Chapter 5

DISPARITIES IN HUMAN DEVELOPMENT IN KERALA:

THE NON-CONVENTIONAL INDICATORS

5.1 Introduction ……………………………………………… 132

5.2 Analysis in terms of Secondary Data ………………………. 133

5.2.1 Personal Disabilities ………………………………… 134

5.2.2 Morbidity ………………………………………… 135

5.2.3 Crimes ………………………………………………… 138

5.2.4 Injustice towards Women ………………………… 140

5.2.5 Suicides ………………………………………… 142

5.2.6 Medical Termination of Pregnancy ………………… 142

5.2.7 Borda Ranking ………………………………… 145

5.3 Analysis in terms of Sample Study ……………………….. 147

5.3.1 Disability and Morbidity ………………………… 148

5.3.2 Crimes ………………………………………… 149

5.3.3 Experiences and Expectations ………………… 150

5.3.4 Borda Ranking ………………………………… 152

132

Food is roughly a $700 billion industry in the United States, counting agriculture, supermarkets, restaurants and the rest. Unfortunately, a good deal of that industry ends up inside us Americans. The result is flab, and a diet and weight loss industry of some $32 billion nationwide and - yes - growing. …………… The food industry spends some $21 billion a year on advertising to goad us to eat more. Then we spend that and half again trying to rid ourselves of the inevitable effects.

Jonathan Rowe & Judith Silverstein1

5.1 Introduction

The conventional studies of human development revolve around some pre-

determined indicators as we have seen in the erstwhile discussion. However, there

are many variables, which can significantly influence—directly or indirectly—the

state of human well-being, yet conveniently ignored by most development

enthusiasts. This is particularly true about distresses—both individual and

social—that are never considered by the GDP accounts and mostly ignored by the

human development balance sheets. As Jonathan Rowe2 points out, ‘The things

economists call "goods" and "services" increasingly don’t strike people as such.

There is a growing disconnect between the way people experience growth and the

way the policy establishment talks about it, and this gap is becoming an unspoken

subtext to much of (American) political life.’ [Parentheses by this author]. The

present chapter is just a very humble attempt to draw the attention of the human

development protagonists to this rarely trodden area of development economics.

1 The GDP Myth: Why "growth" isn't always a good thing, The Washington Monthly, March 1999, 31(3) 2 The Growth Consensus Unravels, http://www.dollarsandsense.org/

133

As already stated, the analysis we are attempting here is only indicative

rather than comprehensive. It points to the inadequacies of depending on the

conventional indicators of well-being alone, about which we have discussed in

Chapter 2 in some detail. We already have a host of indicators to measure the

add-ups to human well-being, but not sufficient indicators to quantify the

deductions. For the individual as well as the society, such deductions take several

forms; morbidity, crimes, social unrest, corruption, pollution, etc., are just a few

important ones among them. The common feature of these is that they all create

distress. It is true that the recent Human Development Reports include statistics

on some of these distresses, but no attempt has been made to integrate them into

the human development indexing and ranking system employed by the UNDP.

Even the deprivation perspective of human development fails to catch them.

The foregoing part of this chapter is a small step towards integrating some

non-conventional indicators with already discussed conventional indicators of

human development, thereby making the study of human development more

productive. The indicators we are employing in this chapter are emphasising the

distress perspective in human development. The pattern of regionalisation and

mode of analysis of the present chapter remain to be the same as those in Chapter

4.

5.2 Analysis in terms of Secondary Data

Physical and mental disability, morbidity, incidence of crimes, atrocities

against women, occurrence of suicides and medical termination of pregnancy

(MTP) are the indicators considered here in connection with the analysis under

distress perspective.

134

5.2.1 Personal Disabilities

Personal disabilities resulting from physical or mental handicap are serious

impairments to the state of human well-being. If we compare the state of well-

being in two societies with significantly different proportions of disabled persons

in total population, all other indicators of human development being the same, the

one with a higher proportion of disabled population will be definitely worse off

than the other will. Table - 5.1 shows the number of disabled persons3 per lakh of

population as per 2001 census data and the ranks of various regions on the basis of

that. Considering the negative impact of disability on human well-being, the

regions with lower proportions of disabled population are given higher ranks and

vice-versa.

Among the districts, Wayanad claimed the top rank with the lowest

proportion of disabled in total population (2357/lakh) and Kollam came last

(3208/lakh). The five top ranks were bagged by the five Malabar region districts

other than Kozhikode. The last six positions were taken by the six Travancore

region districts. The two districts of Cochin region were at the sixth and seventh

positions, between the districts of Malabar and the districts of Travancore.

A detailed examination of the census data revealed that the pattern of

incidence of various disabilities is more or less the same in all the regions. The

most common disability is the one related to sight (nearly two out of every five

disabled persons) followed by movement related impairments (one out of four).

Mental disability came next (about one sixth of total) followed respectively by

3 Here we consider all types of disabilities—disabilities of sight, speech, hearing, movement and mental disabilities—together.

135

hearing and speech impairments. This pattern remained unchanged in all regions

considered.

Table - 5.1: Disabled persons per lakh population in Kerala Regions (2001)

Total Disabled Rank

Kasaragod 2360 2 Kannur 2405 3 Wayanad 2357 1 Kozhikode 2843 8 Malappuram 2439 4 Palakkad 2496 5 Thrissur 2509 6 Ernakulam 2551 7 Idukki 3201 13 Kottayam 2853 9 Alappuzha 3013 12 Pathanamthitta 2859 10 Kollam 3208 14 Thiruvananthapuram 2874 11 KERALA 2703 North 2518 1 South 2840 2 Malabar 2518 1 Cochin 2530 2 Travancore 2994 3

Source: Census of India 2001

5.2.2 Morbidity

Morbidity is yet another factor, which has detrimental effect on the state of

human well-being. While taking life expectancy at birth as the sole indicator of

health achievement, the HDI ignores the impact of morbidity on human

development. For instance, Kerala, the state with the highest life expectancy in

India has the highest self-reported morbidity also.4 It could have been due to the

4 This, however, is no paradox at all. Johansson (1991, 90) argues that developed countries generally have low mortality and high morbidity and developing countries have high mortality and low morbidity. Riley (1990, 916) showed that mortality rate increased in all age groups while age-specific mortality rates declined.

136

higher level of education and the better health awareness of Kerala people.

However, an instance of ill health is, no doubt, an instance of distress. It imposes

economic as well as psychological strains upon the affected individual and his or

her household. Moreover, incidence of diseases, particularly that of

communicable diseases, breeds distortions in social life.

As part of our analysis of the distress perspective of human development,

we consider two indicators of morbidity—incidence of communicable diseases

and the number of HIV positive cases reported. The statistics on communicable

diseases seem to be more reliable than general morbidity statistics, as the former

has closer links with the health awareness and overall standard of living and

human development of the population under consideration. The morbidity

statistics for different regions are given in Table - 5.2. In column 2 of the table,

the annual average value of the total communicable cases reported for the two-

year period January 2000 to December 2001 is given as percentage of the mid-

year population. In column 4, the number of HIV positive cases identified during

the period 1994-2001, on the basis of blood sample screening reports, is shown as

number per lakh of mid-period population. Instead of annual values, total for the

period under consideration has been used for HIV positive cases, owing to its

chronic and cumulative nature.

As far as the incidence of communicable diseases is concerned, there

observed significantly high degree of disparity among the regions. Among the

administrative regions, it ranged from as low as forty per cent in Kannur to as high

as 141 per cent in her immediate neighbour district Wayanad. The southern

district Kollam also had a very high incidence of communicable diseases

137

(136.6%). As many as five districts had above 100 percent incidence, of which

four were from the South. Interestingly, just as the extreme diversity observed

between Kannur and Wayanad in the North, a similar diversity was seen between

Pathanamthitta and Kollam in the South. Overall, the southern region in general

and the Travancore region in particular, displayed a higher incidence of

communicable diseases.

Table 5.2: Morbidity Statistics of Kerala Regions

Communicable Diseases (January 2000-December 2001)

HIV Positive Cases (1994-01)

District/Region

Average of Annual Cases Reported as %

of Mid-year Population

Rank Per Lakh of Mid-year

Population Rank

(1) (2) (3) (4) (5) Kasaragod 67.80 5 3.69 6 Kannur 40.00 1 7.11 7 Wayanad 141.22 14 2.66 3 Kozhikode 64.41 3 19.89 12 Malappuram 72.60 6 10.84 10 Palakkad 77.95 8 2.08 2 Thrissur 67.38 4 21.87 14 Ernakulam 79.31 9 7.51 8 Idukki 77.89 7 0.72 1 Kottayam 109.67 11 16.39 11 Alappuzha 118.34 12 9.02 9 Pathanamthitta 40.82 2 2.95 5 Kollam 136.61 13 2.88 4 Thiruvananthapuram 106.44 10 20.33 13 KERALA 84.40 10.76 North 69.64 1 9.29 1 South 95.30 2 11.83 2 Malabar 69.64 1 9.29 1 Cochin 73.47 2 14.55 3 Travancore 106.14 3 10.49 2

Sources: Data on communicable diseases from the ‘Directorate of Health Services, Thiruvananthapuram’ and the data on HIV positive cases from the ‘Kerala State AIDS Control Society, Thiruvananthapuram’.

The very high incidence of morbidity in some regions could have been due

to the cross border movements of patients, seeking medical assistance. Another

138

reason might be the reporting of the same case from different hospitals, as the

patients unsatisfied with the treatment in one hospital may approach another one

for the treatment of the same ailment. Such duplications in morbidity reporting

could have been particularly high in the case of outpatient cases.

Turning to reported HIV positive cases, Idukki had the lowest

incidence(less than one per lakh of population), followed by Palakkad and

Wayanad. On the other end Thrissur stood with the highest incidence (21.87 per

lakh) closely followed by Thiruvananthapuram and Kozhikode. On the average,

districts with no big urban centres reported low HIV incidence. One possible

explanation here is that people in rural areas would be moving to urban centres for

medical diagnosis and if found HIV positive, it is reported as a case of the district

of diagnosis and not as a case of the native district of the patient. Between the

North and the South, the former had relatively lower reported HIV positive cases.

Among the historical regions, Malabar reported the lowest and Cochin reported

the highest HIV morbidity.

5.2.3 Crimes

The incidence of crime is another source of distress that has an inhibiting

effect on the level of human well-being. The larger the incidence of crimes, the

more will be the feeling of insecurity and more time and resources have to be

devoted for obviate that feeling. As the current Human Development Indices do

not reflect these departures from eudemonia, they tend to overstate the level of

human development.

139

In Table - 5.3, we compare the incidence of cognisable crimes under IPC in

Kerala regions.5 The figures in the table were obtained by computing the annual

average figures for the five-year period between 1996 and 2000 and they were

then converted to crimes per lakh of mid-year population.

Table - 5.3: Incidence of Cognisable Crimes under IPC (Annual Average for the period 1996-2000)

District/Region Crimes per Lakh

of Mid-year Population

Rank

Kasaragod 250.0 3 Kannur 241.1 2 Wayanad 281.7 6 Kozhikode 275.4 5 Malappuram 210.4 1 Palakkad 251.6 4 Thrissur 283.1 7 Ernakulam 398.6 14 Idukki 392.4 13 Kottayam 343.4 11 Alappuzha 331.9 10 Pathanamthitta 352.8 12 Kollam 309.5 8 Thiruvananthapuram 327.0 9 KERALA 299.9 North 245.5 1 South 337.6 2 Malabar 245.5 1 Cochin 341.9 3 Travancore 335.5 2

Source: State Crime Records Bureau, Kerala Police, Thiruvananthapuram

Among the districts, Malappuram had the lowest (210.4 per lakh) and

Ernakulam had the highest (398.6 per lakh) incidence of crimes. The deviation is

indeed significant. Interestingly, the six northern districts held the first six

positions with lower crime rates. The southern districts also remained together

5 Only Indian Penal Code (IPC) crimes were considered by this study. Crimes under Special and Local Laws (SLLs) were not included, as the consequences of many of them did not confine to the geographical area where they were reported and registered.

140

with relatively high rates of crimes. But the disparity between the two districts of

the historical region of Cochin was remarkable. Thrissur with a crime rate of

283.1 and rank of seven remained well in the company of the Malabar districts

where as Ernakulam went seven ranks down to the other extreme. These findings

were well substantiated by the figures given in Table - 5.4.

Table - 5.4: Disparities in the incidence of crimes (Comparison of means and standard deviations of different categories of Kerala Districts)

Districts of

Kerala North/Malabar South Cochin Travancore

Mean 299.9 245.5 337.6 341.9 335.5

Standard Deviation 56.95 25.60 39.11 81.64 28.40

Source: Computed by the Author

5.2.4 Injustice towards Women

The treatment of women in a society is generally regarded as an indicator

of its development. As Sen (1992: 122) points out, “There are systematic

disparities in the freedoms that men and women enjoy in different societies, and

these disparities are often not reducible to differences in income or resources”.

Such a disparity, particularly one coming under the distress perspective we are

discussing, is atrocities against women. We use the annual average number of

grievances registered with the Kerala State Women’s Commission during the

period 1996-2000 per lakh of mid-year female population as an indicator for the

same. The complaints received by the Commission under twenty-five different

heads were taken together for the purpose. The discussion on this count runs in

terms of the data presented in Table - 5.5.

141

Table - 5.5: Cases registered with the Kerala Women’s Commission (Annual Average for the Period 1996-2000)

District/Region Per Lakh of Mid-year Female Population Rank

Kasaragod 18.56 5 Kannur 13.30 1 Wayanad 57.33 11 Kozhikode 18.20 4 Malappuram 14.83 2 Palakkad 31.48 7 Thrissur 16.40 3 Ernakulam 26.37 6 Idukki 56.20 10 Kottayam 41.48 8 Alappuzha 53.65 9 Pathanamthitta 60.00 12 Kollam 60.20 13 Thiruvananthapuram 100.59 14 KERALA 38.67 North 21.22 1 South 51.48 2 Malabar 21.22 1 Cochin 21.39 2 Travancore 66.35 3

Source: Kerala State Women's Commission, Thiruvananthapuram

Among administrative regions, Kannur had the lowest number of cases per

lakh of female population, with the Women’s Commission (13.3) succeeded by

Malappuram (14.8) and Thrissur (16.4). Thiruvananthapuram, on the other

extreme, had the maximum number of cases (100.6) followed by Kollam (60.2)

and Pathanamthitta (60.0). The northern districts as a whole, excepting Wayanad,

had relatively lower proportions of cases with the Women’s Commission.

Wayanad, on the other hand, had the fourth largest number of complaints (57.3)

per lakh of females. All districts of the Travancore region also had relatively

larger number of cases. The Cochin region positioned itself between the Malabar

and Travancore areas. However, the difference between the Malabar and Cochin

142

regions was only marginal, where as the Travancore area stood way apart as can

be seen from the table.

5.2.5 Suicides

Distress, in its extreme forms, leads to psychological derailment and even

to self-annihilation attempts. Emil Durekheim, a French sociologist, at the

beginning of the twentieth century, brought to focus motivational aspects of

suicide and traced them to distinct social factors (Antony, 2000). The number of

suicides can be taken as a good indicator of deviations from the state of eudemonia

in a society. In Table 5.6, the number of suicides in 2001 per lakh of people in

different regions of Kerala is given. Among the Districts, Malappuram reported

the lowest number of suicides (11.7 per lakh) and Idukki reported the highest

number (49.2 per lakh). Although Kasargod and Alappuzha were at the second

and third lowest suicide rates, their rates were twice the rate of Malappuram. At

the dismal end, Thiruvananthapuram and Wayanad followed Idukki. Between

North and South, the North had a much lower rate of suicides. Among the

historical groups, Malabar had the lowest and Travancore had the highest rates of

suicides.

5.2.6 Medical Termination of Pregnancy

The variables we have discussed so far in his chapter are those which are

widely accepted as distress indicators. Many other variables which could have

been used here like pollution and corruption were not used owing to the lack of

disaggregated data on them. So the author has tried the number Medical

Termination of Pregnancy (MTP) cases as another possible indicator to catch up

the extent of distress. Although, MTP is not generally viewed as an indicator of

143

distress, the circumstances which necessitate MTP are definitely imply personal

distress and in most cases imply social distress as well. MTP is legally permitted

on such grounds as possible danger to the life or health of pregnant women,

possibility of serious handicap to the child, pregnancy due to failure of

contraceptive device, pregnancy caused by rape etc. Whatever be the reason, the

adoption of MTP symbolises some kind of human distress. As MTP data was

readily available, it has been decided to employ it as an indicator in the non-

conventional sphere of human development.

Column 4 of Table 5.6 returns data on the number of MTP cases per lakh

of reproductive age-group females6 in the year 2000-01. Among the districts,

Malappuram reported the lowest number of MTP cases (181 per lakh) followed by

Wayanad (206 per lakh). There was considerable inter district variations in MTP

cases. The number of MTPs that reported from the thirteenth ranked Kottayam

was 4.5 times that of the first ranked Malappuram. The most striking difference

between two successive ranks was observed between the last ranked

Thiruvananthapuram (2449 per lakh) and the thirteenth ranked Kottayam (813 per

lakh). Fascinatingly, all the twelve districts other than Kottayam and

Thiruvananthapuram had lower MTP rates than the state average (647 per lakh). It

shows that the high state average was principally due to the extreme MTP rate of

Thiruvananthapuram. And the high MTP rate of Thiruvananthapuram needs a

closer and more detailed examination, which is beyond the scope of this work.

One possible explanation could be the widespread movement of pregnant women

6 Females between fifteen and forty nine years of age.

144

from the neighbouring districts of Kerala and Tamil Nadu to avail MTP facility in

the hospitals in Thiruvananthapuram.

Table - 5.6: Suicides and Medical Termination of Pregnancy in Kerala Regions

District / RegionSuicides / Lakh Population (2001)

Rank MTP / Lakh of 15-49 Age-group Women (2000-01)

Rank

(1) (2) (3) (4) (5) Kasaragod 22.1 2 320 3 Kannur 32.3 7 446 8 Wayanad 39.8 12 206 2 Kozhikode 25.5 5 614 # 11 Malappuram 11.7 1 181 1 Palakkad 33.1 9 390 4 Thrissur 34.3 11 402 5 Ernakulam 25.9 6 462 # 9 Idukki 49.2 14 476 # 10 Kottayam 24.6 4 813 13 Alappuzha 22.9 3 429 7 Pathanamthitta 32.3 7 635 12 Kollam 33.9 10 417 6 Thiruvananthapuram 41.4 13 2449 14 KERALA 29.3 647 North 25.0 1 377 1 South 32.5 2 845 2 Malabar 25.0 1 377 1 Cochin 30.0 2 432 2 Travancore 33.7 3 1050 3 # The data available for Kozhikode was for a period of 7 months and that for

Ernakulam and Idukki were for 11 months only. The monthly averages computed from them were used to arrive at the respective annual figures.

Sources: Data in Column 2 from the State Crime Records Bureau, Kerala Police, Thiruvananthapuram and data in Column 4 from the Directorate of Health Services, Thiruvananthapuram

Although there was considerable variations in MTP rates among the

northern districts (between the two neighbouring districts of Malappuram and

Kozhikode, for instance), the average rate for the northern region as a whole was

much lower than that of South. As far as historical groups are concerned, Malabar

had the lowest and Cochin had the second MTP rates. The difference between the

145

two is also not very significant compared to that with respect to Travancore. The

main culprit here also was the extreme MTP rate of Thiruvananthapuram.

An annoying observation from the MTP data we used was that, during the

year 2000-01, as many as thirty-one females below fifteen years of age were

undergone MTP operations in the state (Ibid, Government of Kerala, 2001). The

majority of them were from three districts—Kannur (11), Thrissur (8) and

Ernakulam (6). It may be noted that they actually belonged to the category of

‘children’ rather than ‘women’. Similarly, there were 1836 MTP cases reported

among females of 15-19 age-group. Further, the reason for MTP was stated as

pregnancy caused by rape in 183 cases out of the total reported cases in the state.

This seems to be an under-reporting when we consider that fact that thirty-six

percent of the total MTPs had not stated any clear reason. The SCRB data on the

incidence of crimes show that on the average there were 508 rape cases reported in

the state every year, during the period 1996-2000.7 The actual figure could be

much larger, considering the possibility of significant under-reporting of rape

cases in the Kerala society. These figures point to the need of reassessing the

status of women in Kerala and her constituent regions, with adequate emphasis on

the distress perspective.

5.2.7 Borda Ranking

Table 5.7 shows the Borda scores of the regions, with respect to the seven

non-conventional indicators we have considered so far in this chapter. Based on

the Borda scores, the regions were once again ranked as shown in the last column

of the table. Among the administrative regions, Malappuram with the lowest

7 State Crime Records Bureau, Kerala Police, Thiruvananthapuram

146

Borda score (25) got first rank and hence could be termed as the least distress-

prone district in the state. Malappuram had the lowest reported incidence in three

out of the seven non-conventional indicators considered and second lowest in one,

among the fourteen districts. Her worst performance had been in the number of

HIV positive cases, in which she got only tenth rank. Kasargod acquired the

second place in Borda ranking, with just one point margin in Borda score. She

managed to keep a relatively high rank in all the seven indicators, the highest

being two and the lowest being six. Interestingly, the six North Kerala

districts/Malabar districts appropriated the first six ranks. Wayanad, even with her

miserable performance in the incidence of communicable diseases, suicides and

female grievances, had been able to land at the sixth position owing to her

splendid performance in the incidence of disability, MTP cases and HIV positive

cases.

The two districts of the erstwhile Cochin State—Thrissur and Ernakulam—

got the seventh and the eighth ranks. The last six positions were taken by the six

districts of the Travancore region. Among them, the best achievement was that of

Pathanamthitta and the worst was that of Thiruvananthapuram. Out of the seven

indicators, Thiruvananthapuram had the thirteenth and fourteenth ranks in two

indicators each and the ninth, tenth and eleventh ranks in one each.

Between the northern and southern regions, the north had better

performance in all seven indicators and hence got the first rank in overall

performance. Among the historical regions, Malabar got first position in all the

seven. Cochin got second rank in five indicators and third rank in two.

Travancore scored second rank in two and third rank in five. Naturally, Malabar

147

came first and Travancore came last as far as their overall success in reducing

human distress is concerned.

Table - 5.7: Borda Ranking of Non-Conventional Indicators (Secondary Data)

District/Region Borda Score Borda Rank Kasaragod 26 2 Kannur 29 3 Wayanad 49 6 Kozhikode 48 5 Malappuram 25 1 Palakkad 39 4 Thrissur 50 7 Ernakulam 59 8 Idukki 68 12 Kottayam 67 11 Alappuzha 62 10 Pathanamthitta 60 9 Kollam 68 12 Thiruvananthapuram 84 14 KERALA North 7 1 South 14 2 Malabar 7 1 Cochin 16 2 Travancore 19 3 Source: Computed by the author

5.3 Analysis in terms of Sample Study

The analysis of the non-conventional indicators of human development

under the sample study also concentrates on the distress perspective. The

discussion here is not much different from the preceding part of this chapter, as the

indicators considered are somewhat similar. A small element of diversion is the

inclusion of certain normative indicators like the households’ assessment of their

experiences and expectations about future. Here too, the variables used are rather

indicative in nature; they are neither indispensable, nor self-sufficient.

148

5.3.1 Disability and Morbidity

As we have already stated, physical or mental disability and disease-

proneness are two major sources of human distress. Table - 5.8 presents a brief

account of them obtained from the sample survey. Column (2) shows the

percentage of people handicapped by physical or mental disabilities and column

(5) shows the corresponding ranks of the regions. The midland region had the

lowest proportion (2.76%) and the highland region had the highest proportion

(3.86%) of handicapped persons.

Table - 5.8: Disability and Morbidity Rates of Low, Mid and High Land Samples Percentage of people who were Rank

Samples

Han

dica

pped

With

Chr

onic

D

isea

ses

With

Sh

ort-d

urat

ion

Mor

bidi

ty

Han

dica

pped

Chr

onic

D

isea

ses

Shor

t-dur

atio

n M

orbi

dity

(1) (2) (3) (4) (5) (6) (7)

Lowland 3.44 10.63 19.38 2 2 2

Midland 2.76 14.57 22.05 1 3 3

Highland 3.86 9.66 17.39 3 1 1

Source: Sample Survey

The disease-proneness had been considered under two heads—chronic

diseases and short-duration morbidity. The former category consists of diseases

that need treatment for relatively long periods, such as tuberculosis, diabetes,

hypertension, cardiovascular disorders, and cancers. Diseases that need relatively

shorter periods of treatment—from a few days up to a maximum of thirty days—

were termed as short duration morbidity. For the first category, the number of

persons suffering from chronic diseases at the time of the survey were collected

149

and for the latter, number of individuals infected during the thirty days’ period

immediately preceding the date of the survey were obtained.

From Table 5.8 it is clear that the highland area had the lowest rates in both

chronic ailments (9.66%) and short-duration morbidity (17.30%). The highest

rates in both were experience by the midland sample (14.57% and 22.05%

respectively). The lowland area remained at the second position in both.

5.3.2 Crimes

For the analysis of the incidence of crimes, the total number of IPC cases

reported from each one of the sample Panchayats, during the one-year period from

January to December 2000, were collected from the respective Police Stations

under the jurisdiction of which the Panchayats come. These figures were then

converted as number of crimes per 1000 of mid-year Panchayat population. The

highland sample had the lowest number of reported crimes per 1000 population

(2.33), lowland sample came second (3.38) and the midland area came last (4.11).

There observed significant inter-regional disparity in the incidence of crimes,

particularly between the highland area and the other two. The incidence of crimes

in the lowland sample was only 82.2%, and that in highland area was just 54.3%

of that of midland.

Table 5.9: Cognisable Crimes under IPC in Low, Mid and High Land Areas

Sample IPC Cases/1000 people (2000)

Rank

Lowland 3.38 2

Midland 4.11 3

Highland 2.23 1

150

Source: Sample Survey

5.3.3 Experiences and Expectations

An attempt had been made to understand the households’ assessment of the

change in their present state of well-being in comparison with that five-years

before. The responses were broadly grouped into three, viz., improved, remained

the same and worsened. The data relating to these from the three areas are given

in the form of a table and percentage bar diagram, in Chart 5.1. Out of the 150

households from each region 74.7% of lowland households, 85.3% of midland

households and 81.3% of highland households reported improvement in their

conditions over the last five-year period. 9.3% of lowland households, 2.7% of

midland households and 5.3% of highland households reported deterioration in

their condition, compared to five years before. The rest of the households stated

that their condition remained to be more or less stable over the five-year period.

Thus, as the maximum percentage of households considering themselves to be

better off and the minimum percentages considering their conditions to be worse

or static compared to five-years before, the midland sample acquired first rank

here. The highland sample came second and the lowland sample third.

It is worth noticing at this point that the lion share of households mentioned

employment and income as the principal cause of improvement or deterioration in

their state of well-being. Better and stable employment to the already employed

and new employment to the unemployed family members were given as the major

reasons for the improvement in household’s condition by the majority of

respondents. Similarly, loss or reduction in employment was attributed as the

main cause of deterioration in household’s level of well-being.

151

0%10%20%30%40%50%60%70%80%90%

100%

% o

f Hou

seho

lds

Chart 5.1: Change in Household's Level of Well-being over the Last 5-year Period

Worsened 14 4 8

Same 24 18 20

Improved 112 128 122

Low Mid High

0%10%20%30%40%50%60%70%80%90%

100%

% o

f Hou

seho

lds

Chart 5.2:Household's Expectation about Future Prospects

Uncertain 4 2 2

Worse 10 4 12

Same 20 18 16

Better 116 126 120

Low Mid High

The survey also tried to get hold of the level of optimism that the

households of different regions possess about their future prospects. Optimism

about the future is, no doubt, a product of experiences and present circumstances.

Four types of responses were observed in connection with the expectations about

152

future prospects—better, same, worse and uncertain. Of these, expectations of

worse or uncertain future, involve distress elements. Chart 5.2 presents the data

and percentage bars of them for the low, mid and highland samples.

It was found that most households in all the three regions had optimistic

outlook about future. 77.3% of lowland households, 84% of midland households

and 80% of highland households reported that they expect better future prospects.

6.7%, 2.7% and 8% of households respectively presented a pessimistic view about

their prospects. 13.3% of lowland, 12% of midland and 10.7% of highland

households did not expect any ups or downs in the immediate future. Relatively

small proportions, 2.7% in lowland area and 1.3% each from the other two areas,

were uncertain about their prospects. Overall, the midland area’s performance was

the best here, followed by the highland sample. The lowland sample came last.

Once again, the majority of respondents considered aspects of employment as the

decisive factor, in deciding their prospects of well-being.

5.3.4 Borda Ranking

The Borda ranking of the three samples were made on the basis of their

performance on the six non-conventional indicators considered for the sample

data, four of which are purely distress indicators. The summery results are

presented in Table 5.10. The highland sample with a Borda score of ten was the

best performer here. In the matter of chronic diseases, short duration morbidity

and crimes, she got first rank, second rank in experiences and expectations and

third in disability. The second position in terms of Borda scores went to the

midland sample. She got first rank in disability, experiences and expectations; but

only third rank in chronic diseases, short duration morbidity and crimes. The

153

highest Borda score and hence the lowest overall rank were given to the lowland

sample. She got second position in disability, chronic diseases, short duration

morbidity and crimes, and third rank in the other two.

Table 5.10: Borda Ranking of Non-Conventional Indicators (Sample Data) Sample Borda Score Borda Rank

Lowland 14 3

Midland 12 2

Highland 10 1

Source: Computed by the Author

The use of non-conventional indicators in the analysis of human

development needs further exploration. What this author had tried here is only a

feeble step, just an attempt to attract scholarly attention to some relatively untried,

yet highly useful, aspects of human development. In addition to the distress

indicators we had employed, one could use several other useful and plausible

indicators like pollution, social unrest, corruption etc. They failed to find a place

in this thesis, only because of the non-availability of suitably disaggregated data

on them. It is the reason for the non-computation of the Child Development Index

that we have discussed in Chapter 2, for the different regions of Kerala also.