Research Methodology

Transcription

1 CHAPTER III Research Methodology In the present study, an attempt has been made to study the role of women in agriculture sector of Punjab. This study was based on the primary data collected from women of farm families of Punjab with the help of a well drafted, structured and pretested questionnaire (Appendix-I). Research Question In order to develop sound theoretical framework for this research work, a comprehensive review of literature was undertaken. The review of literature revealed that much work was not done in this field. Punjab had witnessed a revolution in the field of education of rural people, especially women, and significant changes had occurred in employment of farm labour and participation of women in agriculture sector. There has been an improvement in the literacy levels, communication, agricultural practices and other infrastructural systems. The government has been giving due importance and priority to rural development which acted as a fillip for national development. The basic research question was: What is the extent of participation of women and their effectiveness in agriculture sector? It was also decided to study the role of women in decision making in agriculture sector and factors affecting the same. Universe of Study Punjab is the one of the smallest states of India representing 1.5 percent geographical area and 2.5 percent population of the country. The latitudinal and longitudinal extent of the state is from N to E to E. It is almost triangular in shape with tip pointing to the north. The geographical area of the state is Sq kilometres and its population lives in villages and 108 towns. For better administration of the state, it has been divided into three divisions comprising 20 districts, 117 blocks and 71 tehsils. The agricultural resource base of the Punjab varied widely from one corner to the other. This was visible from great disparity in agricultural development and economic growth of different parts of the state. In order to plan for the harmonious development, it 47

2 was essential to pinpoint the agricultural problems and potentials of the different areas. This was possible when spatial variation in the resource bases in terms of climate, physiography, soil type and underground water reservoir were thoroughly assessed. Sampling Design As the extent of participation of women and their effectiveness in agriculture sector, role of women in decision making in agriculture sector and the factors responsible for the same were to be accessed, we carried out all the investigations in an appropriate area which represented the state of Punjab in a comprehensive manner and at the same time was suitable for carrying out such a research. On the basis of variations in physiography, under ground quality and quantity of water, amount of rainfall and moisture index, the Punjab was divisible into six regions (Deptt. of Agricultural Meteorology, PAU, Ludhiana) viz. Sub-Mountain Undulating Region, Undulating Plain Region, Western Plain Region, Western Region, Flood Plain Region and Central Plain Region (which has been taken purposively for the present study). Five of these regions were further divisible on the basis of the variations in soil characteristic. The regions thus delineated on the basis of these criteria were homogeneous spatial units in terms of agricultural problems and potentials, hence provided a sound base in the planning for agricultural development instead of the districts, the boundaries of which cut across the various agro-climatic regions. The six Agro-Climatic Regions are discussed as below: SUB-MOUNTAIN UNDULATING REGION This region extends along the eastern borders of the state and is 10 to 20 kilometer in width except in Gurdaspur district where it is much wider. This region covers nearly 4800 square kilometres, where it is about 9.5 percent of the total area of the state. Bamial, Narot Jaimal Singh, Pathankot and Dharklan blocks of Gurdaspur district, eastern half of Mukerian, Talwara, eastern halves of Dasuya, Bhunga, Hoshiarpur I and Hoshiarpur II, Mahilpur, Garhshankar and entire Balachaur and Saroya blocks of Hoshiarpur district, Dera Bassi block of Patiala district and Nurpur Bedi, Anandpur Sahib, Ropar, Sialba Majri and Kharar blocks of Ropar district fall in this region. 48

3 The western limits of the region coincide approximately with 300-metre contour. The slope of the land surface is more than 15 meter per kilometer near the Shiwalik hills and decreases to about 8 meter per kilometer towards its western limits. The distinctive character of the terrain in this region is that it is badly dissected by innumerable seasonal streams. Hundreds of streams which originated in the Shiwalik hills have produced a very uneven topography. The upper courses of the seasonal streams are covered with small pebbles and coarse sand, whereas a few kilometer away from the Shiwalik hills, the beds are covered with pure sand. Steep gradient, bare-land surface and torrential and heavier rains during the monsoons have created serious problems of soil erosion. UNDULATING PLAIN REGION This narrow and transitional region runs parallel to the sub-mountain undulating region and is 15 to 30 kilometer in width. This region covers about 4600 sq. kilometres of land which represent about 9 percent area of the Punjab. It includes Dinanagar, Gurdaspur, Kalanaur, Dhariwal, Kahnuwan and eastern Hargobindpur blocks of Gurdaspur district (excluding their flood plain areas); western parts of Mukerian and Dasuya, whole of Tanda, western half of Bhunga, Hoshiarpur I, western parts of Hoshiarpur II, western parts of Mahilpur and Garshankar blocks of Hoshiarpur district; Chamkaur Sahib block of Ropar district; Machhiwara block of Ludhiana and Bassi Pathana, Rajpura and Ghanaur blocks (except the flood plain of the Ghaggar river) of Patiala district. The height of this region varies between 260 and 300 meters above sea level. It has all the topographical characteristics of the region due east but in a moderate form. The number of streams is less numerous. The slope of the land is considerable but smaller than the eastern region. Soil erosion did take place but is less severe as compared to the first region. WESTERN PLAIN REGION This region lies between the central flat plain on the east and the plain with sand dunes in the extreme west. It covers about 9500 sq. kilometer representing nearly 19 percent area of the state. 49

4 Patti, Bhikhiwind and Valtoha blocks of Amritsar district; Zira, Ferozepur and Ghall Khurd blocks of Ferozepur district; Faridkot, Moga I, Moga II, Nihal Singhwala and Bagha Purana blocks of Faridkot district; Rampura Phul, Mansa eastern part of Talwandi Sabo and Budhlada blocks of Bathinda districts and most of Barnala (except its eastern extension), western parts of Sangrur and Sunam blocks and entire Lehragaga block of Sangrur district are covered in this region. Flood plain areas of Sutlej river covering the adjoining parts of Patti Tehsil and Zira and Ferozepur blocks and a small area occupied by Ghaggar flood plain in Lehragaga block of Sangrur district in the extreme south are excluded from this region. It is transitional region where the flat topography merges gradually into a sand dune dotted land surface. The average height of the land varies between 200 and 250 meter above sea level. There is no stream or river worth mentioning which crosses through this region. The northern half is free from any topographical feature whereas towards the western margins in the southern half, sand dunes are quite frequent feature of the landscape. WESTERN REGION This region lies in the extreme southwest covering nearly 10,000 sq. kilometres representing nearly 19.5 percent area of the Punjab. Guru Har Sahai, Jalalabad and Fazlika blocks except the flood plain of river Sutlej, and Abohar and Khuyan Sarwar blocks of Ferozepur district; Muktsar, Kot Bhai, Malaut, Lambi and Kotkapura blocks of Faridkot district and Nathana, Bathinda, Sangat, most of Talwandi Sabo and Jhinir blocks of Bathinda district fall in this region. This is a conspicuous region of Punjab because of its dry climate and uneven topography. The major part of the region lies at a height of less than 200 meter above sea level and the land slopes less than one half of a metre in a kilometre. The entire region is dotted with sand dunes of varying dimensions. In general, the sand dunes are bigger in size in the southwest as compared to northeast. Wind erosion is mainly responsible to give this area its distinctive topography. Sand dunes are the result of strong and desiccating southwesterly winds which transport the huge clouds of sand from southwest. Many of the sand dunes have been levelled off with the intensification of 50

5 agriculture. Some of the sand dunes are, however, of shifting nature and remain bare of any vegetation or crop. FLOOD PLAIN REGION (Bet) This region has four separate components- the Ghaggar, the Sutlej, the Beas and the Ravi flood plains. The flood plains are locally known as the bet. Along the northern borders of Gurdaspur and Amritsar districts lies the flood plain of the Ravi and along the southern border of Patiala and Sangrur districts is the flood plain of the Ghaggar. The flood plains of the Beas and the Sutlej combine at Harike and make a common flood plain along the northern border of Ferozepur district. Area covered by the flood plains is about 3500 square kilometers which is about 7 percent of the total area of the Punjab. The width of the flood plains, on an average, is between 10 and 15 kilometers. It is relatively less in the sub-mountainous areas and increases to the maximum in the middle of the state. The boundaries of the flood plains are well defined by an abrupt depression in the land surface. The important characteristic of the flood plains is their almost flatness with nothing to break the monotony of longitudinal or the transverse profile. The only feature is some obliterated traces of interlocking channels of streams. During the heavy rains, flood plains are sometimes turned into virtual swamps. CENTRAL PLAIN REGION The central plain region was taken as the area for the present study as this region, 70 to 80 kilometres in width, cuts through the state from northwest to southeast. The region covers sq kilometers which represents about 36 percent of the total area of the Punjab. Whole of Amritsar district except the Bhikhiwind, Patti and Valtoha blocks and flood plains of river Ravi and Beas; Batala, Fatehgarh Churian, Dera Baba Nanak and Western part of Hargobindpur block of Gurdaspur districts (except the food plain parts in the block) entire district of Kapurthala (except the flood plain of Beas) Jullundur and Ludhiana districts (except Nawanshahar, Eastern Banga Machiwara block and flood plain areas of Sutlej river) Dharmkot block of Ferozepur district (expect flood plain area of 51

6 river Sutlej) Mahal Kalan, Malerkotla, Duri, Bhawanigarh, eastern parts of Barnala, Sangrur and Sunam blocks of Sangrur district and entire Sirhind, Nabha, Patiala, Bhunerheri and Samana block of Patiala district (except the flood plain of river Ghaggar) fall in this region. The general character of the land is homogenous. The slope of the land is very gentle. The region intercepted transversally by the flood plain of the Sutlej and Beas. The northern and Southern limits are also marked by the flood plains of the Ravi and Ghaggar respectively. The average height of this plain is 230 to 260 meter above sea level. The slope of the land decreases gradually from northeast to southwest where it diminishes to less than a meter per kilometer. The most important characteristic of the land surface lies on in its featurelessness except for few small pockets of sand bars. One such pocket lies in Dona area of Kapurthala and Nakodar, one stretching from Machhiwara to Khanna and the third in deep south in between Patiala and Samana. There are no traces of wind or water erosion. Underground Water The depth of water table varies from 2 to 20 meter below the ground surface. In blocks of Amritsar district (except Rayya, Jandiala and Khadur Sahib) Dera Baba Nanak and Batala of Gurdaspur district, the strata available from 50 metre to 65 metre depth contains medium to fine sand. The tubewells of 15 litres/sec capacity can be installed within the depth. In remaining blocks of Amritsar and Gurdaspur districts, whole of Kapurthala, Jullundhur and Ludhiana districts, Sirhind and Nabha block of Patiala district Ahmedgarh, Mlerkotla, Mehal Kalan, Dhuri blocks of Sangrur district, the tubewell yielding upto 15 litres/sec can be installed within 50 meter depth. The deeper tubewells with 30 litre/sec or more discharge can be installed successfully with 100 meter depth. In the remaining blocks of Patiala and Sangrur districts, tubewells can be installed a little deeper. The quality of water is good in this region, except in parts of Sangrur district and some pockets of other districts where it is marginal to good. The main problem is that of residual sodium carbonates. 52

7 Climate The mean maximum temperature recorded during the first fortnight of June is 42 C in the southern half and 41 C in the northern half, whereas the mean minimum temperature recorded during the month of January varies from 7 C in the southern parts to 4 C in northern parts of the region. The mean annual rainfall varies from 800 mm in the east to about 500 mm towards the western limits. In the southern half, 3 months of the rainy season receive a rainfall between 200 to 300 mm and one month between 50 and 100 mm. In the northern half, 2 months receive a rainfall between 200 to 300 mm, in 1 month the rainfall is less than 50 mm. In the rainy season period, June to September in the Southern-half, 12 weeks can be classified as humid to wet, 2 weeks intermediate dry to intermediate humid whereas 3 weeks are arid to dry. In the northern side, 13 weeks of the session are classified as humid to wet, 1 week inter humid and 3 weeks as arid to dry. Soils On the basis of the texture of the soil, this region is further sub-divided into two sub-regions. a) Central Plain Region-North: The sub region covers the Amritsar district (Excluding Bhikhiwind, Patti, and Valtoha blocks) and Dera Baba Nanak, Fathegarh churian, Batala and Western part of Hargobindpur block of Gurdaspur district. The western half of Kapurthala district along the river Beas also falls in this sub-region. The soils are medium to heavy in texture. Mild to serious alkali problem exists in the entire areas of Kapurthala district which fall in this subregion. Alkali problem of the similar magnitude also exists in the northern and western blocks of Amritsar district. Serve alkali problem exists in Dera Baba Nanak and Fathegarh Churian blocks of Gurdaspur district. b) Central Plain region-south: This sub-region extends from the eastern flood plain of river Beas upto southern limits of Patiala district. The soils of this sub-region are light to medium in texture. Mild to severe alkali problem exists in the area of Kapurthala, Patiala and Sangrur districts. A small pocket consisting of Sirhind, Rajpura, Ghanaur and Bhunerheri blocks has, however medium to heavy textured soils and are very close to the Southern component of the undulating 53

8 plain region. The areas of Sirhind and Patiala blocks are affected by severe alkali problem along with water logging. Cropping Pattern In kharif season, Paddy is the principal crop over a large part of the region. In addition to this, maize, groundnut and cotton desi occupy sizeable areas in Ludhiana, and Sangrur districts. Around Phagwara and Dhuri sugar factories, sugarcane crop occupies sizeable area. In rabi season, wheat is the dominant enterprise in the region. In addition, gram and barely occupy an important place in the cropping pattern of Sangrur district. Pear (Pathar Nakh) followed by guava are important fruit trees in some areas of Amritsar district. Grapes are grown in some localities in all the districts. Sample Size A sample of 300 female respondents from farm families was collected on the basis of multi-stage sampling. Three districts of Punjab Amritsar, Jalandhar and Ludhiana were selected for the study from the Central Plain Region of Punjab on the basis of convenience sampling. Two blocks from each district viz. Majitha and Tarsikka blocks from Amritsar district, Adampur and Bhogpur blocks from Jalandhar district and Doraha & Jagraon blocks from Ludhiana district were selected for the study on the basis of random sampling. Further, five villages from each block were selected using random sampling technique. Ten respondents, i.e. married female members of farming families with only one respondent per family, from each of the villages were selected using convenience sampling for the purpose of the study. The study was exploratory in nature. The break up of respondents, according to their age, education, occupation and income was as given below: Age wise distribution The respondents were classified into four age groups, viz., up to 30 years, more than 30 up to 40 years, more than 40 up to 50 years and above 50 years. Table 3.1 revealed the age wise distribution of the respondents. It revealed that 22.3% of the 54

9 respondents were up to the age of 30 years, 44.7% fell in the age group between years while 21.0% of the respondents were in the age group of years. Rest of the 12.0% of the respondents belonged to the age group of above 50 years. Table 3.1 Age Wise Distribution of Age (in years) Number of Percentage of Cumulative Percentage Up to Above Total Education Wise Distribution The respondents were also categorised on the basis of their educational qualifications. The educational qualification of the respondents was categorised into four categories, viz. up to matriculation, up to senior secondary, up to graduation and post Table 3.2 Education Wise Distribution of Education Level Number of Percentage of Cumulative Percentage Up to Matric Up to Sr. Secondary Up to Graduation Post graduation or above Total

10 graduation or above. Table 3.2 revealed that 50.3% of the respondents had an educational qualification of up to matric level. They were followed by another 26.0% of those having an educational qualification of up to senior secondary level. 18.0% of the total respondents were graduates followed by the remaining 5.7%, who were postgraduates or above. Thus, the majority of the respondents were found to be undergraduates. Occupation Wise Distribution of The occupational grouping was also done for the purpose of the study. The main objective of this distribution was to know the percentage of respondents engaged in any other occupation along with agriculture. Table 3.3 revealed that 79.3% of the respondents were not having any other occupation along with agriculture. Only 20.7% of the respondents were found to be involved in some other occupation along with agriculture. It meant that majority of the respondents were dependent on agriculture alone for their livelihood. Table 3.3 Any other occupation along with agriculture Response Number of Percentage of Cumulative Percentage Yes No Total Income Wise Distribution Apart from the above, the respondents were also classified on the basis of their annual family income into the five following categories viz. up to Rs. 1 lac, Rs. 1-2 lacs, Rs. 2-3 lacs, Rs. 3-5 lacs and more than Rs. 5 lacs. Table 3.4 revealed that 27.7% of the respondents were having a family income of more than Rs. 1 lac but less than Rs. 2 lacs per annum. They were followed by another 26.3% of those having their annual family income of less than Rs. 1 lac. Another 21.3% and 18.7% of the respondents were having 56

11 their annual family income of Rs. 2-3 lacs and Rs. 3-5 lacs respectively. Merely 6.0% of the respondents were having an annual family income of more than Rs. 5 lacs. Table 3.4 Income Wise Distribution of Annual Income (in Rs) Number of Percentage of Cumulative Percentage Upto 1 lac lacs lacs lacs More than 5 lacs Total Ownership of Agricultural Land The following discussion gave the details regarding the total land possession, land taken on lease, if any, total land under cultivation and number of crops cultivated per year by the families of the women respondents. Table 3.5 revealed that out of the total of 300 respondents, a total of 84 respondents i.e % of the total respondents had a land holding of not more than 5 acres. This meant that a total of 28.00% of the total respondent women belonged to marginal farming families. Further, 97 respondents, i.e % of the total respondents had a land holding of more than 5 acres but not more than 10 acres. This meant that 32.33% of the total respondent women belonged to small farming families % of the respondents, i.e. a total of 96 respondent women were found to be belonging to families having a land holding of more than 10 acres but not more than 20 acres. This meant that 32.00% of the respondent women belonged to medium farming families. 57

12 Table 3.5 Total Land Possession (in acres) Land Possession Number of Percentage of Up to More than Total Note: Figures in parentheses indicated percentages. Only 23 respondents, i.e. only a total of 7.67% of the total 300 respondents were from families having total land holding of more 20 acres. This meant that a total of only 7.67% of the total women respondents belonged to large farming families. Hence, most of the respondents belonged to marginal or small farming families. Type of Ownership of Agricultural Land Table 3.6(a) revealed the type of ownership of agricultural land. A total of 198, i.e. 66.0% of the total women respondents belonged to families that cultivated only their own agricultural land while 34.0% of them, i.e. 102 of the total of 300 belonged to families that, apart from their own land, cultivated agricultural land taken on lease also. It revealed the fact that majority of the respondents belonged to families that cultivated their own agricultural land only. Table 3.6 (a) Whether cultivating land taken on lease Response Number of Percentage of Cumulative Percentage Yes No Total

13 Table 3.6(b) revealed that out of the total farming families of women respondents, who owned agricultural land less than five acres, 59.5% of them were also cultivating land taken on lease whereas the rest of the 40.5% of farming families of respondent women had not taken any land on lease. Further, out of the total farming families of women respondents having land possession of 5 to 10 acres, only 34.0% of them had taken land on lease also whereas the rest of the 66.0% of these farming families of women respondents were cultivating only the land they possessed. As far as the families of respondents having total land possession of 10 to 20 acres were concerned, only 27.1% of these farming families were cultivating land taken on lease apart from their own land whereas the remaining 72.9% of them cultivated their own land only. Table 3.6 (b) Whether cultivating land taken on lease Land holding Yes No Total (in acres) Less than 5 acres 34 (40.5) 50 (59.5) 84 (100.0) 5-10 acres 33 (34.0) 64 (66.0) 97 (100.0) acres 26 (27.1) 70 (72.9) 96 (100.0) More than 20 acres 9 (39.1) 14 (60.9) 23 (100.0) Total 102 (34.0) 198 (66.0) 300 (100.0) Note: Figures in parentheses indicated percentages. 59

14 In case of those farming families of the respondents, who had a land possession of more than 20 acres, 39.1% of these had taken land on lease also whereas the rest of the 60.9% of these farming families of the respondents were cultivating their own land only. Land Taken on Lease The following discussion explained the amount of land taken on lease by the farming families of the women respondents. Table 3.7(a) revealed that 34.3% of the families of respondents had taken land between acres on lease followed by 28.4%, who had taken land on lease between 5-10 acres. 21.6% and 15.7% of the families of respondents had agricultural land less than 5 acres and above 20 acres taken on lease respectively. Table 3.7(a) Total land taken on Lease Area of land Number of Percentage of Cumulative Percentage Less than 5 acres acres acres More than 20 acres Total Table 3.7(b) gave the details of the distribution of amount of land taken on lease by the families of respondents with respect to their own land holding. The table revealed that out of total of 34 families of respondents who were 33.3% of total and had a land holding of less than 5 acres, 18 of these, i.e. 17.7% the total had taken a total of less than five acres of land on lease. Another 14, i.e. 13.7% families of respondents had taken land between 5-10 acres on lease. Rest of the 2, i.e. 1.9% of the total families of respondents had taken land between acres on lease. No family of any respondent had taken land above 20 acres on lease. 60

15 Table 3.7(b) Distribution of Having Land on Lease with respect to their Own Land Holding Land on lease (in acres) Land Possession (in Less than 5 acres 5-10 Acres acres More than 20 Acres acres) Less than 5 acres (17.7) (13.7) (1.9) (0.0) 5-10 acres (3.9) (10.8) (12.8) (4.9) acres (0.0) (2.9) (14.7) (7.9) More than 20 acres (0.0) (1.0) (4.9) (2.9) Total (21.6) (28.4) (34.3) (15.7) Note: Figures in parentheses indicated percentages. Total 34 (33.3) 33 (32.4) 26 (25.5) 9 (8.8) 102 (100.0) Out of the total of 33, i.e. 32.4% of the total families of respondents, who owned land between 5-10 acres, 4, i.e. 3.9% had taken less than 5 acres on lease. Another 11, i.e. 10.8% of the total had taken 5-10 acres on lease. Another 13, i.e. 12.8% had taken acres on lease. Rest of the 5 (4.9% of the total) had taken more than 20 acres of land on lease. Families of 26 respondents having land ownership of more than 10 acres but less than 20 acres constituted 25.5% of the total. Out of these, 15, i.e. 14.7% had taken acres of land on lease. Another 8, i.e. 7.9% of these had taken more than 20 acres on lease. Rest of the three of these families of the respondents, forming 2.9% of the total had taken 5-10 acres of land on lease. None of these families had taken less than 5 acres on lease. 61

16 Rest of the 9 farming families of the respondents constituted 8.8% of the total of those who had taken any land on lease. Out of these, 4.9%, numbering 5 had taken acres on lease. These were followed by another 3, i.e. 2.9% of the total who had taken more than 20 acres on lease. None of these farming families of respondents had taken less than five acres of land on lease. The overall analysis of the table 3.7(b) revealed that 34.3% of the families of respondents had leased land between acres followed by 28.4% of those who had leased land between 5-10 acres. 21.6% and 15.7% had leased lands less than 5 acres and more than 20 acres respectively. The above analysis also reveals that most of the marginal farming families of respondents having less than five acres of land possession had total land on lease not more than ten acres, though with a few exceptions which may be because of some other source of income like some other occupation of the spouses. Similarly, nearly 85% of the total farming families of respondents, having not more than 10 acres of land ownership, had taken on lease not more than 20 acres of land on lease. It is interesting to note that as much as 68.75% of the total farming families, who had taken more than 20 acres of land on lease, were those who had a land possession of more than at least 10 acres. This showed that the amount of land taken on lease by the farming families was directly proportional to their own land holdings as may be seen in the above table. This meant that as the buying power of these families increased with their land holdings, the amount of land taken by them on lease also increased. Total Land under Cultivation Table 3.8 gave a detailed account of the total land under cultivation by the farming families of the women respondents. 31.7% of the total of these had total cultivated land between 5 10 acres followed by 29.3% of those who had cultivated land of more than 10 acres but less than 20 acres. Another 19.7% had less than 5 acres of total land under cultivation. Rest of the 19.3% had more than 20 acres of land under cultivation. Thus majority, i.e. 61.0% of the farming families of the respondents had cultivated agricultural land between 5-20 acres. 62

17 Table 3.8 Total land under cultivation Number of Percentage of Cumulative Percentage Less than 5 acres acres acres More than 20 acres Total Number of Crops Cultivated per year Table 3.9 revealed the details regarding the number of crops being cultivated by the families of the respondents in a year. The findings revealed that all the families of the respondents grew more than one crop in a year. Table 3.9 Number of crops cultivated in a year Number of crops Cultivated Number of Percentage of Cumulative Percentage One Two More than two Total Further, the table explained that 74.3% of the total families of the respondents cultivated two crops in a year while the rest of 25.7% of them cultivated more than two crops in a year. The difference can be attributed to different farming practices, crops grown and certain other factors. having the Experiencing of Various Subsidiary/Crop Enterprises 63

18 Similarly, table 3.10(a) revealed the number of respondents were or had been involved in various subsidiary enterprises. As shown in the table, the number of respondents having the experience of dairy was respondents had the experience of mushroom cultivation whereas 61 of the total 300 respondents had the experience of bee keeping. 53 respondents were or had been involved in agri-processing and 97 had the experience of poultry. Finally, the total number of respondents out of 300, who were or had been involved in kitchen gardening was found to be 215. Table 3.10(a) having the Experiencing of Various Subsidiary Enterprises S. No. Subsidiary Enterprises No. of 1 Dairy Mushroom Cultivation 43 3 Bee Keeping 61 4 Agri Processing 53 5 Poultry 97 6 Kitchen Gardening 215 Table 3.10 (b) revealed the total number of respondents who were found to have the experience of cultivation of various crops. As is clear from the table, all the 300 respondents were found to have the experience of various activities involved in the cultivation of paddy as well as wheat, the major crops of Punjab. As for maize, only 217 respondents had the experience of various activities involved in its cultivation. Only 37 of the respondents were found to have the experience of various activities involved in the cultivation of cotton. Further, the number of respondents having the experience of various activities involved in the cultivation of potatoes was out of the total 300 respondents were found to have the experience of various activities involved in the cultivation of peas. Finally, the number of respondents having the experience of various activities involved in the cultivation of fodder was 300 i.e. all the respondents were found to have been involved in the cultivation of fodder at some point of time in their life. 64

19 Table 3.10(b) having the Experiencing of Various Crop Enterprises S. No. Crop Enterprises No. of 1 Paddy Wheat Maize Cotton 37 5 Potato 54 6 Peas 72 7 Fodder 300 Data Collection The required data were collected by interviewing the respondents personally with the help of a pre-tested interview schedule. The preliminary draft was tested on thirty respondents. After a few changes, the final questionnaire was developed which was used for data collection. As would be clear from the questionnaire, an attempt was made to collect as detailed the data as possible from respondents surveyed to explain the various aspects of the study. Also, the questionnaire was kept as simple as possible and translated into Punjabi, so as to enable the respondents to understand it properly and respond to it as correctly as possible, as most of the respondents were expected to be very less educated. Analysis of Data The tabulation of data was done to have a comprehensive picture of the analysis commensurate with the different objectives of the study. Apart from percentage method, the following tests have been applied for analysing the data. Factor Analysis The factor analysis is general and frequently used as an interdependence statistical technique that has found increased use in marketing research (Luck, 1987, p.542). 65

20 The factor analysis is designated as the queen of analytical methods because of its power and elegance (Dwivedi, 1997, p.199). It is a method of extracting common factor variances from a set of measures. It minimises the multiplicity of measures to the utmost simplicity. It indicates what measures go together and suggests unities the basic characteristics underlying varied measures. a) The correlation matrix is computed and examined to find out whether it reveals enough correlations. b) Anti-image correlation matrix shows the negative values of partial correlations among variables. True factors exist if the partial correlations are low among variables. c) Kaiser-Meyer-Olkin Measure of Sampling Adequacy (MSA) is an index for comparing the magnitudes of the partial correlation coefficients. The index ranges from 0 to 1. KMO should be sufficiently high for individual variables and also for overall MSA. d) Bartlett s Test of Sphericity indicates statistically significant number of correlations among variables. Principal Component Analysis was used to extract factors. The linear combinations of variables were used to account for variation (spread of each dimension in a multivariate space). The variances of the factors are called Eigen value, characteristic root or latent root. The most common approach for determining the number of factors to retain in the analysis is to examine the Eigen value of the solution matrix. Although there are a number of rules on what factors should be retained for analysis, the most commonly used is the Eigen value greater than one. Communalities are the percentage of total variance summarised by the common factors. The communalities can be found mathematically by squaring the factor loadings of a variable across all factors and then summing these figures. A low communality figure indicates that the variable is statistically independent and cannot be combined with other variables. Factor loadings are the correlation between the observed variables and the newly produced factors (Luck, 1987, p.546). In addition to latent root criteria where we consider factors which have latent roots greater than one, there are other methods like priori criteria where the researcher 66

21 already knows how many factors to extract and instructs the computer accordingly. The other is percentage of variance. In social sciences, 60% of the total variance (or sometimes less also) is considered satisfactory. Lastly, scree test takes at least one factor more than the latent root criteria extracted. In the present study, all the above methods were used for the analysis of data except the priori method. The scree test was used taking latent root as the guideline. The percent of total variance explained was taken into consideration. Factor Rotation Loadings are rotated to make them interpretable. Varimax rotation is the most recognised popular orthogonal rotation procedure. Orthogonal rotation with varimax is run. Orthogonal can be done with quartimax also. Varimax criteria maximises the sum of the variances of the squared loadings within each column of the loading matrix whereas quartimax simplified the rows. Variamx was considered more relevant and tried because quartimax created a large general factor and in oblique rotation the axis are rotated and th 90 degree angle is not maintained making it more flexible. Oblique rotations are still controversial. Promax was also tried to find some correlation between the factors. The final step is naming the factors and the labelling is intuitively developed depending upon the creativity of the researcher taking into consideration its appropriateness for representing the underlying dimensions of a particular factor. The process of naming factors is not very scientific although some guidelines have been recommended (Hair et al, 1995, p.388). Software Package Used SPSS 10.0 version was used for all statistical analysis of the study. The Microsoft Excel was used to arrange the data and check the discrepancies or missing values. Limitations of the Study Though utmost care was taken to get accurate data and results yet the possibility of some inaccuracy cannot be ruled out because of misinterpretation and misunderstanding on the part of the respondents. 67

22 a) As the present study was confined to rural areas of three districts under study, the findings may not be applicable to other parts of the country because of economic, political, social and cultural differences resulting in variations in attitude, perceptions and preferences. b) As in all such studies, the results and findings of today s research may become less relevant tomorrow as the different factors affecting the role of women in agriculture sector being dynamic in nature. c) The findings of the study may vary in other agro-climatic regions due to variations in crops being grown, socio-cultural differences, changes in economic levels and educational standards, changed cropping patterns, and climatic conditions. d) Although every effort was made to get the accurate information from the respondents, the possibility of a respondent giving biased information could not be completely ruled out. 68