by PC-2. Child sex ratio dominating in this loading. Child sex ratio of Ranibandh block is even lower than national average (914) and Taldangra, Saltora, Chhatna, Hirbandh, Simlapal, Raipur and Sarenga blocks experiencing child sex ratio below the state average of (950). Sex wise literacy gap and child sx ratio and its spatial variation is very concerning issues and government must focus on the latent factors responsible behind the phenomena. In order to focus on regional disparity of social conditions, Prince Score:1 and Prince Score:2 have been calculated from PC-1 and PC-2. Spatial location of blocks based on quadrant distribution on social conditions have shown at figure 3. Saltora block is located at the quadrantal position of negative development (-, -). Gangajalghati, Bankura-II, Raipur, Indpur and Mejia blocks are moderately developed and attentions must put on these blocks along with Saltora block obviously.

 

 

 

Figure 4: Educational Facilities

 

Educational Condition:

We can consider any place as developed if the place has proper educational facilities. To determine the educational faclities in blocks of Bankura, the following variables are selected (Table 4). Composite index form the selected varibles in pictural form has been shown in figure 4 and it is qite clear that Bankura-I has achieved leading postion as the value of composite index is more than 0.706. Composite index ranges within 0.533 to 0.705 in Bankura-II, Bishnupur, Ranibandh and Hirabandh. Lowest educational facilities are found in blocks like Gangajalghati, Indpur, Onda, Patrasayer, Indus, Kotulpur. Bankura-I, being district headquarter has maximum numbers of schools (primary, middle, HS); colleges (degree and techincal), public libraries, mass educational centres and free reading rooms. Population served by number of primary schools is highest in Bankura-I, Bankura-II; Chhatna, Ranibandh, Simlapal. Most of the blocks of Bishnupur sub-division, Mejia, Barjora, Saltora, population is served by lesser numbers of primary schools. There are lesser number of middle schools serve the population of Hirabandh, Bankura-II, Gangajalghati, Sarenga               ; on the other side Barjora, Khatra, Ranibandh, Simlapal, Mejia, Kotulpur have good numbers. High and Higher secondary schools are quite less in number in blocks like Raipur, Sonamukhi, Ranibandh, Saltora, Mejia, Simlapal, Hirabandh and Onda blocks. Schools makes the base of intellectual sphere, so planners must focus to maximum number of schools in each blocks that every section of the society must access educational institutions. In many blocks of Bankura like Mejia, Simlapal, Hirabandh, Onda, Kotulpur do not have degree and technical colleges. So this is barrier in educational infructural development.

 

Table 4: List of Variables to focus on Educational Facilities

Variable	Sub-variables	Data Source
	X7. No. of primary schools/ 10,000 population	District Statistical Handbook (DSH), Bankura 2016
	X8. No. of middle schools/ 10,000 population
	X9. No. of high schools/ 10,000 population
Educational	X10. No. of HS schools/ 10,000 population
Facilities	X11. No of colleges/ 10000 population
	X12. No. of public library/ 10,000 population
	X13. No. mass literacy centres/ 10,000 population
	X14. No. of Free reading rooms/ 10,000 population

 

 

Table 5: Correlation Matrix on Educational Facilities

Variables	X7	X8	X9	X10	X11	X12	X13	X14
X7	1	-0.137	0.357	0.639	0.417	0.403	0.544	0.368
X8		1	-0.332	-0.317	-0.145	-0.132	0.093	-0.209
X9			1	0.253	0.313	0.427	0.086	0.348
X10				1	0.509	0.49	0.153	0.459
X11					1	0.389	0.052	0.41
X12						1	0.341	0.971
X13							1	0.316
X14								1

From the seleced variables, again co-relation matrix has been calculated to to PCA.

 

Table 6: Factors Dominating the Block-wise Development of Educational Facilities by PCA

Variance  Explained                                     Variables	X7	X8	X9	X10	X11	X12	X13	X14
PC-1 (28.2%)	0.738	-0.340	0.570	0.750	0.632	0.846	0.439	0.828
PC-2 (19.9 %)	0.257	0.684	-0.348	-0.150	-0.214	0.122	0.730	0.080

Extraction Method: Principal Component Analysis.

 

Two components have been extraced (table 6). These two component have explained 48% of the variables. In the first primary school has shown dominent role. Distribution of free reading rooms, public library and primary school are well distributed. In the second component, middle schools influence is quite moderate. So government must focus on establishment of middle and high and higher secondery schools. As school builds the platform of the future of society.

 

Infrasructural Facilities:

Generally Infrastructure is considered as very important to social and economic developemnt (Nair, 2004). Relative position of infrastructural facilities is very good indicator to determine the regional diversity. Selected variables to determine infrastructural development are as follows in table 7:

 

Table 7: List of Variables to focus on Infrastructural Facilities

Variable	Sub-variables	Data Source
	X15. Distance of the nearest railway station from block HQ	District Statistical Handbook (DSH), Bankura 2016
	X16. No. of originating or terminating bus routes
	X17. Road density (km/km2)
Infrastructural	X18. Electricity
Facilities	X19. Intensity of net irrigation
	X20. No. of Banks/ 10,000 population
	X21. % household having drinking water within premise
	X22. No. of Seed stores/ 10,000 population

 

Composite index (see figure 5) reveals the disparity of infrastructure in various blocks of Bankura district. Kotulpur, Sarenga, Raipur blocks are developed in terms of infrastructural facilities (> 0.610). From infrastructual facilities, Saltora, Mejia, Gangajalghati, Indpur and Onda are least developed blocks of Bankura. Railway is one of very important mode of communication and measure of infrastrucutal development. In terms passengers and freight trasportation its role is very important. Distance of nearest railway station form block headquater is lowest in Sonamukhi, Joypur, Bishnupur, Onda, Parasayer, Chhatna, Indus, Bankura-II, and Bankura-I. Raipur, Ranibandh, Khatra, Hirabandh, Simlapal and Sarenga blocks nearest raiway station is very far away. Services in terms of originating and terminating bus routes are highest in Bishnupur sub-division except Indus and Joypur. Raipur, Chhatna, Khatra blocks having the highest numbers of originating and terminating bus routes. Road density is one of the major key indicators of development. In Bankura, Raipur, Khatra, Chhatna, Kotulpur and Taldangra, road density per km² is good. But government must focus on the connectivity of blocks like Gangajalghati, Sonamukhi, Bankura-II, Barjora and Joypur blocks. Thus Raipur is quite developed in terms of train and bus services. Number of banks both commercial and gramin to provide services a certain number of population is quite less in Sonamukhi, Indpur, Joypur, Mejia blocks. Khatra, Barjora, Simlapal, Chhatna and Bankura-I blocks are having good numbers of banks to render servives a certain population. Government must put attention supply electricty particularly to the blocks of Ranibandh, Saltora, Hirabandh, Indpur and Khatra blocks (see table 8).

 

 

Figure 5: Infratructural Facilities.

 

 

Table 8: Correlation Matrix on Infrastructural Condition

Variables	X15.	X16.	X17.	X18.	X19.	X20.	X21.
X15.	1.000	.003	.539	-.310	-.065	.230	-.407
X16.		1.000	.141	-.002	.229	.118	.356
X17.			1.000	-.081	.117	.468	-.345
X18.				1.000	.595	.142	.521
X19.					1.000	-.132	.516
X20.						1.000	-.058
X21.							1.000

 

Table 9: Factors Dominating the Block-wise Nature of Development of Infrastructuralal Condition by PCA

Variance Explained                       Variables	X15	X16	X17	X18	X19	X20	X21
PC-1 (35.00%)	- 0.647	0.240	-0.494	0.713	0.648	-0.266	0.855
PC-2 (25.21 %)	0.445	0.461	0.748	0.354	0.494	0.631	0.167
PC-2 (14.40 %)	0.03	0.815	-0.079	-0.499	-0.108	-0.206	0.181

 

Extraction Method:

Principal Component Analysis.

In the first PCA, number of seed stores and electricity distribution has shown dominant role among all variables. For agricultural development seed stores are determined as a very important variable and electricity also. Bus connectivity is showing negative loading in the first PCA but in the third PCA it is 0.815. Bankura is quite less developed in terms of railway connection. So from that perspective, government must focus on the railway connectivity in the district and this step in long term will upgrade the economy of the district also.

 

 

Figure 6: Location of Blocks based on Infrastructural Development

 

Blocks of Bishnupur sub-division are leading in terms of infrastructure in the district (figure 6).

 

Health Facilities:

Access to health care facilities and availability of suitable environment to protect health are one of the very important issues to determine regional variation in health services. Here selected variables are divided into preventive and curative measures. Variables are as follows at table 10:

 

Table 10: List of Variables to focus on Health Facilities

	Curative	District Statistical Handbook, Bankura, 2016
Health Facilities	X23. Medical Institutions/ 10,000 population
	X24. Doctors/ 10,000 population
	X25. Beds/ 1000 population
	X26. Primary health centres/ 10,000 population
	Preventive	Census, 2011
	X27. Households having latrine facilities (%)
	X28. Households having separate bathrooms (%)
	X29. Households having safe drinking water

 

Result of composite index (see figure 7) shows Bankura-I and Kotulpur blocks have highest health facilities (> 0.601), whereas Onda, Gangajalghati, Indpur blocks are laggers. Allmost all blocks of Bishnupur have more or less moderately good health facilities. In Bankura Sadar sub-division, Mejia, Barjora, Bankura-II blocks also moderate condition of health facilities. Khatra sub-division are quite less developed in this regard (0.271- 0.430). Availability of doctors and beds per population are in very good numbers in Bankura-I, bankura-II, Bishnupur and Khatra blocks. Patrasayer, Sonamukhi, Joypur Indus, Onda blocks where numer of doctors and beds per certain population is quite low. Thus government must focus attention at these blocks. Number of medical institutions per certain population are higher in two Bankura, Sonamukhi, Bishnupur and Kotulpur blocks. In Patrasayer, Raipur, Indus, Onda and Khatra the number of medical institutions are quite less. In blocks Primary Health Centres play a very important role to provide primary health care services. Primary Health Centres are less in numbers per certain population in Khatra, Sarenga, Bankura-II, Patrasayer, Gangajalghati and Raipur blocks. Households enjoying latrine facilities and separate bathrooms in terms of preventive health, Bishnupur sub-division has secured good postion, whereas Hirabandh, Ranibandh, Saltora, Raipur and Indpur blocks have shown worse conditions. Access to safe drinking water is quite less in Hirabandh,

Indpur, Onda, raipur, Sonamukhi blocks. Thus higher authorities must put their kind attention to the facts like giving assistance to build up latrine, bathrooms and provide treated drinking water to the people to ensure good health for the population.

 

Table 11: Correlation Matrix on Health Condition

Variables	X23	X24	X25	X26	X27	X28	X29
X23	1	-0.139	0.768	-0.068	0.003	0.034	0.338
X24		1	0.092	-0.272	-0.225	-0.174	0.365
X25			1	-0.174	-0.062	-0.090	0.631
X26				1	0.959	-0.034	-0.338
X27					1	0.951	0.231
X28						1	0.266
X29							1

 

Extraction Method: Principal Component Analysis.

From the selected sub-variables of social condition, correaltion matrix has been derived from SPSS software (Table 11).

 

Extraction Method: Principal Component Analysis.

In terms of health condition, two PCA has explained about 60% of the total variance. In first PCA, primary health centres and households consuming safe drinking water are dominating and in second PCA latrine and batrooms facilities are very strongly influencing the scenerio. Based on the prince scrores extracted PC 1 and PC 2, quadrant distribution of the blocks have been shown and it reveals that Bankura-II, Kotulpur, Indus, Barjora are positioned in good location Bankura-I (+, -) is positioned relatively bad condition as preventive measures are not positively coorelated in this case. Blocks like Hirabandh. Ranibandh. Onda, Indpur and Taldangra are situated at the upper left postion of quadrant (-, +) where health conditions both curative and preventive measures are not fitting well (figure 8)

 

 

Figure 7: Health Facilities.

 

 

 

 

 

Table 12: Factors Dominating the Block-wise Nature of Development of Health Condition by PCA

Variance Explained                              Variables	X23	X24	X25	X26	X27	X28	X29
PC-1 (33.23%)	0.721	0.225	0.862	-0.397	0.228	0.275	0.853
PC-2 (29.67 %)	-0.113	-0.406	-0.269	0.235	0.955	0.927	0.30

 

 

 

Figure 8:Location of Blocks in Health Facilities   

 

Economic Scenario:

Economic condition of any place is one of the most important sides to determine the level of development of any area. To measure the economic strength of Bankura district, the following sub-variables are selected (Table 13). Concentration of workers both in farm and non-farm sector to look at workers’ nature, distribution of variatios servives and individual’s assets will focus to some extent the economic condition of any place.

 

After analysing the data by composite index (see figure 9), of blocks like Barjora, Bankura-II, Kotulpur and Khatra (composite value >0.538) have shown a good economic condition as a whole. Chhatna, Bankura-I, Indpur, Raipur, Sarenga have shown the value of composite index between 0.364 to 0.450. Saltora, Mejia, Gangajalghati, Ranibandhand Indus blocks are the block which are quite less developed in terms of economic variables.

 

Table 13: List of Variables to focus on Economic Scenario

Variables	Sub-variables	Data Source
Economic Scenario	X30. Main workers (%)	PCA, 2011
	X31. Farming population (%)
	X32. Non-farm population (%)
	X33. No. of fare price shops/10000 population	DSH, Bankura, 2017
	X34. No. of co-operative societies/10000 population
	X35. Households using banking services (%)	Census, 2011
	X36. Assets availability
	X37. Computer or laptops with internet	DSH, Bankura, 2016

 

In Sonamukhi, Patrasayer, Kotulpur blocks percentage of main workers is quite high, people engage in agriculture is high at Raipur (82% of total workers), Ranibandh, Sarenga, Hirabandh, Taldangra, Sonamukhi, Patrasayer, Indus, and Simlapal (74% of total wokers) blocks. Non farm population is concentrated at Mejia (55 %), Bankura-II, Bankura-I, Barjora, Saltora, Gangajalghati, Chhatna, Bishnupur and Kotulpur blocks where agriculture is secondary activity and other activities like industries, services are high. Households using banking services is variable that reflects economic strenght of the individuals of any area. In Chhatna block people using banking facilities is quite high (68 % of the total population). Chhatna has a very old and historical background, it is the place where in early days printing press were existed with a quite good infrastructural development. Raipur, Kotulpur, Joypur, Bishnupur also shows good results. But antonishingly Bankura-I block inspite of the district centre where people using banking services is quite less and followed by Ranibandh, Mejia, Indus, Gangajalghati and Patrasayer blocks. Assets availability is quite less in Hirbandh, Ranibandh, Saltora, Raipur, Sonamukhi blocks.

 

 

Figure 9: Economic Condition, Bankura

 

 

Table 14: Factors Dominating the Block-wise Nature of Development of Economic Condition by PCA

 

From table 14, it is clear that there are three principal components have been extracted. These three components have explained 83% of the total variance. Households’s assects availability and households using computer with internet influencing strongly in the first PCA (0.927 and ).814). Fare price shops influence strongly negative in the second PCA (explained 25.69% of total variance) means services by fare price shops are not in proper proportion and government must focus to in increasing the facility in all blocks. In the third PCA, co-operative societies influence is very strong (0.858).

 

Overall Development Scenerio:

thus after amulgamating all factors which are responsible for development like social, educational, infrastructural, health and economic scenerio, a total copmosite index has been calculated and the result is shown at figure 10. Value of composite index is high at Kotulpur (0.627) and Bankura-I (0.62) and in the figure 8 these blockshave shown by darker colour. Saltora, Gangajalghati, Indpur, Ranibandh, Onda and Hirabandh blocks are less developed in terms of the selected indicators. The north-western and western blocks of Bankura district are less developed whereas Bishnupur sub-division is developed in many aspects. In Khatra sub-division of the district, Indpur, Ranibandh and Hirbandh blocks are less developed in terms of either social parameters or educational or infrastructural or health facilities or economic conditions. Variation in terms of physiacl properties do exists in all areas. It is the role of planner and development agencies not to let this physial differences into developemtal inequalities. They have to find out the reasons behind the fact why some blocks are gaining or achieving all sorts of developed environment and why other blocks are laggging behind. In Bankura, blocks like Saltora, Mejia, Gangajalghati inspite of being located nearner to Asansol Durgapur Industrial areas, level of development is quite less though this areas have shown improvement in non-agricultural activities but still the overall development is quite less. Likewise southern blocks are quite less developed. Connectivity is one of the most important indicators to be focus in this district by government. Primary Health Centres must be upgraded with proper iquipments in each blocks that people must get the primary health care services.

 

 

Figure 10: Development scenerio, Bankura

 

 

CONCLUSION:

Every place has its own characteristices. There may some positive attributes and some negative attributes and some may be in between these two. But it is the culture of human being spread the good and eradicate the loop holes. Some times government does the planning things but the implementations remain untouched. The developed areas becoming more and more developed day by day but the lagger areas remain poor in terms of development. From these, regional disparities widen. Thus government along with people active awareness and participation will help to reduce the anomalies and try to lessen the gap between the extremes.

 

REFERENCE:

1.        Das, B. (2017). Social infrastructure in Assam: A stydy of its inter district disparities. RAY: International Journal of Multidisciplinary Studies, 2(1),1-18.

2.        Dikshit, D. R. (2006). Geographical Thought: A comprehensive history of ideas. PHI Publishers, ISBN: 8120311825

3.        Raychaudhuri, A. & Haldar, k. S. (2009). An investigation into the inter-district disparity in West Bengal, 1991-2005, Economic and political weekly, 26, 27 (44), 258-263

4.        Dinda, S. & D, Ghosh. (2015). A search for backward blocks in burdwan district, west bengal: an application of composite development index. Munich Personal RePEc Archive. Online at https://mpra.ub.uni-muenchen.de/67158/

5.        Shah, A. S. R. (2003). Bridging the economic divide within countries: a scorecard on the performance of regional policies in reducing regional income disparities. World Development, 31(8), 1421-1441

6.        Nair, G. R. K. (2004). Economic reforms and regional disparities in economic and social development in India. Report of a Research Project funded by the SER Division of the Planning Commission of the Government of India.

7.        Sam, K. and Chakma, N. (2016). An inter-block level analysis of regional disparity in the youngest alipurduar district of west bengal. Space and Culture India, 3(3), 10-21. DOI: 10.20896/saci.v%vi%i.159

8.        Human development report, Human development for everyone, (2016). United Nations Development Programme. Retrieved from hdr.undp.org/sites/default/files/2016_human_development_report.pdf

9.        Census of India, (2011). Registrar General of India, Government of India.

10.     Kothari, C. R. and Garg, G. (2016). Research methodology methods and techniques. New Age International Publishers, New Delhi. ISBN: 978-81-224-363-5

 

 

 

 

 

Received on 14.04.2018          Modified on 11.05.2018

Accepted on 22.06.2018      ©A&V Publications All right reserved