Current World Environment

Introduction

India is the land of agriculture; it may sound like cliché for many of us. But it’s also true that Agriculture as an occupation is the main source of livelihood among the rural community from the pre-historic time and still approximately 50 percent of our population is directly dependent on agriculture.¹ But, the recent trends in agriculture and allied sectors are showing some depressing pictures in agriculture and that is a threat to our “sustainable agricultural dream” in the current environment. The share of agriculture and allied sectors in India's GDP has declined to 13.7 percent in 2012-13 from 51.9 percent in 1950-51.²

The reason given to this decline by few of the Agricultural experts was due to shift from traditional agrarian economy to industry and service sectors. There is some fact in their statement, but we can’t ignore the fact that the living condition of majority of farmers in our country is pitiable to such an extent that a large number of farmers in India are compelled to commit suicide and are at the verge to quit farming than to live in a miserable livelihood conditions. Today, India is world's suicide capital with a suicide in every 2 minutes.³ Moreover, Suicides as a whole rose nationally in the 1997-2005 period, but the rate of increase in farm suicides was far higher than the rate of increase in suicides by non-farmers.⁴

Indian subcontinent is highly vulnerable to major natural disasters such as earthquakes, tsunami, cyclones, floods, droughts, landslides and bushfires. Whether, it is early morning tsunami of 26^th December 2004 in Andaman & Nicobar Islands or in the form of national calamity in Bihar on 18^th August 2008, calamity (flood) which affected 3.3 million people or October 13, 2013 Cyclone Phailin which hit Odisha at wind speed of 210 km per hour and in which over seven lakhs people were evacuated. The common link among all the three calamities was that “the severely affected communities were of the farmers. 18^th August 2008, Kosi flood was declared as “National Calamity” by Prime minister of India, Dr. Manmohan Singh on 28^th August 2008⁵ and so far it is the single calamity in the history of India that a calamity was officially declared as a “National Calamity”. Subsequent years in the same region were seen as dry years (as 2009, 2010 and 2013 were declared as drought hit years in Bihar, India).

The worst happens when our primary sector is getting another setback in the form of farmers’ apathy or antipathy towards agriculture. As per the 59^th Round of NSSO,⁶ 40 percent of the farmers wish to quit farming. 76 percent farmers want to quit farming.⁷ Centre for studies of developing societies (CSDS) survey revealed that 76 percent of farmers would prefer to do other work while 60 percent wanted their children to migrate to and settle in a city. On an average, that’s about 2,035 farmers losing ‘Main Cultivator’ status every single day form the last 20 years¹ and in a time of jobless growth, they have had few places to go beyond the lowest, menial ends of the service sector. There are few “distress hotspots” in India, where farmers are committing suicide or want to quit farming.⁸ So, it is important that special attention should be paid to such areas to reduce risk. It has been recorded that distressed hotspots are those where farmers had faced crop failure due to several reasons including natural calamities.

Those distressed hotspots have been identified in the country like: Kosi region of north Bihar where farmers are quitting farming and becoming laborer due to concurrent flood and drought in the region, southern Punjab's Sangrur and Bhatinda district, Bundelkhand region in Uttar Pradesh, Vidharba region in Maharashtra etc. Therefore, it is necessary to find suitable tool in order to find out the reasons of their disinterest in agriculture and taking the extreme step like suicide in the past few decades. Policy makers need to know what the farming community wants, in order to design policies that will benefit the farmers in true sense. Therefore, while developing any coping strategies or formulating policies in respect of farmers’ distress, the interest of the farmers at grass-root level must be kept in the forefront. So, “resilience scale” was constructed to know the reason why farmers are committing suicide or what motivates them to cope up in their life despite of numerous hardships.

  Few popular ‘resilience scales’ were constructed to measure midlife crisis in Men and Women⁹ and to measure resiliency level in students and United States Army.¹⁰ It must be taken into consideration that no single ‘resilience scale’ would be able to capture the resiliency level of farmers countrywide. So, separate resilience scale should be constructed for each distressed hotspot of our country. Hence, to find out the resilience level of one of the most backward and vulnerable region of Bihar, Kosi region has been purposively selected. In addition it is rightly said that a ‘true resilience’ can only be measured in ‘post-traumatic condition’. So, 6 years (2008-2014) was adequate time for them to bounce back after the calamity. The respondents should be categorized into five groups namely ‘In need, Fragile, Vulnerable, Coping and Resilient’ based on cumulative square root frequency (CSRF) method after getting the response of the farmers’ in 3 point continuum scale.

Materials and Methods

The word resilience had Latin origin in 1620-30; Latin resili (Ä“ns), present participle of resilÄ«re to spring back, rebound (see resilient) + -ence. Resilience is a dynamic process in which the individual displays positive adaptive skills despite experiencing significant traumatic adversity; it is a measure of the ability to cope with stress. Assets and resources within the individual, their life, and environment facilitate this capacity for adaptation and “bouncing back” in the face of adversity.¹¹ Resilience in this study was operationalized as the degree to which farmers bounced back in relation to their life after the national calamity.

The method of summated rating suggested by Likert (1932)¹² was followed in the development of scale. The following steps were considered for measuring resilience of the farmers in relation to their life. Collection of statements: The first step in the construction of resilience scale was to collect statements pertaining to the resilience in relation to life. Utmost care was taken to include equal number of positive and negative statements in the list to reduce the effects of social desirability and positive response bias. A tentative list of 54 statements pertaining to “Resilient in relation to farmers’ life” were collected by consulting relevant literature and through consultation with extension experts, agricultural scientists, rural journalists, livelihood experts and doctors from top medical college in order to incorporate the psychological parameters for “resilience in relation to farmers’ life (RFL-Scale)”.

Editing the statements: These statements were edited as per the 14 informal criteria enunciated by Edwards (1969)¹³ Likert (1932)¹² and Edwards and Kilpatrick (1948).¹⁴ Out of 54 statements, 33 statements were retained after editing. These statements were found to be non-ambiguous and non-factual. Response to raw statements: The proforma containing raw statements on three point continuums i.e. Agree (A), Undecided (UD), Disagree (DA) were mailed by post, e-mail and also handed over personally to the total 75 judges.

These judges were experts in the field of Extension Education, Psychology and Rural Journalism and were from various Agricultural and Veterinary Universities, Medical College, Media houses and Institutes. The judges were requested to examine each statement and rate them on three point continuum indicating the suitability of statements. The judges were requested to make necessary modifications and additions or deletions, if they desired so. Out of 75 judges 60 judges from 30 different institutes had returned the same set of statements after duly recording their judgements in a stipulated span of 4 months and were considered for the item analysis.

Item analysis: Statement analysis is an important step while constructing valid and reliable scale. The judges were asked to indicate their degree of response with each statement on three point continuums ranging from Agree (A), Undecided (UD) and Disagree (DA) with scoring of 3, 2, and 1; for positive statement and the scoring pattern was reversed i.e. 1, 2, and 3 for negative statement. The total individual judges’ score was calculated by summing up the score of each statement given by individual judge. Calculation of ‘t’ values: Based upon the total individual scores, the judges score were arranged in descending order.  The top 25 percent of judges with their total individual scores were considered as high group and bottom 25 percent as the low group so that these two groups provided criterion groups in terms of evaluating the individual statements. The ‘t’ values were worked out in order to discriminate the responses of high and low groups for the individual statements by using the under mentioned formula (Edwards, 1969).¹³ Thus, out of 60 judges to whom the statements were administered for the item analysis, 15 judges with highest and 15 judges with lowest scores were used as criterion groups to evaluate individual statement.



X_H= The mean score on a given statement for the high group
X_L= The mean score on a given statement for the low group
ΣX_H²= Sum of squares of the individual score on a given statement for high group
ΣX_L²  = Sum of squares of the individual score on a given statement for low group
ΣX_H = Summation of scores on given statement for high group
ΣX_L = Summation of scores on given statement for low group
n = Number of subject in low and high group
t   = The extent to which a given statement differentiate between the high and low group.

Example: Statement 1: I always hope for the best while being mentally prepared for the worst.

The calculation of t for evaluating the difference in the mean response to resilience statement by a high group and a low group   

Table 1A  Click here to View table

 

The ‘t’ value is a measure of the extent to which a given statement differentiates between the high score and low score groups. The ‘t’ value equal to or greater than 2.467 (n₁+n₂-2 df at 1% level of significance i.e. at 28 degree of freedom) indicating the average response of high and low groups to a statement differs significantly. Thus 18 statements on “Resilient in relation to farmers’ life” (9 positive and 9 negative) with significant discriminating values were retained in the scale (Table 1).

Table 1: Resilience in relation to Farmers’ Life Statements Analysis and their respective‘t’ Values 

Sl.No.	Statements to measure Resilience in relation to farmers’ Life	‘t’ Values
1	I always hope for the best while being mentally prepared for the worst.	3.47**
2*	I feel hurt when my family and relatives don’t support me, even when, I am going in the right track.	0.91
3	I learn something of value from all my mistakes.	1.90
4*	I am easily influenced by what other people think or say about me.	6.77**
5	I infuse hope to my family/relatives/ neighbours, whenever they are pessimistic.	0.74
6	I can find a solution to every problem, no matter what may be the gravity of the problem.	3.84**
7*	I don’t have other kinds of job, during agricultural ‘lean season’.	4.48**
8*	If my nearby school is destroyed due to flood, I don’t care to send my children to the next nearby school.	4.02**
9	I prefer to spend money on my children’s education than to expand my land holdings or livestock numbers.	4.58**
10*	I avoid participate in public welfare scheme that is being run in my village.	4.73**
11	I pursue my dream once I am convinced (no matter, my family or relatives oppose or support me).	0.69
12*	I don’t rely on trust, reciprocity and values in the present world.	3.52**
13*	I don’t give priority to groups/family solidarity.	0.96
14*	If I am poor, I don’t care much to make a better living.	1.00
15	I have bounced back to my normal life (or much better than before) after the calamity.	5.18**
16*	I don’t know my weaknesses and so it is very difficult for me to sort it out.	7.15**
17*	I can’t demarcate between my friends and foes.	2.34
18	The incidence of the year 2008 has made me stronger to face adversity/setbacks.	0.83
19*	I usually feel depressed about my future.	0.39
20	In the coming years, I am going to opt for non-farm enterprise, which is more remunerative than Agriculture.	5.26**
21	I have someone with whom, I can share my problems.	0.41
22	I have a good sense of humour to deal with the situation of criticism.	5.76**
23	Life is not smooth path for me and that’s what makes it more interesting.	6.08**
24*	I am in the company of those people who always demotivate me.	5.70**
25	There is a purpose of my life and my life has meaning.	0.25
26	I stand up for myself without putting others down.	2.31
27*	I don’t have trust on my own ability.	2.11
28*	I completely depend on others in taking making my decision.	2.63**
29	I feel proud because I have accomplished things in my life.	2.36
30	I see difficulties as a God’s/ nature’s way to check my patience and endurance.	4.03**
31	I am a work-loving person, so I can’t sit idle	2.07
32*	I spend more than my capability on the marriage/ceremony due to peer pressure.	8.69**
33*	I endorse other farmers taking the extreme steps, like suicide due to their series of problems faced by them.	9.83**

* indicates negative statements **Significant at 1% level of significance

Reliability and Validity of the scale: A scale is reliable when it gives consistently the same results when applied to the same sample. The final set of the 18 statements which represent the Resilience in relation to Farmers’ life, was administered on three point continuum to a fresh group of 30 farmers of non sample area, who suffered from 16 June 2013 flood in Lapra and Odhri Villages of Jagadhri Block of Yamunanagar district of Haryana. The designed resilience scale for the study was pre-test for its reliability by using the split half method. Reliability was calculated by using the Formula of (Spearman, 1910¹⁵; Brown, 1910).¹⁶ The coefficient of correlation between odd and even scores was 0.87 which was found to be significant at 1 percent level, thereby testifying the reliability of the scale.


Where,   r_hh = Pearson correlation between odd and even



The coefficient of correlation between odd and even scores was 0.87 which was found to be significant at 1 percent level of significance. SPSS Version 20 (Statistical Package for the Social Sciences) was used for calculating Cronbach’s alpha and Guttman Split-Half Coefficient. The RFL-Scale has good internal consistency - Cronbach’s alpha for the present study was 0.874 and Guttman Split-Half Coefficient value was 0.872. It shows that scale is reliable.  As the content of the resilience was thoroughly covered the entire universe of farmers’ life through literature and expert opinion, it was assumed that present scale satisfied the content validity.

Results and Discussion

The final scale consisting of 18 (9 positive and 9 negative) statements can be administered to the national calamity affected farmers on a 3 point continuum viz., Agree (A), Undecided (UD) and Disagree (DA) with a weight age of 3, 2 and 1 for positive statements and reverse scoring system for negative statements. The overall possible maximum and minimum score ranges between 54 to 18 (Table 2).

Table 2: Final Resilience in relation to Farmers’ Life Scale (RFL-Scale) comprising 18 statements

S.No.	Statements	A	UD	DA
1	I always hope for the best while being mentally prepared for the worst.
2*	I am easily influenced by what other people think or say about me.
3	I see difficulties as a God’s/ nature’s way to check my patience and endurance.
4*	I completely depend on others in taking my decision.
5	I can find a solution to every problem, no matter what may be the gravity of the problem.
6*	I avoid participation in public welfare scheme that is being run in my village.
7	I prefer to spend money on my children’s education than to expand my land holdings or livestock numbers.
8*	I don’t rely on trust, reciprocity and values in the present world.
9	I have bounced back to my normal life (or much better than before) after the calamity.
10*	I am in the company of those people who always demotivate me.
11	I stand up for myself without putting others down.
12*	I spend more than my capability on the marriage/ceremony due to peer pressure.
13	Life is not smooth path for me and that’s what makes it more interesting.
14*	I don’t have other kinds of job, during agricultural ‘lean season’.
15	In the coming years, I am going to opt for non-farm enterprise, which is more remunerative than Agriculture.
16*	I know my weaknesses but it is very difficult for me to sort them out.
17	I have a good sense of humour to deal with the situation of criticism.
18*	I endorse other farmers taking the extreme steps, like suicide due to their series of problems faced by them.

Note: Equal number of positive (+) and negative (-) worded statements were taken alternately to reduce the effects of social desirability and positive response bias. Asterisks (*) mark statements are reverse coded/negative statements. A=Agree UD =Undecided DA=Disagree

Conclusions and Recommendations

As established by ‘father of positive psychology, E.P.M. Seligman,¹⁰ resilience can be measured as well as built by proper guideline and training. So, resiliency level of Indian farmers should be measured and built simultaneously in order to prevent them from taking the extreme step like suicide. Moreover it has been seen in India that farmers usually hesitate to share their opinion (psychological factor) as well as value of their assets (physical factor) due to several reasons associated to it. In addition, it has also been seen that farmers are disenchanted by their profession i.e. farming, but still very optimistic about their life.

So, to measure the overall resiliency level (psychological factor) of the farmers “Resilient in relation to farmers’ life” Scale (RFL-Scale) should be used along with Resilience in relation to Farmers’ Profession Scale (RFP-Scale). In order to get the more precise result about the farmers’ true condition Livelihood Security Index (physical factor) should be used along with both the resilience scale (psychological factor).  So, in its first attempt a scale to measure the resilience of farmers in relation to their life has been presented in this paper. The resilience scale constructed in the present study can be used by future researchers with suitable modifications in the distressed hot spots to measure the resiliency level of farmers in relation to their life.

References
 

1. Census of India (2011) Provisional population totals - India - data sheet. Office of the registrar general and census commissioner, India ministry of home affairs, data released on 31^st March 2011.
2. Central Statistics Office report (2013) Agriculture's share in GDP declines to 13.7% in 2012-13, data released on August 30, 2013.
3. World Health Organization (2014) Preventing suicide: A global imperative. India is World's Suicide Capital, Department of Mental Health and Substance Abuse in Geneva, Report released on September 04, 2014.
4. Sainath P (2007) A Farmer is Committing Suicide Every 32 Minutes. Counter Punch, Weekend Edition, November 17-19, 2007.
5. SAARC (2008) South Asia disaster news. SAARC Disaster Management Centre, New Delhi. 47: 1
6. NSSO 59^th Round Survey (2003) 40 percent of the farmers wish to quit farming. Survey conducted from January to December 2003.
7. CSDS, Lokniti Survey (2014) 76 percent farmers want to quit. Published in Business Standard on March 12, 2014.
8. The National Commission on Farmers (2007) National policy for farmers under the chairmanship of Prof. M.S. Swaminathan, final report in October 2006. DAC, MoA, Government of India. P-21.
9. Ryan L (2009) Development of a New Resilience Scale: The Resilience in Midlife Scale (RIM Scale). Asian Social Science, 5 (11): 39-51.
10. Seligman, E.P.M. (2011). Building Resilience. Harvard Business Review, April 2011.
11. Windle G, Bennert K.M, Noyes J (2011) A methodological review of resilience measurement scales. Health and Quality of Life Outcomes, 9 (8).
12. Likert R (1932) A technique for the measurement of attitudes. Arch. Psychology, 140.
13. Edwards A.L (1969) Techniques of attitude scale construction. Vakils, Feffer and Simons Private LTD., New York.
14. Edwards A.L, Kilpatrick F.P (1948) A technique for construction of attitude scales. J. App. Psycho., 32:374-384.
15. Spearman C.C (1910) Correlation calculated from faulty data. British Journal of Psychology, 3: 271–295.
16. Brown W (1910) Some experimental results in the correlation of mental abilities. British Journal of Psychology, 3: 296–322.