INTRODUCTION

In India, tribal-indigenous populations have been historically excluded from mainstream society, culture and civilization. Social exclusion, as the case of these tribes clearly exemplifies, is not simply about poor material living conditions; it regularly draws pejorative moral judgments about those marginalised that work against a favourable reception of their problems, making it more difficult to find appropriate solutions for them.

The economic and social condition of tribal communities is desperate. For instance, the average landholding has declined more rapidly among tribes than among any other social group in India. This reflects the alienation of tribes from their traditional lands largely due to displacement over infrastructure projects or fraudulent transactions (Panda, 2016). Numerous official reports identify tribes as the most excluded section of Indian society: their levels of literacy are lower than those affecting Scheduled Castes; and the same can be said of the former’s poverty rates and health indicators. Shah (2014) points out that in contemporary India, tribes’ living standards are adversely impacted by a series of factors such as money lending, land alienation, deforestation and agricultural displacement. All of these factors combine to produce high poverty rates among tribes. Further, tribes show the highest levels of victimization concerning the incidence of atrocious crimes (Ministry of Home Affairs, 2016; Ministry of Tribal Affairs, 2016; Planning Commission, 2016; Ministry of Social Justice and Empowerment, 2016). Hence, in spite of the significant economic growth that has characterised the Indian economy since the 1990s, the social condition of tribes remains markedly backwards.

The Indian central state and local governments have implemented a number of schemes and programmes aimed at improving the living conditions of tribal populations. Hence our interest in exploring the impact of such development plans with special reference to the plight of tribal populations in the state of Kerala.

TRIBAL POPULATIONS IN KERALA

Kerala houses 484,839 tribal people in 119,788 family units that constitute 1.43 per cent of the total population of the state. Wayanad and the Attappady region of Palakkad are the most populated tribal districts in Kerala. Wayanad has the highest concentration of tribal population (31.2%), followed by Idukki (11.5%) and Palakkad (10 %). The tribes show a very low literacy rate (75.81%) compared to the general population in Kerala. With respect to employment, only 10 per cent of the total tribal population living in Kerala cultivate their own land, whereas 40 per cent are agricultural wage labourers (Scheduled Tribes Development Department STDD, 2013).

The Paniyan (inhabitants of Pudur) represent 22.5 per cent of the total tribal population, followed by the Kurichian (9%) and the Malayarayan (8.9 %). The Malayarayan show an exemplary literacy rate of 94.5 per cent that is comparable to that of the general population of the state. However, the Kattunaikan and Muthuvan show very low literacy rates, 40.2 and 41.5 per cent respectively. The Paniyan is the poorest group among the tribes: only 1.7 per cent of members are cultivators, whereas 65.7 per cent are agricultural wage labourers. Communities like the Kurichian, the Malayarayan and the Muthuvan include a greater number of cultivators, whilst the majority of the Adiyan and Kattunaikan are agricultural wage labourers.

Kerala’s tribal population dwell mostly in the dense forests of the Western Ghats and are thereby cut off from mainstream society. They eke out a living either through rudimentary agrarian set ups or through the open access to forest resources which they exploit making use of traditional skills; they know the ins and outs of the forest and its biodiversity, and the importance of its resources for sustainable livelihood. Nonetheless, tribes usually face the dangers posed by infrastructural projects, wild animals and the harsh climatic conditions of the forest.

A major setback to the self-sustained tribal economy has occurred as the result of Kerala’s proliferated large-scale migration of non-tribes into the prime abodes of the tribal population, seeking to exploit the rich natural resources of the forest. The expansion of the tourist industry in the Western Ghats represents one more factor contributing to the plunder of the forest. Such expansion keeps forest dwellers tied to inhumane forms of exploitation and reinforces the exclusion of most of the 450.000 aborigines of the state (CSSEIP, 2009; Rajasenan, 2010; Rajasenan, Bijith & Rajeev B, 2013).

Over time policy-makers have implemented several schemes and programmes seeking to uplift the tribal population from their present condition. During the 1970s the Indian government introduced the Integrated Tribal Development Project (ITDP).² In Kerala, seven ITDP district offices were created to bring all of the geographically scattered tribes into the development process. The ITDP has the supervisory authority over all the tribal development activities of the state. With the aim of promoting decentralization, the ITDP proceeded to allocate 50 per cent of all tribal development funds directly to local self-governments (Kjosavik & Shanmugaratnam, 2006).

The launching of the ambitious Tribal Sub-Plan (TSP)³ in 1974, the Decentralization of Tribal Development Schemes of 1996 and the passing of the Forest Rights Act (FRA)⁴ of 2006 represent further key signposts in the history of tribal development in Kerala (Chemmencheri, 2013). Nevertheless, in spite of a plethora of central and state schemes and special allocations made the through the TSP, the distress of the tribal communities continues unabated (Rajasenan & Rajeev, 2013; Devika, 2016).

RESEARCH ISSUE

Unequal levels of economic growth and development among distinct social groups in Kerala are the result of marked imbalances in the ownership and control of productive assets such as land. Aside from landlessness, we must point to the existence of high levels of illiteracy, lack of occupational mobility and poor health indicators. Given these facts it is no surprise tribal populations comprise an extremely deprived and vulnerable social group, prompting indelible dark spots in the glorified development experience of the state, widely known as the Kerala Model of Development (Veron, 2001; Govindan & Sreekumar, 2003; Thresia; 2014).

We must note the existence of a culture of poverty among tribes that influences all aspects of their life. Following Lewis (1975) the culture of poverty expresses as an established pattern of adaptive mechanisms that are socially constructed by the poor from elements of their everyday lives, allowing them to survive in very adverse material and social conditions. The concept does not imply, as is usually contended (Valentine, 1968), that it is more important to abolish these adaptive cultural patterns, than to do away with poverty itself. On the contrary, as Harvey and Reed (1996) contend, the concept suggests that under favourable political conditions the poor hold within themselves the abilities necessary to forge their own destiny. Stated differently, if given access to and control of productive resources such as land, assets and expertise, the poor would be able to build and sustain their own communities.

Unfortunately, there are strong countering forces to the social progress of tribal populations in Kerala such as discrimination and the intergenerational transmission of poverty that tend to reinforce one another. In our view, there is an urgent need for the implementation and proper management of policies that are able to place the tribal population’s degree of progress at a par with the social progress achieved by other social groups in Kerala.

The present research sets out to investigate the effectiveness and impact of a number of developmental schemes as they concern two Kerala districts mostly inhabited by tribal communities: Wayanad and Palakkad. The examination follows two different routes. First, we undertook the task of scrutinising the utilization rate of funds pertaining to tribal development schemes in the state. Second, we proceeded to explore the perceptions beneficiaries held in relation to the benefits attendant to such development plans.

METHODOLOGY

The present study is based upon primary and secondary data. The primary data was gathered during 2016 from interviews with household heads in the tribal districts of Wayanad and Palakkad. We selected 200 samples distributed in five clusters, three from Wayanad and two from Palakkad. The sample was determined through the application of stratified random sampling. The fieldwork was based on a household survey comprising 77 questions organized in three modules. We surveyed the head of each sample household and each interview lasted for over an hour. Three prominent tribal communities the Kuruman, the Kattunaikan and the Paniyan comprise the Wayanad sample. Two tribal communities, the Irular and the Kurumbar, comprise the sample from the Attappady/ Palakkad region. We identified the community’s perceptions regards development programmes such as the Tribal Housing Schem⁵, the Integrated Child Developed Scheme .ICDS),⁶ the Mahatma Gandhi National Rural Employment Guarantee Scheme .MGNREGS),⁷ the Kudumbashree⁸ and the Self-Help Groups (SHG).⁹ Factor Analysis (FA) was used to establish the recipient’s perceptions regarding the functioning and management of development plans as a whole. We also gathered secondary data regarding the allocation/utilization ratio of development funds. The process of analysis relied on correspondence analysis, graphical methods and CHAID techniques.

EVALUATION OF UTILIZATION RATES.

The Indian government has allocated a substantial amount of funds intended to improve the living conditions of tribal populations in Kerala. One main purpose of these allocations is to achieve a fairer distribution of the benefits brought about by the Kerala Model of Development between the general population and tribal communities living in the state. Following is a appraisal of the TSP, firstly with respect to the panchayat level allocation and expenditure rate and secondly with respect to the ITDP and TOD schemes

1. Tribal Sub Plan (TSP)/Inter-Panchayat Analysis

Table 1 presents the effectiveness of programmes according to fund utilization rates on a per-rupee basis in various tribal development schemes for the period 2007-2015.

The values range from 0 to one (0 indicates non-spending and one full spending of the allocated funds). Results based on the panchayat level analysis indicate that the Meenangady panchayat of the Wayanad district has a high utilization rate (0.8772) as compared to other panchayats for the 2007- 2008 period. Subsequently, Meenangady fails to achieve this same rate of fund utilization until 2014-2015. Pudur shows a utilization rate 0.1480 which is the lowest spending panchayat in the sample. This result is a cause for concern due to the fact that Pudur is the poorest tribal community in Kerala. In the cases of Kalpetta and Meenangady the utilization rate is more adequate, followed in descending order by Meppady and Agali. Overall, the data show an inadequate and decreasing utilization rate of funds. The issue of underutilization of funds becomes more poignant when we look at the backward condition of the tribes and the actual resources needed to generate a multiplier effect on other targets. Thus, in spite of the impressive allocations¹⁰ associated to several development and welfare programmes, the underutilization of funds makes the schemes destined for tribes’ advancement remain at best limited.

We employed the technique of Chi-Squared Automatic Interaction Detector (CHAID) as an evaluation tool concerning the inferences obtained from the analysis of the variance in the fund’s allocation/expenditure ratio. For this purpose, the values are further categorized into a five-point-scale according to its score, assigned as follows: Low (0.20 and below), Medium-low (0.21-0.40), Medium (0.41-0.60), Medium-high (0.61-0.80) and High (0.81 and above). These values are followed by plotted CHAID prediction model using CHAID algorithm (see Figure 1).

Figure 1
CHAID Diagram for Five Panchayats
Source: ITDP-TDO data, 2015-2016. Our own estimates

Nodes 0, one, two, and three represent five panchayats (Meenangadi, Kalpetta, Meppady, Agali and Pudur). Node 0 represents parent one showing all the utilization categories. Most of the observations fall under a medium- high to high ratio. The second split shows the fragmentation of Node 0 into three terminal nodes: Node one corresponds to Meenangady and Kalpetta; Node two to Meppady and Agali; Node three to Pudur, based on the panchayat with a significant Chi-Square value of 40.968 with eight degrees of freedom. The Meenangadi and Kalpetta results are merged together in Node one, as they do not show any significant differences in the utilization rate. Similarly, Meppady and Agali only show slight differences in the utilization rate as they share Node two. Meenangady and Kalpetta show a high utilization rate of 43.4 per cent in most of the cases, whereas the Pudur panchayat shows the opposite with a low utilization rate of 42.1 per cent in most of the cases.

The CHAID inference concerning the overall fund utilization for the period 2007-2015 based on panchayats, reveals that the Meenangady and Kalpetta regions have a better utilization rate with concomitant development. However, in the case of the remaining three panchayats -Meppady, Agali and Pudur- the utilization rate is low hence contributing to keep these regions mostly underdeveloped and backward.

Inter-panchayat differences in the utilization rate of development assistance are again evaluated by plotting the utilization rate values with the aid of Correspondence Analysis (CA). Table 2 shows significant Chi-Square values and an inertia value of 0.177, which means that the model explains 17.7 per cent of the total variance. The Eigen values (inertia) reflect the relative importance of each dimension. Out of the total variance of 17.7 per cent, 77.6 per cent is explained by the first dimension. Similarly, the second dimension, accounts for 18.4 per cent of the total inertia.

Correspondence Analysis by region and utilization rate (Figure 2) indicate that the Meenangady and Kalpetta regions fall closer to the “High” fund utilization rate; hence the results are comparable to the inferences obtained from the CHAID analysis. A clear-cut difference can also be inferred for the Meppady and Agali panchayats with respect to CHAID and CA, as in CHAID these panchayats appear in Node two, whereas Meppady is closer to the Medium-low level and Agali is closer to the “Medium” level of fund utilization as per CA. These results tell that the Agali panchayat has a better fund utilization rate compared to Meppady for the period under review. In both analyses, Pudur comes close to the “Low” utilization rate.

Figure 2
Correspondence Chart: Panchayat and Fund Utilization for 2007-2015
Source: Source: ITDP-TDO data, 2015-2016. Our own estimates

The statistical inferences shown in Figure 2 are indicative of the overall inadequate fund utilization rate associated to development plans. Indeed, Figure two reveals that most panchayats fall between the medium to low utilization rate.

2. Integrated Tribal Development Project (ITDP) and Tribal Development Office (TDO) Analysis of Utilization Rates

Following we offer an evaluation of the ITDP and the TDO in terms of their utilization rate for various years.

The results presented in Figure 3 disclose that, overall, the majority of development schemes fall within the high utilization rate (0.80 per one rupee of allocation) of funds

Figure 3
CHAID Diagram ITDP-TDO
Source: ITDP-TDO data, 2015-2016. Our Own Estimates

Nonetheless, in comparison Palakkad and Mananthavady TDO show a lower utilization rate. The CHAID analysis does not reveal significant differences between the allocation and expenditure ratio. This is why the CHAID does not develop into a tree level node extension (Figure 3) with respect to the ITDP and TDO based schemes included in the TSP.

Beneficiaries’ Perceptions of the Benefits Attendant to Development Programs

1. Housing Schemes

Financial housing assistance is provided to tribes under various government schemes. Housing assistance is also provided through agencies like the Attappady Hills Development Society (AHADS).¹²Figure 4.a reveals that 77 per cent of the sampled households received government aid under the sponsorship of different housing schemes. Inter-tribal comparisons show that 55.6 per cent of the Kuruman families, 76.5 per cent of Paniyan families and 76.2 per cent of Kattunaikan families received government funds for house construction. The Irular and Kurumban groups received a higher level of assistance for house construction, 86.1 per cent and 90.5 per cent respectively.

Figure 4.a
Received Assistance Under Housing Scheme
Source: Authors’ Survey (2016).

Figure 4.b reveals that nearly the totality of the houses built with government assistance were owned by the household head; however, in the Pudur community 11.5 per cent of the homes were owned by relatives of the household head. The overall results show that the main source of funds for house construction was government aid, linked to different policy schemes

Figure 4.b
Ownership of Government Funded Houses
Source: Authors’ Survey (2016)

Figure 5 indicates, that the majority of respondents were dissatisfied with the financial support received from housing schemes. Nonetheless, few respondents (7.8%) expressed high levels of satisfaction with said support.

Figure 5
Level of Satisfaction with Housing Schemes
Source: Authors’ Survey (2016).

Most of the respondents expressed concerns regarding the shortfall of funds allocated to housing projects. Figure 6 shows that 79.7 per cent of the households receiving support reported requiring additional financial assistance in order to complete their houses.

Figure 6
Additional Funds Required for Completion of House
Source: Authors’ Survey (2016).

On the whole, our data indicate that beneficiaries blamed the limited amount of funds received from housing programs for the poor condition of their homes. Dissatisfaction of beneficiaries with housing support was mostly related to the high costs associated to both construction labour and the transportation of construction materials.

The setbacks associated with insufficient support from housing schemes shows in that only 4.5 per cent of the government funded houses are pucca.¹³ Pucca houses are to be found mainly in areas belonging to the forward Kuruma tribe. Indeed, the majority of Kuruma houses are either semi-pucca or pucca (40% and 20 % respectively). We must note that in terms of educational level, land ownership and income the Kuruma are comparatively better off than other Kerala tribes. These comparative advantages allow the Kuruma to invest their own savings and borrow money for the purpose of house construction (Rajasenan et. al, 2013; Rajasenan, 2015; Rajasenan & Rajeev, 2016a).

Figure 7
Condition of Government Funded Houses
Source: Authors’ Survey (2016).

Figure 7 shows that 94.7 per cent of the houses of the Kurumbar community, a backward tribal group, are semi-pucca. This is an exceptional case owing to the fact that AHADS has taken up the initiative of constructing houses in this area. In this region, the houses are usually completed with proper flooring, windows and doors. The case is that backward tribes such as the Kurumbar and the Kattunaika receive special assistance for house construction; yet, in spite of this support, the majority of Kattunaika houses are kutcha.¹⁴ Such condition is mostly due to the fact that these backward tribes live deep within the forest and have no access to proper roads or transportation facilities. In fact, the Kattunaika colonies are located far away from a proper road. The only way of reaching these colonies is by the use of 4X4 transmission vehicles and even then, visitors and dwellers have to travel through dense forest exposing themselves to the attacks from elephants and other wild animals. The majority of Kattunaika, Paniya and Irular houses are kutcha; thus, their residents reported requiring further financial assistance to complete construction work.

2. The Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS)

Our data revealed that 34 per cent of the surveyed households hold the MGNREGS job card. On average, beneficiaries worked for 1.8 days a week in the MGNREGS and requested to work more days under the scheme. We also found that the MGNREGS is the main source of employment for most women. This finding is in-line with that of Breitkreuz et al. (2017) who found that in Kerala and Tamil Nadu, the rate of women participation in the guaranteed job scheme approached 85 per cent.

Table 4 shows that the Irular and the Kuruma communities register the highest percentage of families holding the MGNREGS job card (43% and 35.6% respectively). On the other hand, participation in the scheme is 23.8 per cent for the Kattunaika, 20.6 per cent for the Paniya, and 28.6 per cent for the Kurumban. As shown in Table 4, 67.60 per cent of the surveyed households relied on the scheme as a critical employment option. The scheme also represented an important subsidiary means of employment for 36.80 per cent of the households. The data at community level reveals that employed members in the Irular, Kurumbar and Pudur households relied heavily on the MGNREGS as a significant source of income.

Table 4

Percentage of Households Holding MGNREGS Job Card and MGNREGS as Main and Subsidiary Employment by Tribal Community

Source: Authors’ Survey (2016)

Table 5 reveals that the MGNREGS income represents a large share of household earnings for the tribes. Indeed, such income represents on average 0.4863 of each rupee household income.

Table 5

Share of MGNREGS Income in the Household Earnings

Source: Authors’ estimations based on field survey data (2016).

The MGNREGS emerged as the main source of employment and income for the Kattunaika households. For their part, the Kurumban and Irular displayed a value of 0.4880 and 0.5158, respectively. The average value is lower for the tribal groups of Wayanad: the Paniya with 0.3640 and the Kuruma with 0.3375. We must note that the Paniya derive most of their income from wage labour, whereas the Kuruma obtain most of their income from farming their own land. The limited workdays available in the MGNREGS determines that a member can only earn an income between Rs. 1,700 and 1,800 per month; nonetheless this discrete income represents a significant amount of money for community members who do not have other sources of employment.

3. Self-Help Groups (SHG) and Kudumbashree Membership¹⁵

The SHG scheme has been hailed in several studies as pivotal in the empowerment of rural women in Kerala. The scheme, it is argued, has contributed to the alleviation of poverty, in the promotion of women’s entrepreneurial capacity and in overall household prosperity (Reji, 2013; Kumar & Jasheena, 2016). However, the scheme’s impact on tribal women has been trivial. Indeed, one indication of the problems faced by SHG in Kerala is the low percentage of tribal women enrolled in the scheme. Figure 8 shows that scarcely 20 per cent of the households included in our sample subscribed to the SHG. The SHG membership is limited to the Kuruman and Irular households, whereas most of the backward tribes in Kerala such as the Kattunaikan, the Kurumban and the Paniyan are far from joining the scheme.

Figure 8
Membership in SHG/Kudumbashree
Source: Authors’ Survey (2016).

Interviewees from the Kuruma and the Irular tribes reported that the SHG were a failure. They stated that the scheme was unable to bring forth income generation activities, to produce regular savings for households, to facilitate access to capital and loans, and to foster labour skills. Another fundamental reason for the failure of the SHG in Kerala’s tribal districts is related to the lack of interaction between tribal and non-tribal populations. This is a very serious problem: Tribes, especially the backward tribal groups, are not allowed to participate in non-tribal SHG. As a matter of fact, the SHG are formally thought of as consisting of people of similar socio-economic standing and who live in close proximity to each other (Planning Commission, 2008). Moreover, non-tribal communities generally refuse to come into contact with tribal groups. Segregation is rooted in various issues such as class and caste stigma, the isolated nature of tribal communities and the prejudiced attitude mainstream society holds in relation to tribal populations (Manuel & Kumar, 2012).

4. The Integrated Child Developed Scheme (ICDS)

Our research assessed the sample’s level of participation in the ICDS. The scheme is meant to provide food supplements to children of different ages and to their mothers. The ICDS also contemplates providing education and health care to beneficiaries.¹⁶ The responses to questions concerning the ICDS are presented in Figures 9.a and 9.b. We found that 110 households were eligible for participating in the scheme, representing 55 per cent of the total sample. Of these 55 per cent of households, 70.9 per cent were enrolled in the scheme.

Figure 9.a
Eligible for ICDS Assistance (%)
Source: Authors’ Survey (2016).

Figure 9.b
Participation in ICDS (%)
Source: Authors’ Survey (2016).

When speaking about the benefits associated to the ICDS, recipients complained about the irregularity of the food supply. The irregularity occurs on account of three related issues: tribal hamlets are located in remote areas, the elevated cost of transporting foodstuffs and the high cost involved for beneficiaries in having to collect provisions in faraway anganwadis.¹⁷

Table 6 shows the various categories of ICDS as these relate to children’s age. Twenty-nine households were eligible for assistance to children less than three years of age; 42 households were eligible for children between three and six years of age; and 56 households were eligible for assistance to girls between six and 14 years of age. Our data indicates that some households were not fully aware of their entitlements under each age category.

Table 6

ICDS Assistance

Source: Authors’ Survey (2016).

Figure 10 presents the opinions of our interviewees regarding the quality of the food provided under the ICDS programme.

Figure 10
Quality Assessment of ICDS Foodstuffs
Source: Authors’ Survey (2016).

Most of the mothers receiving Amrutham (a baby food supplement) were satisfied with the quality of the infant formula and other food items provided through the anganwadis. Mothers rated foodstuffs supplied to children between three and six years of age as moderately good or very good. However, a good percentage of mothers (47.5%) with children between the ages of six and 15 years old said that the food was of low quality. Notwithstanding, all mothers were very concerned regarding the irregular pattern of food supply.

5. Beneficiaries’ Perceptions Regarding the Impact of Development Programmes

A complementary way of evaluating development schemes entails asking recipients about their own opinion vis-à-vis the benefits associated to such programmes. The present section tries to answer these questions relying on Factor Analysis (FA). The Kaiser-Meyer- Olkin test showed the adequacy of our data for Factor Analysis (Table 7).

We gathered information concerning the perception of household heads regarding 12 statements relating to the efficacy of government programmes, the attitude of officials toward community issues and the level of community involvement in decision-making. The answers were recorded in a five-point scale and analysed with the aid of Factor Analysis. Communalities (Table 8) explains the variability in a particular variable accounted for by all factors extracted in the factor analysis

Four factors with Eigen values of more than 1 are extracted (Table 9), which together explain 64.32 per cent of the total variance. The first factor has an Eigen value of 2.746 in the rotated solution, which explains 22.887 per cent of the variance. 16.589 per cent of the variance is explained by the second factor whereas factors three and four explain 13.423 and 11.416 percentages respectively of the total variance.

Due to the inconclusiveness of the component matrix (see Table 10), a rotated solution was sought. Results are presented in Table 11.

The rotated component matrix features four factors. Five statements linked to problems of development assistance feature as the first factor. Statements relating to the role-played by community members in the success of development programmes and attitudes of local authorities to community issues constitute the second factor. The role of local authorities in the success of development schemes emerged as the third factor. As to the fourth factor, tribe members acknowledged that government schemes were sound. Yet, tribes complained about the inappropriate use of funds in the task of uplifting tribal living conditions.

Overall, tribe members reported that present development schemes are a right step in the direction of economic and social development; however, they argued that schemes and plans needed proper implementation, assessment and a scaling up of strategies. By way of example, beneficiaries often experienced inordinate delays in receiving financial assistance and argued that such delays worked against the overall success of development programmes. A second issue of concern was related to the methods employed by official agencies in selecting the household/member beneficiary. The interviewees expressed the view that community participation was a much better way of implementing plans, selecting beneficiaries and providing assistance to the needy. Thirdly, there was concern with the shortfall of funds allocated to some government schemes, specially housing related schemes.

Conclusions

The present paper aimed to evaluate the impact of a number of development programs over the living conditions of tribal populations in the districts of Wayanad and Palakkad. We determined this impact by recourse to two strategies. Firstly, by analysing the utilization rate of funds pertaining to such developmental schemes. Secondly, by gathering information about the beneficiaries’ own perceptions concerning the quality of development programs.

Our data show that fund utilization rates and per-rupee utilization rate of funds are generally inadequate. Most panchayats showed a utilization rate that fell into the medium or low measure. Special attention must be paid to the case of the Paniyan community who resides in the Pudur panchayat: this is the poorest tribal panchayat in Kerala and yet it displays the lowest utilization rate in our sample. By all accounts, efforts must be made in order to increase the utilization rate allocated to this area. It follows that the underutilization of funds makes the schemes intended for tribes’ social and economic advancement limited in their impact.

In relation to housing schemes, we found that 70 per cent of the sampled households received housing support (Figure 4.a.). Also, that 97.4 per cent of the families owned government funded homes (Figure 4.b.). Nonetheless, there were criticisms regarding the housing schemes that vented in two different directions. One related to the need of assuring that homes given under government schemes are well constructed. The other complaint related to the lack of funds needed in order to complete home construction (Fig. 6). It is noteworthy that only 7.8 per cent of the sample expressed high levels of satisfaction with housing schemes (Figure 5).

Likewise, our data indicate that the MGNREGS represented a major share of household income among tribal households, especially for women. Indeed, the MGNREGS represented on average 0.4863 of each rupee household income (Table 5). However, the average income share of the MGNREGS was lower for the tribal groups of Wayanad, as the Paniya derive most of their income from wage labour and the Kuruma from farming their own land. We must also note that 68 per cent of households carrying a job card were willing to work more days than those allowed under the guaranteed work scheme.

In connection to the SHG we found that barely 20 per cent of the households included in our sample were enrolled in the scheme. The Kuruman and Irular household heads expressed the opinion that the scheme was a failure. The respondents pointed to the scheme’s inability to generate regular savings, its lack of potential for capital formation and the low labour skills and educational levels prevalent among members. To these constraints, we must add issues such as lack of interaction between tribal and non-tribal populations which was due to the stigmatization of tribal populations. The low enrolment rate in the SHG among Kerala tribes is a matter of serious concern for the scheme represents one of the most important avenues to foster women’s capacity building, access to productive resources and enhanced position in the household. One strategy for improving the impact of the SHG would be to create SHG-Cooperative frameworks modelled on those which have been implemented in the coastal areas of Kerala through Matsyafed. We refer to fish farms that have been successful in guaranteeing the welfare of fishermen and women by offering members the opportunity to engage in diverse activities such as fishing, commerce, aquaculture, transport and many in-land undertakings (Rajeev & Rajasenan, 2015; Rajasenan, 2016; Rajasenan & Rajeev, 2016).

Respondents were critical of the ICDS. They complained about the irregularity of food supply and the high costs associated to retrieving such foodstuffs. Tribal hamlets are usually located in remote areas, thus creating two problems: problems related to high transportation costs and problems related to having to collect provisions in faraway anganwadis. Most respondents argued that foodstuffs were of low quality. Yet, 74 per cent of mothers with children under the age of three reported being satisfied with the quality of infant formulas.

Overall, the respondents held the view that tribe development programmes were sound. Nevertheless, the beneficiaries raised a number of concerns regarding the implementation of such plans. They expressed the view that plans needed proper implementation, evaluation and a scaling up of strategies. The most important complaints revolved around significant delays in obtaining financial assistance, flawed criteria in the selection of beneficiaries and insufficient funding of housing schemes.

The exclusion of Indian tribal populations is well beyond the mere experience of being poor. Whereas poverty refers to lack of disposable income, exclusion entails a relative loss of social rights and limited access to essential services such as education, proper housing and health care. Moreover, these indigenous groups often find themselves disempowered and oppressed. Hence, the urgent need to evaluate and monitor tribal development schemes by looking at their tangible impacts. Nevertheless, there is also a requirement to examine a number of additional factors that may contribute to the outcome of development plans: The level of commitment of policy makers, the implementing agencies’ mode of governance and the extent of stakeholders’ level of participation in development plans.

REFERENCES

Ashutosh, K., & Jasheena, C.J. (2016). Kudumbashree: Promoting the Self- Help Group Model of Empowerment Through Women Entrepreneurship in Kerala - A Study. Indian Journal of Management, 9(6), 20-34

Breitkreuz, R., et al. (2017). The Mahatma Gandhi National Rural Employment Guarantee Scheme: A Policy Solution to Rural Poverty in India? Development Policy Review, 35(3), 397-417

Census. (2011). Census of India 2011, Registrar General, Government of India, New Delhi.

CSSEIP (Centre for the Study of Social Exclusion and Inclusive Policy). (2009). Human. Development Report of Tribal Communities in Kerala. Cochin: CUSAT

Chemmencheri, S. (2013). Decentralisation, Participation and Boundaries of Transformation: Forest Rights Act, Wayanand, India. Commonwealth Journal of Local Governance, 12, 51-68

Devika, J. (2016). Aspects of Socioeconomic Exclusion in Kerala, India: Reflections from an Urban Slum. Critical Asian Studies, 48(2), 193-214

De Venanzi, A. (2004). Discursive and Social Practices in the Construction of Exclusion. Electronic Journal of Sociology, http://www.sociology.org/content/2004/tier1/venanzi.html.

Govindan, P., & Sreekuma, T.T. (2007). Kerala’s Experience of Development and Change. Journal of Contemporary Asia, 33(4), 465-492

Harvey, D., & Reed, M. (1996). The Culture of Poverty: An Ideological Analysis. Sociological Perspectives, 39(4), 465-495.

Institute of Social Sciences. (2003). Impact of the Tribal Sub-Plan Implementation in Improving the Socio-Economic Condition of the Tribal People with Special Focus on Reduction of Poverty Level Covering the States of Assam and Tamil Nadu, New Delhi

Integrated Tribal Development Project (ITDP). (2015-2016). Attapady Allocation and Expenditure Data, Agali, Kerala.

Integrated Tribal Development Project (ITDP). (2015-2016). Kalpetta. Allocation and Expenditure Data, Kalpetta, Kerala.

Kjosavik, D., & Shanmugaratnam, N. (2006). Between Decentralized Planning and Neo Liberalism: Challenges for the Survival of Indigenous People of Kerala. Social Policy and Administration, 40(6), 632-651

Lewis, O. (1975). Five families: Mexican case studies in the culture of poverty. New York: Basic Books

Manuel, P., & Kumar, D. (2012). Empowerment of Rural Women Through Self- Help Groups. In U Jerinabi and P Santhi (Eds), Creativity, innovation and entrepreneurship (pp. 41-45). New Delhi: Allied Publishers.

Ministry of Home Affairs. (2016). National Crime Records Bureau/Crime in India-2016, New Delhi

Ministry of Tribal Affairs. (2016). Annual Report, New Delhi

Ministry of Social Justice and Empowerment. (2016). Handbook of Social Statistics, New Delhi

Mohan, S. (2017). Indian policy and development: A manual of national schemes and international policies. Chennai: McGraw Hill

National Rural Livelihoods Mission. (2017). Status of Self-Help Groups and Village Organisations under National Rural Livelihoods Mission as of 31.07.2015, New Delhi

Panda, R. K. (2016). Social Exclusion and Inequality: Opportunities in Agenda 2030. Socially Excluded Task Force & Center for Equity Studies, New Delhi

Planning Commission. (2008). A Report on the Success and Failure of SHGs in India- Impediments and Paradigm of Success, New Delhi

Planning Commission. (2012). The Twelfth Year Plan (2012-2017) Social Sectors (Volume III), New Delhi

Planning Commission. (2016). Report on Social Justice, New Delhi

Rajasenan, D. (2010). The Perception-Reality Gap in the Health Status of the Disadvantaged: Evidence from Tribal Communities in Wayanad, Kerala. In D Rajasenan (Ed), Inclusion of the excluded: Dynamics and challenges (pp.10-26). Cochin: Directorate of Publications and Public Relations CUSAT

Rajasenan, D. (2016). Residential segregation and social exclusion among the scheduled castes and scheduled tribes of Kerala. Cochin: Directorate of Publications and Public Relations CUSAT

Rajasenan, D., & Rajeev, B. (2013). Development Dynamics Involved in Tribal Sub Plan. CSSEIP Working Paper, 3(1), 1-30

Rajasenan, D., & Rajeev, B. (2016a). “Poverty and Poverty Correlates of the Marginalised Social Groups in the Rural Belts of Wayanad, Kerala: Role of Policy Aspects for Inclusive Development”, paper presented at the Third International Conference on Social Sciences, Sri Lanka, September 30 to October 1, 2016.

Rajasenan, D., & Rajeev, B. (2016b). “Role of Formal Institutional Linkages in Reducing Poverty and Income Inequality of the Small-Scale Marine Fishers of Kerala”, Journal of Indian Fisheries Association, 43 (2), 7-21

Rajasenan, D., Bijith, G. A. & Rajeev, B. (2013). Health, Education and Employment in a Forward-Backward Dichotomy Based on Standard of Living Index for the Tribes in Kerala. Journal of Economics and Sustainable Development, 4(7), 100-107

Rajeev, B., & Rajasenan, D. (2015). SHGs as an Inclusive Development Option among the Fisher folks in Kerala, Inclusive Development. International Journal of Social Sciences and Humanities, 2 (1), 177-212

Reji, D. (2013). Economic Empowerment of Women Through Self-Help Groups in Kerala. International Journal of Marketing, Financial Services and Management Research, 2(3), 97-13

Scheduled Tribes Development Department (STDD). (2013). Report on the socio-economic status of the scheduled tribes of Kerala, Scheduled Caste Development Department, Government of Kerala.

Thrsia, C.U. (2014). Social Inequalities and Exclusions in Kerala’s “Egalitarian” Development. Monthly Review (February), 28-38

Valentine, C. (1968). Culture and poverty: Critique and counter-proposals. Chicago: University of Chicago Press.

Veron, R. (2001). The "new" Kerala model: lessons for sustainable development. World Development, 29 (4), 601-617.

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