PARTE DOS

Here I describe how I created the variables which were not used in the regressions but could be helpful in exploring trends in the data. The scripts used to extract the data from various sources will be made available on GitHub.

5.6.1.1 Trend in the Electricity Supply

I used the daily satellite imagery that Brian Min3 _{was able to get from NOAA-NASA.}

Images between 1994 and 2003 were used as the electricity sector was privatized after 2003. Once we have time-series data for every village, we need to come up with a summary measure. I am interested in a measure of the trend over time. A positive trend would indicate a more steady and reliable delivery of electricity while a negative trend would imply the reverse i.e., unsteady and unreliable. The measure that I use is the autocorrelation of the extracted values for every village. A positive autocorrelation would be interpreted as evidence of steady and reliable electricity supply while a negative autocorrelation would be interpreted as the opposite. Figure 5.10 shows the spatial distribution of the autocorrelation measure.

Figure 5.10: Reliability of electricity supply (red is high reliability and green is low reliability)

5.6.1.2 Trend in the Area under Double/Triple Crop

Similar to the idea behind the measure of the reliability of electricity supply, I develop a measure for the area sown under double/triple crops. Growing two or three crops through the year requires a steady supply of inputs such as water and electricity for irrigation and other inputs such as labor, seeds, fertilizers and machinery. In the case of Gujarat, the crops that come under this category are generally cash crops such as cotton and tobacco. A sustained increase in the area which is sown with such crops requires the reliable provision of services such as water and electricity from the state.

I was able to acquire annual satellite imagery from ISRO’s Bhuvan portal beginning in 2005 and ending in 2012. These images classify different types of vegetation into 12 categories such as wasteland, forest land, urban build up, fallow, winter crop, summer crop and double/triple crop. I calculated the average proportion of land classified as “double/triple crop” across all the years. An autocorrelation measure is not meaningful here because there is not much variation in the proportion of land classified as double/triple crop. Figure 5.11 shows this variation.

Figure 5.11: Trend in the cultivation of the proportion of double/triple crop (red is a high average and green is a low average)

5.6.1.3 Numerical Strength of the Largest jati

I used the 2016 electoral rolls that are publicly available on the Gujarat State Election Commission’s website. This data is however very difficult to work with. It is in a PDF format and it is in the Gujarat script. Raphael Susewind4 _{however has downloaded all}

the PDFs and extracted the text using OCR. He has put his data into a SQL database which can be queried by users. The data is about 30GB and he shared it with me.

I wrote Python scripts that extract the data from the SQL database, put it in a CSV format and transliterated the Gujarati surnames to English. To this I added the polling station name which also happens to be the name of the village. In order to merge this to the larger data set, each village had to have the unique census code. As doing this manually for 18,000 villages would take a lot of time, I wrote a Python script which automated this process by matching village names in the two lists - electoral rolls and

village census directory5_{. When names matched, the village in the electoral roll was}

assigned a unique census code from the village census directory.

Once we have the names of all the electors by village, it is easy to assign ranks based on the proportion of each jati which is calculated by counting the number of individuals with the identical last name. Figure 5.12 shows this variation.

Figure 5.12: Proportion of the surname with a majority in a village

5.6.1.4 Distance to the nearest Swaminarayan Institution

There is not much scholarly work on the Swaminarayan movement in Gujarat. In 1986, when Makrand Mehta published an article in the Arthat, a publication based in the Centre of Social Studies, and edited by Ghanshyam Shah and Achyut Yagnik, followers of the sect harassed Mehta, Shah and Yagnik and sued them in the high court for the publication of an article which hurt religious sentiments6_{. While I have not been able to}

5 _{Some villages can have identical matches. In order to get around this the matching was based on a}

combination of district name, sub-district name and finally the village name.

6_{https://www.indiatoday.in/magazine/education/story/19880531-research-paper-on-swaminarayan-sect-} triggers-off-controversy-797283-1988-05-31

find a copy of the article, I have spoken with Achyut Yagnik who brought to my notice the role that sects play in the transformation and preservation of caste based behavior.

The location of all the BAPS institutions are publicly available7_{. I scraped all the}

addresses and used Google Maps to geocode the exact locations i.e., longitude and latitude. With this information the distance between a village and all BAPS locations were calculated and the minimum distance was finally used. Figure 5.13 shows this variation.

Figure 5.13: Distance to the nearest BAPS temple

Chapter 6 Conclusion 6.1.0 Introduction

In this dissertation I have tried to account for why some villages exhibit higher levels of discrimination while others manifest lower higher levels? I endeavored to provide a framework for understanding variation in discrimination by using insights from the literatures on state-building, distribution of public goods and social movements. I tested the implications of the proposed theoretical framework on data from the western state of India, Gujarat.

In brief, I first provide some historical context around the issues of caste and untouchability. I show how prior to Independence, caste was privatized i.e., it remained outside the jurisdiction of the colonial state. Post-Independence, certain aspects of caste, namely untouchability, came under the purview of the state. Despite what seems like to be a clear mandate for the state to address untouchability, the issue is far from being addressed. I attributed this to the inherent ambiguity in the law which one, does not define untouchability and two, protects the freedom to practice the religion of one’s choice (and consequently follow caste rules) but simultaneously makes illegal untouchability (which are caste rules grounded in religion). It is at this point that I argued that the state becomes embroiled in an intractable conflict over the place of caste in society. This ambiguity allows for a variation of interpretations of the law by the citizens of the country. While some interpretations are in the direction of transformation, others tilt towards preservation.

I then proceeded to argue that whether untouchability is preserved or transformed depends in the interpretation of the village-level upper-caste elites. Specifically, I contend that untouchability is jointly produced by two levels of interactions of the village- level upper-caste elites. One with the state and the second with their own caste communities in the village.

There are two types of analyses that I conducted to test my hypotheses. I did an exploratory content analysis of all the articles published in Gujarat on the topic of untouchability in the Times of India (1838-2009) to examine the narrative around caste and untouchability across time. And second, I used the Navsarjan study to create a valid measure of untouchability. I also put together a novel village-level dataset of covariates which would be used for the quantitative analysis.

In the next part of the Conclusion, I summarize the five chapters. This is followed by contributions made by the dissertation. And I end by identifying some shortcomings of this dissertation project and identify areas of future work.