Professor Thorat’s Nehru Memorial Lecture to the University of Mumbai in 2006 raises some vital issues of concern. Although the reach of higher education has increased dramatically since independence, it still leaves a lot to be desired at all levels – access, inclusiveness and quality.
Three alternative methods are used to estimate the extent of access to higher education: Gross Enrolment Ratio (GER), Net Enrolment Ration (NER) and Enrolment of Eligible Ration (EER). GER measures access by taking the ratio of persons in all age groups enrolled in various programs to total population in age group of 18 to 23. EER measures the level of enrolment if those who completed higher secondary level education. Data on student enrolment is provided mainly through three sources: Selected Education Statistics (SES), National Sample Survey (NSS) and population Census (PC).
Accurate data is a problem. For example, GER based SES is 8% in 2000. The NSS and PC figures are 10% and 14% respectively. For 2003-2004, the GER work out to 9%, 13.22% and 14.45% respectively. The differences could be because of two reasons: SES does not take into our account enrolment in unrecognized institutions and also some State Governments do not report their enrolment annually. The NSS and PC may even report because their data is collected from households and hence may include those who are doing diploma or training programmes like computer training in unrecognized institutions also. The PC data also does not distinguish between professional degree and diploma programs.
Throat studies disparities under seven hears: (i) rural and urban; (2) inter-state; (3) inter-caste; (4) inter-religion; (5) male-female; (6) occupation group and (6) poor and non poor.
The inter-caste data tells us that in 2003-04, the overall GER was about 13.22%. However it was much lower for ST,SC and OBC being only 5%, 7.5% and 11.34% respectively as compared to 24.89% for others. Between SC/ST and OBC the GER was higher for OBC and between SC and ST, the GER was higher for SC by about 2.5% point. Thus the GER was the lowest for ST.
The PC figures reveal a similar disparity in GER. The general Hindu population excluding SC/ST has a GER of 15.57% and for SC and ST, it is 8.39% and 7.46% respectively. The EER, however, reveals a different pattern. In 2003-2004, it was 54.4% for ST, 57% for SC, 54.8% for OBC and 62.5% for the other Hindu population. This shows that the general Hindu population has a higher EER as compared to SC, ST and OBC but the difference among them are marginal. This implies that although the OBCs, have a higher enrolment rate based on GER, compared with SC and ST, but a smaller proportion of them entered the higher education stream after completing the higher secondary stage that the higher castes.
Now the question arises, why do the SCs and STs have such a low access after over 60 years in spite of reservations in institutions of higher learning. Is there a need to look at other indices besides caste? Thorat himself provides data on some other relevant factors. One is the disparities between rural and urban areas. In 2003-2004, the GER for rural and urban area was 7.76% and 27.20% respectively, the GER inn urban areas being four time higher compared with rural area. The PC figures 8.99% for rural areas and 24.52% for urban areas in 2001, showing the rural area enrolment as three times lower than that of the urban area. The EER worked out 51.1% for rural and 66% for urban areas showing the latter to be about 15% higher.
Second there are wide inter state variations. The GER at the aggregate level is 13% but there are states like Nagaland (38.6%), Goa (27.3%), Kerala (24.2%), Manipur (24.7%), Himachal Pradesh (20.0%) and Jammu& Kashmir, Tamil Nadu and Pondicherry (18%) show more than the national average. There are other states like Tripura (3.2%), Assam (6.6%), Meghalaya (7.2%), Chhatisgarh (7.6%), Orissa (8.2%), Jharkhand (10.3%), West Bengal (9.7%), Bihar (10%), Sikkim (10.8%) and Rajasthan (11%) where the GER is lower than the national average.
The EER is useful as it estimates the access to education to those who have completed the higher secondary stage. In 2003-04, 59% of those who completed higher secondary entered higher education. The ratio is much higher in states like Mizoram (87.1%), Manipur (87.7%), Nagaland (85.6%), Jammu & Kashmir (&^.6%) and Kerala (70.6%). By national comparison the ratio is much lower in Tripura (37.8%), Chhatisgarh (49.6%), Orissa (50.2%), Arunachal Pradesh (53.5%). In the rest of the States, the ratio was around the national average of 59%.
Third, there are variations in the various religious groups. This is seen in the 200-4 figures. The GER is higher for Jains followed by Christians, Sikhs/ Buddhists, Hindu and Islam is 57.43%, 27.29%, 15%, 13.47% ad 8.19% respectively. The EER is similarly different with Jains and Christians on top, their EER being 74.7% and 71.3% respectively. Next come the Buddhists and Hindus with about 60%. The EER is the lowest for Sikhs being 52.8%.
Fourth, the access to higher education is lower for girls than boys. This is mainly because of visible differences in rural areas. Significant male-female disparities also exist in EER. In 2003-04 the EER is 62.9% and 54.1% for male and female respectively. This shows that the girls are 9% points lower than boys. The differences in EER are visible in both urban and rural areas. The gender disparity is aggravated by caste and religion. For instance, in 2000 as against the overall average of 9.4% for the female, the GER was 2,4% for ST females followed by 4.7% for SC females and 7.6% for OBC females and 17.2% for other females. In case of religious groups, the Muslim suffer the most. The GER of Muslim female was 6.3% compared to 10.8% for Hindu females, 12.7% for Sikh/Buddhist females. If we take the EER, we see that it is 50% for SC/OBC females and 57% for ST/other high caste females. Similarly the EER was the lowest for the Muslim female compared to females belonging to other religions being 48% for Muslim females, 54% for Hindu/ Buddhist females, 56% for Sikh and about 69% for Jain/ Christian females.
Poverty creates disparities too. In 1999-2000 the GER for the poor was 2.4% as against 12.91% for non-poor, the average being 10.10%. Similar disparities are seen in rurl and urban areas. The GER for poor and non-poor in rural areas was 1.30% and 5.51% compared to the poor and non poor in urban areas – 7.12% and 27.15% respectively.
Among the poor, the GER was the lowest for ST and SC followed by OBC and others. The GER for the poor belonging to ST, SC, OBC and other is 1.55%, 1.89%, 2.30% and 3.58% respectively. Similar pattern is observed for poor in rural and urban area. In rural area, the GER is the lowest for ST being 1.11% followed by 1.35% for SC, 1.13% for OBC and 1.66% for others. The overall GER is 1.30%. In urban area, the GER for the urban poor is 3.86%, 4.78%, 5.10% and 7% respectively for SC, ST, OBC and others – the average being 5.51%. Among the non-poor, the GER for ST, SC and OBC is lower than for others. The GER for SC,ST,OBC and other respectively is 6.68%, 9.7%, 8.69% and 19.73% respectively. The all India average is 12.81%.
Occupation is another factor, and can be clearly seen across occupation groups in rural and urban areas. In rural are, the GER is generally higher for self-employed households engaged in farm and non-farm economic activity compared with those who worked as wage labour in farm and non-farm activities. The GER for the self-employed in farm and non farm activities was about 5% as compared with 1.41% for farm wage labour and 3% for non-farm wage labour. Similarly in urban areas, the GER was much higher for those engaged in business, regular salaried and other activities as compared with casual labour. The GER was 50%, 28%, 15.74% and 3.21% respectively for other, self employed, regular salaried and casual wage labour. Thus both in rural and urban area, the enrolment was casual wage labour was the lowest as compared with self-employed and regular wage earner and salaried. The GER was particularly low for Farm Wage Labour.
The occupation can be correlated to caste. The GER is generally low for wage labour and particularly low for SC/ST compared to other groups. For instance, while an overall level for wage labour in rural area is 1.41%, that of the ST, SC, OBC and other in this group is o.67%, 1.63%, 1.16% and 1.93% respectively.
Similarly in urban area, the GER for casual labour is 3.26% at over all level as against 1.53%, 2.61%, 3.34% and 4.30% for ST, SC, OBC and other wage labour.
Similar inter-caste differences are observed in case of self-employed cultivator in rural and urban area. The overall GER in rural area for self employed in agriculture is 3%, 3.95%, 4.21% and 8.33% for ST, SC, OBC and other respectively as against an overall average of 5.64%. The GER for self employed in business in rural areas in 2.53%, 3.77%, 3.97% and 7.73% for ST, SC, OBC and other. In urban area, the GER for self employed among ST, SC, OBC and other work out to 6.15%, 7.37%, 10.0% and 22% respectively.
Among the self-employed and wage labour, the emolument is particularly low for the poor among them. For instance, the enrolment rate at overall level for the self-employed cultivator, self-employed in non-farm sector, agriculture labour other labour, other households in rural area is 5.17%, 1.41%, 2.99%, 5.64%, 18.55% respectively compared with 1.43%, 0.86%, 0.37%, 1.78%, 2.98%, 1.30% for poor self employed, self-employed in non-farm sector, agriculture labour, other labour other household respectively.
Similarly in the urban area while the enrolment rate at overall level is 15.74%, 28.10%, 3.26%, 50.15% for self-employed, regular salaried, casual labour and other household respectively, it is 4.59%, .6%, 2.38% and 14.39% respectively for poor households belonging to self-employed, regular salaried, casual labour and other households. In other words, the enrolment is lowest among the poor casual wage labour household in rural and urban area (agriculture labour, other labour in rural and urban area – 0.86%, 0.37% and 2.38% respectively) it is particular low among the same poor group from the ST/SC/OBC. The enrolment rate for agricultural labour for ST, SC, and OBC is 0.9%, .01% and 0.93%. Similarly it is nil for ST and SC and only 0.52% for OBC casual non-farm wage labour in rural areas.
The Diversity Index
The foregoing figures show that there is no one single factor that leads to lack of access to institutions higher education. Gender, poverty, caste, religion, region, occupation, habitation are at least some of the factors that reduce equality of opportunity and deny or reduce access. An expert group was formed to identify rise of concern in the content of unequal access of different segments of population to public space and institutions and propose an appropriate Diversity Index and work out modalities of policies and programe based on the index. This came out of the recommendations of the Sachar Committee which although it was to evaluate and enumerate the conditions of a specific minority group, put forward the idea of operationalizing a broader notion of diversity.
The Sachar Committee had recommended the establishing of an Equal Opportunities Commission. Consequently two expert groups were set up – one chaired by N.R. Madhava Menon to design an EOC and the other chaired by Amitabh Kundu to design a Diversity Index to measure diversity in public spaces of education, health and housing. The Madhava Menon group was to “address the concerns of all deprived groups, with respect to equality of opportunity in education, employment and other sectors in a proactive manner.”
A significant point made in the World Development Report 2006 (Equity and Development) is that disparities arise among different sections of society due to various factors such as caste, gender, schooling, work/occupation and sources of income generation. The report points out that poverty rates computed at national or state levels have only limited utility as they are not of much help in targeting policy towards the poor or those who need special assistance. To do that, poverty figures would be needed at district or even lower levels. That is why a diversity index is needed especially when there is obvious widespread discrimination. It is an attempt to devise a quantitative measure to provide a working estimate of exclusion in specific areas, a measure that can be used for inter institutional comparisons as well as to assess patterns over time. With this objective, the Expert Group was given three areas where diversity should be measured: work, education and living spaces.
Although devising anti-discriminatory practices or identification of the domains of discrimination require a deep understanding of social, historical and political environments, but one needs statistical measures for policy targeting. The use of statistical measures has been a contentious issue but experiences in UK, France, US and Canada amply demonstrate the efficacy of using a properly developed indicator.
It is possible to make a case for reservations in certain specific situations but a long term solution for a systemic change, a system of incentives and disincentives based on a Diversity Index appears to be a more effective and hopefully a more acceptable solution. Every institution needs to develop a non-discriminatory and non-exclusionary framework and must constantly evolve norms and practices that ensure greater diversity over time.
The Expert Group felt that affirmative action through quotas has produced uneven results. Through the diversity index it would be possible to see clearly where a difference has been made and where not. The Sachar Committee has pointed towards under representation of religious minorities in education and workspaces. Trends shows pronounced exclusion and evidence of discrimination at higher levels education or employment which mask the fact that exclusion and discriminatory processes get initialized at much lower levels. The Expert Group strongly felt that its deliberations should transcend the unidimensional division between religious majority and minorities and capture other dimensions of exclusion as well. It felt that there was a need to bring together different kinds of exclusion into a common index which should be able to respond to the requirements of specific policies.
Affirmative action is a set of positive anti-discriminatory policy measures designed to increase the presence of under-represented groups in various social spheres, particularly in preferred positions and levels in the society. Thomas Weisskoff make a useful distinctive between two forms of Affirmative Action: preferential boasts and quotas. India has had a long history of quotas for Scheduled Castes and Scheduled tribes and more recently for Other Backward Classes. Preferential boasts imply implicit or explicit points being given for being a member of the target group. The Diversity Index is an example of preferential boast system. Examples of both are employed internationally.
The case for Affirmative Action for disadvantaged groups can be made both on account of historical deprivation as well as persistence of disparity and continuance of discrimination. For example, historically, communities such as Dalits’ in India or the Blacks in the Americas have suffered deep injustices, disparity, deprivation and discrimination. However, the case for affirmative action on grounds of contemporary disparities and discrimination is highly contentious. Nevertheless there is evidence to suggest that the current economic and social systems perpetuate patterns of group based disparities in all spheres of life, education, occupation/work, income/consumption, health indicators. The continued presence of social and economic discrimination aggravates these disparities across several countries in the world.
Over the years, the manifest discrimination may have toned down and avert biases may be constrained as politically incorrect, but unequal access to not just education but many other common, public or private resources have not disappeared. In a multicultural and highly stratified country like India, where discriminatory practices had societal approval derived from religious sanctions and upper castes practiced untouchability with impurity, a commodity like education was zealously guarded by those at the helm of affairs and the social institutions that developed worked to ensure that it was denied to the untouchables.