Fatima Bi, who are you voting for?

The majority of pollsters got it wrong about Trump, about Brexit and the Modi victory in India in 2014. What gives? How can experienced, smart pollsters get it wrong in three different democratic settings? Besides the obvious need for introspection for liberal politics, there is also a need to understand why polls get it so wrong. I had written earlier of the difficulty of conducting surveys in India, and this is a follow-up to that – here, I reflect a bit more on surveying itself.

I think two aspects are important in thinking about the usefulness of polls in predicting elections. First, social cleavages are far more complex than anyone can imagine. Prediction polls tend to paint people in broad strokes but people are complex beings with multiple identities. And belonging in one group (e.g. white women) does not mean that you subscribe to all views that members of that group are expected to hold (eg. support for Hillary Clinton).

A related dimension is that polls look for outcomes and rarely engage with the why that underlies decision-making.  At different points in time, individuals may exhibit similar behaviour, but they are for entirely different reasons. In the absence of surveys capturing this information (many do not), the we are left with information that captures apparent choices, but not causes. This is significant – during fieldwork, I it puzzling as political relations in two parts of the field site were vastly different, though the party ID of voters was the same. It was only when I was able to move myself away from inquiring about party preference towards understanding why political relations took a particular form that I was able to understand shifts and changes better. I realised that particular material conditions brought about peculiar forms of political relations which allowed voters to switch more easily. Capturing the presence of these conditions helped me predict outcomes better.*

Second, the the existence of social desirability bias and our ability to capture it also needs re-thinking. The existence of the bias itself is unquestionable – we all want to seem better than we are. For example, during fieldwork here in India, voters of the BJP in a Congress dominated area who chose to share their choice with me did so in secret.* Similarly, in the US, in the face of demeaning characterisations for Trump supporters (not just his politics), it is quite likely voters shied away from committing support to seem like somebody else. Surveyors identify shy voters by looking at other behavioural traits – for instance, an inclination to oppose migrants and outsourcing may be seen as tacit support for Trump. But social desirability extends to these as well.

A related issue arises from confirmation bias – it is a tendency for us all to confirm initial hypotheses, beliefs and attitudes. In the US electoral context, Trump started out as a non-serious candidate and later on, he received little support from the GOP. On the other hand, the Democratic campaign was serious, Hillary Clinton had contested in the primaries earlier and it was widely believed she would win. This possibly fuelled pollsters assumptions and combined with people’s desire to appear better and compromised predictive ability.

In sum, surveys are an instrument whose efficacy is complicated both by the surveyor as well as t he surveyed. Lack of knowledge about the why and social desirability bias come together to refract the results.

*This desire for secrecy may be linked to the flows (or perceived flows) of benefits locally – these are often linked to party ID

Address illa -2 : De-monetisation, identity and the migrant poor

In a move to curb black money, counterfeiting, and fight corruption, India de-monetised two currency notes today – the INR500 and INR1000 ones. I rushed about to find these notes to keep (for memories’ sake, you know), debated the silliness of my friend owing me money for what are essentially pieces of paper as I gave her INR 1000, and contemplated how to live cash free in urban India. At some point I even tried to sell the notes I have at higher values as memorabilia. Droll indeed.

The new changes mandate that anyone with these currency notes seeking to have the equivalent value must exchange this in a bank or a post office. The idea is that this will bring dishonesty surrounding these notes out – counterfeiters will not be able to get notes exchanged, and hoarders will be left with piles of useless paper if they don’t whitewash their holdings. Presently hoarded money will possibly come out as a result of this move, but unfortunately, this is a bit like easing constipation –  it is unlikely to prevent being stopped up in the future.

So far, there doesn’t seem to be much that is terribly wrong. Except this – in order to exchange money, you need to show a valid ID to the bank/post office. In the past, I have written about the difficulties the urban poor, particularly migrants, face in getting access to identity documentation. Because so many of them live in shanty towns and slums with no documentation to show for their occupation, they lack ‘address proof’, a crucial step to securing identity documentation. Even Aadhaar, which is reliant on biometric information, requires proof of address.

The absence of ID documentation creates big difficulties for the poorest in accessing the formal banking system for liquidity. This is particularly hard for women, who more often don’t have IDs. Never has the digital divide been so wide. This policy consequently creates the space for intermediaries to emerge. Local leaders who have IDs offer to covert money for the poor in exchange for a fee, which I see already happening in some of the communities I worked in. Brokerage and intermediation are not always bad, but when brokers are able to position themselves in an all or nothing scenario (no cash without ID), they are able to extract greater value for themselves, at the expense of the poor.

A spot of sunshine in this bleak story for poor migrants – many migrant workers in the construction industry, do not receive salaries, but are paid lump sums. This means that the employer (usually the broker/maistry) keeps monthly payments, giving workers a weekly “stipend”, and pays over the balance every few months or so, usually prior to a trip home. In these cases, the money held by migrants is notional, and they can withdraw from their mastery when they desire, hopefully with new INR2000 notes.

Overall, however, the numbers of poor affected by this policy is high as many industries in urban areas are reliant on cheap, undocumented migrant labour from the same or neighbouring states. For a poor migrant, whose savings are usually in the form of high-denomination banknotes stuffed with immense care into a wallet, this move will thus be adverse. Migrants are just one category of individuals who transact (and often save up) in cash – there are plenty of others.

The wide reach of the Aadhaar and the Jan Dhan programmes may minimise some of the difficulties with this move, and people may move to a cashless economy. Until that is established, offer change to your fellow citizens.

Poor servi (and a first world problem rant)

I am the partner in the household responsible for ensuring that appliances (fridge, oven, microwave, dishwasher, washing machine) work well. Electronic goods have troubles, and that means I have a lot of experience trying to get things fixed. In my years of experience, I have learnt that service quality is uniformly bad. Poor responsiveness, lack of communication, professionalism and timeliness, and slipshod repair practices are uniform across brands.


I find that service centres, and therefore the brands they represent, rarely think in terms of the problem being solved by the use of a machine – which, for me for example, is to keep the kitchen running. Thus, with the dishwasher, ensuring there are clean vessels every day is the problem I am trying to solve.  Instead of aligning themselves to solve this, brands market themselves as being well-manufactured (Siemens to a large extent), cool-looking (Siemens – “For a kitchen, worthy of your living room”), or based on the latest technology (e.g. Videocon Satellite a/c). While some do make references to the tasks actually being done (Videocon claims its washing machines are “cleanliness meets comfort”*), others rely on bizarre marketing platforms completely unrelated to the function of the good (I just saw an ad for Panasonic life conditioners – that’s what they call A/Cs btw).

Service centres/service teams are aligned accordingly. So when you contact a service centre, you try to tap into a system that is aligned towards NOT solving your fundamental problem – namely, having clean vessels every day. Rather, the orientation is towards just fixing the machine.  It may seem a subtle point. But it has never, ever occurred to anyone in any service department I or my friends and family have encountered** that the machine is just the means to solving a bigger problem. Which is why it took 4 visits from Samsung to tell me how to prevent the problem that was occurring with my washing machine. And over 2 months for the Siemens manager to offer a standby dishwasher.

It is hard for me not to think that this is a problem that has its roots in gender. Women are responsible in most (if not all) households for clean vessels, food on the table, and a few thousand other things. Machines are  means to solve these problems, not ends in themselves. However, companies’ service departments, reflecting the poor gender ratios in Indian workplaces, are populated by men.

The gendered structure limits the ability to see service problems like the end-user woman does (a dirty vessel to clean vessel transition every goddam day). Rather, it may be viewed in terms brand alignment and commitment. Service quality parameters are therefore often set on turn around times, responder politeness, number of rings, etc. I have even filled out one form that asked me if the clothes of the repair man were alright. And marketers therefore continue to focus on life conditioners and ‘comfortable’ washing machines.

The real implication is that the user and the seller are never seeing the problem the same way. Solutions, therefore, are also limited in their creativity. Offers like standby machines, service providers to clean up, etc are non-existent. Repair professionals don’t even bother to clean up after themselves!

Of course, capital doesn’t care to solve for anything but profitability/growth, but I’m still waiting for a service centre to at least say “we are sorry you have a mound of dirty vessels” instead of just “our service parts are imported from Germany, that’s why it takes longer”.

(I don’t mean for this theorising to exculpate sheer incompetence and lack of professionalism, which may be more proximate/elegant explanations.)

* I am yet to understand the import of ‘comfort’ in the context of a washing machine.

**  I did a brief survey among friends and family members.




Where is Fatima Bi? Reflections on conducting surveys in India

The political and social context of a research site may influence the availability, character and quality of statistical information, especially those studies reliant on electoral lists for randomisation. Using my quest for Fatima Bi for an interview as a metaphor, I contemplate the local political factors that influence the construction of electoral lists and voting, and intermediate the ‘availability’ of data. I argue that these factors accentuate or attenuate local trends, and thereby impeding the interpretation of studies.


After several months of ethnographic work in Area X, I plunged into preparing a survey – making questionnaires, poring over maps and seeking electoral lists from which to sample respondents. I intended to use a strategy frequently used in randomized surveys in India – I selected respondents for interviewing randomly from official voter lists. I marched out on enthusiastically on a clear winter day through the narrow gullies of Area X, printed questionnaires in hand, ready to interview my first respondent, Fatima Bi.

But where was she? Fatima Bi simply could not be found. Frustrated, I sought the counsel of a local NGO worker who informed me that some recently prepared voter IDs had wrong addresses. Together, we asked several individuals in the neighbourhood and, a few hours later, we finally found Fatima Bi.

Here, I use my struggles in implementing a probabilistic sampling strategy and my quest for Fatima Bi as metaphors to reflect on the political realities that distort quantitative work. The promise of neutrality has been at the basis of the surge in quantification in political research, which in turn relies on the ability to randomise. Random samples represent the larger population from within which they are drawn, and thus, sample characteristics can be said to be true of the population. In the coming sections, by describing the machinations in the preparation of voter lists and instances of vote-buying in Area X, I will argue that statistical findings are constituted by context within which they are instantiated and animated, and a statistic, therefore, is a creature of the space it is born in.

Preparation of voter lists

In the few days prior to elections, all parties put ‘leaders’ to work to boost enrollments from potential voters.* These efforts are usually undertaken in the last weeks before enrollments close. Support from political aides during these pre-election enrollment drives involves filling up and collecting forms, following up at the office of the Electoral Registration Officers responsible for electoral lists, and securing and delivering the Election Photo Identity card (“EPIC” or “ID card”).

Those involved in such work claim to be unconcerned about voters’ loyalties and perceive the process of procuring IDs as “social work”** rather than as a partisan effort. There is a debate amongst scholars as to whether parties target marginal voters or loyalists with clientelistic benefits. In Area X, for the delivery of ID cards, parties indeed target loyalists. P, a local Congress leader tells me, “Every party must help their people, is it not?”. Moreover, though the majority of Area X voters have IDs due to government enrollment efforts in the early 2000s, newer voters, mainly migrants, report that they go to their party leader for IDs.

Arguably, in the face of equal effort by all parties, roughly equal proportions of loyalists would be enrolled. Thus, the proportion of voters in the electoral list that support any party may be unaffected, not troubling the randomization process. Here’s the rub – in fact, leaders’ personal ambitions and party interactions with these leaders combine to influence the rate of enrollment.

Leaders ambitions determine the level of investment in the enrollment process. D, a Congress party leader prides himself in his long-term service to the poor. His years of service have earned him the post of nominated member of the municipal corporation , a senior position that gives him status within Area X. Several posters stand testimony to this. A crucial requirement in order to complete enrollments is ‘boys’ to do the required oDaTa (running around). In the few nights before lists close, D leverages his power, generated from his formal position and years of service to engage several local youth to enroll voters. D is politically ambitious and has contested the municipal elections in the past. In contrast, P has lesser goodwill, and is unable to marshal resources.

Additionally, political parties use different approaches in managing ground level networks, also affecting enrollment rates. In Area X, the Congress party is reliant on leaders such as P and D, and other lower level leaders managed by them, who have been nurtured over time. In contrast, the BJP, which is newer in Karnataka is reliant on leaders it engages during election. These workers are otherwise inactive and, unlike P an D, are not entrenched in the bureaucratic systems for enrollment. BJP in-charge for Area X does not even live in Area X.

A peculiar factor is that Area X has several residents from Area Y, which is in a neighbouring assembly constituency and was recently evicted. I found that 7.5\% households in Area X had formerly lived in the evicted area and this proportion represents close to 200 households . Many of these voters continue to vote in Area Y, though some have been enrolled in Area X. While this is a temporal occurrence, studies relying on random sampling in Area Y will be unable to find these voters as they now reside here. Dynamism of neighborhoods due to migration and movement is a feature of urban life and contributes to a significant discrepancies in voting lists.

Thus, election lists in Area X likely do not represent the population that ultimately votes. Temporal factors, like these shifts combine with voter list preparation practices to bring in or exclude voters whose preferences may not have been included in pre-election survey research.

Vote buying and turnout buying

A focus within the clientelism (very simply, the exchange of goods, public or private, for votes) literature has been to determine the motivations of the actors (brokers, voters, party bosses) in the process. While clientelistic practices may undermine the fairness of a democratic process, deeply rooted systems of reciprocity are unlikely to complicate probabilistic research as sampled voters may indicate their preference for clientelistic parties even when surveyed. However, some practices of vote-buying, such cash for vote exchanges have the potential to seriously undermine sample-based survey research as they are concealed and furtively implemented in the days prior to elections. In this section, I describe particular practices of vote-buying in Area X that I have encountered.

In a perverse form of vote-buying in Area X, parties are able to magnify the proportion of votes they actually win by preventing turnout of opposing partisans. Local workers of both major parties allege that parties “purchase” voter IDs of impoverished loyalists*** of the opposing party prior to elections to ensure that they do not cast their vote. Setting aside the normative and legal implications, this practice reduces the monitoring costs associated with targeting goods to voters (leaving only the cost of the good and distribution costs), and is an effective tactic in first past the post systems. The moral turpitude involved makes the precise extent hard to discuss, investigate and verify. However, in accordance with the literature, if the poor are particularly vulnerable, such practices may result in lesser proportions of the poor on voting day than the electoral lists suggest.

Other strategies are also used to prevent or encourage voters to support particular parties. In Area X, voters are made to swear on religious texts that they will vote for a party, others have stated that they were threatened with water disconnections and denial of social entitlements (such as cancellations of ration cards) if they do not vote for a particular party. The instrument varies with the individual and the community, as does the target, and one interviewee told me, “these leaders know our vices!”.

In the case of Area X, these practices lead to a distortion of voters’ presence on election day. The particular vulnerability of the poor to practices of vote-buying may lead to their absence at the pooling booth. This presents a serious challenge to the ability of random samples to represent the views that find utterance (or not) on voting day.


The combined effects of practices of voter list preparation and vote buying in Area X presents a challenge to the expectation in probabilistic research that proportions within the survey sample roughly represent the proportions among those who will vote. Pre-election spurts of enrollment may drive increased presence of certain types of voters; similarly, vote buying by political parties influences who appears to vote as well as the actual vote choice itself. You see, even if Fatima Bi is found, it is not certain that her actions on voting day are in accordance with her survey responses.


* The preparation of voter lists, though overseen by the Election Commission and administered by the Bruhat Bengaluru Mahanagara Palike in Bangalore, is in often controlled by local party workers and leaders. The current system of enrolment allows voters to apply for an election photo identity card and submit relevant proofs. Many voters are unable to cope with the cumbersome process and consequently rely on external help.

** “Social work” is a term freely used in Area X for services rendered where the beneficiary does not directly compensate the service provider.

*** It is generally expected that the poor are most vulnerable to offers of targeted goods as the marginal utility of a particularistic good (usually cash) is higher for the poor.


Some levity

I don’t know how this started, but a long time ago my brother (who is at Purdue) and I got in a fight. When we were little, we used to punch each other and that settled most disputes. Of course, as adults, we can’t do that, so we compose verse. I can’t find the poem he wrote, but here’s my response anyway:

From the depths of Purdue those that cannot climb,
Abandon logic for quite terrible rhyme,
They flail about and string words together
And hope to hell that they can leave the nether.

But rhyme that’s both piteous and pompous,
Can’t really substitute a moral compass,
It reeks much of seedy desperation,
Appropriate, though for the Boiler station.

The Lion, meanwhile, continues its stately roar,
Columbians rise to the sky, evermore,
Mayors, Bookers, Winners of the Nobel,
Pulitzers, Presidents – ’tis greatness hard to quell.

So, darling brother, would you please forget,
This piteous poetry and the empty threat?
My dear Columbia, my alma mater,
Will boil the Boilers and them will slaughter.

Some notes on the BBMP elections

Here are a few preliminary findings from the data on the BBMP elections. I use publicly available data (2015 is here, and a big shout out to Thejesh GN who provided the 2010 data). Where possible, I use my fieldwork insights to buttress findings and arguments.


BJP flags at a polling ‘office’

A little boy in Congress paraphernalia

Story of the peripheries

First, both in 2010 and 2015, the probability of a BJP win increases as you move further away from the centre of the city (taken as the GPO – pin code 560001). This remains the case after controlling for the level of SC and ST population (they are not traditional bases of support for the BJP),  Janaagraha’s ward quality scores (2010 and 2013), turnout and number of candidates. In the case of 2015, I also controlled for 2010 outcome and being in the same as the party in the Assembly for both 2010 and 2015. Preliminary regression analyses bear this out, though further robustness checks and perhaps better controls are required.

When one visualises the data on a map as KarthikS has shown so helpfully, it is not so apparent perhaps. The Congress has had some success in the peripheries, notably in the northwest and in the east. It also appears that the Congress has won the outermost wards. To be sure, I checked the relationship between probability of an INC win and distance from the GPO – it is a negative relationship. The BJP has also won a few seats in the South and the West, mainly in the Jayanagar, JP Nagar constituencies, considered as BJP strongholds.

These exceptions are interesting, and every ward has a story. But, there is a bigger picture. Why does the BJP appear to do better in the peripheries? I think there are a couple of reasons. First, the peripheries in Bangalore have large proportions of skilled professionals from all parts of India. The BJP has adopted, since 2014, various strategies and channels to engage with them. For instance, there are Facebook groups which communicate with these individuals. The BJP also held, at least in 2014 language-based events to cater to groups among these professionals. There remains some spillover effect from these.

Second, local leaders’ orientation matter. Poor migrants who live in the outer peripheries frequently live in shadowy settlements. Their continued occupation of public land is tied up with being on favourable terms with petty politicians. The votes of residents on occupied land is almost entirely controlled by these local leaders’ party affiliations. The availability of booth-level data has facilitated monitoring, and residents feel compelled to vote for the party that these leaders recommend.

Now, this in itself does not tie up to any particular party affiliation, as there is constant churn among local leaders – in my field sites, I have encountered leaders who have stood in various elections from all the three major parties. Though it is hard to statistically verify these, I find that these leaders are frequently oriented to the BJP. This may also explain their strengths in the peripheries.

Housing and the elections

I studied the relationship between the number of unauthorised households* and the probability of a BJP win in the regression context above. In 2010, the probability of a BJP win decreased with increases in the number of unauthorised slum households. In 2015, this increased. Needless to say, this needs to be verified further (something I am up to over the next few weeks) but the change is noteworthy.

Why/how did this happen? Affiliates of the BJP such as the RSS and other Sangh organisations have continued their social service in slums of the city. These movements are avowedly apolitical, but in the 2014 elections several such organisations campaigned actively for the BJP. This good work has probably acted as a foundation, and continued efforts by these organisations have helped. While they did not actively campaign this time around as far as I could see, it is not possible to dissociate them from the BJP, and a spillover effect remains.


Interestingly, very little has been written about the performance of the previous BBMP and its effect on the election*. Between 2010 and 2013 (the two years when Janaagraha conducted its ward level quality assessment), ward quality scores had actually declined. The decline was greater in the BJP wards than in the INC-led wards**. There was also the garbage crisis of 2014, which continues in many parts of the city until now. noticed in my fieldwork also the lack of emphasis on the performance of the BBMP. Informants regularly mentioned the failures of the Congress government in power in the state, or that the achche din weren’t here yet.

Party Average of change in WQS
BJP -1.10
INC -1.04

The reasons are multifold. FIrst, some others were probably just replicating their vote in 2014 in part due to fatigue – Bangalore voted in 2013 (Assembly) and 2014 (Parliamentary) elections as well. It was difficult for a new set of issues to emerge. Second, perhaps local elections are just a reflection of broader political trends. The emphasis on the performance (or lack of it) of the Congress at the state level to a large extent dominated the debate, where issues were discussed. Given that the BBMP has little power in important issues on housing and urban poverty, the evaluation was focused on the state government which is responsible for these.

Missing women: Gender

There are three dimensions to gender. First, the Election Commission statistics show that only 48% of the enrolled women voted, while 50% of the men voted. This meant that the overall difference was that ~208,000 more men cast their vote then women. There is a whole lot of interesting jugglery that is possible with those numbers about the value of a woman’s vote in comparison with a man, but the broader point is that about a 1000 women voters per ward did not cast their vote. Why?

Second, I find that in the 25 seats reserved for women in 2010 but not in 2015, the two major parties nominated ONE woman between them***. The nominated woman did not win. There were 3 women winners in the in wards not reserved for women, and they were lone candidates (all other candidates were men). Evidence from Bombay suggests that women are more likely to win in reserved constituencies – something that does not seem to bear out in Bangalore.

Third, I conducted my fieldwork in a reserved ward. I was there for 15 days prior to the election for half a day, sometimes all of it. I rarely saw the women candidates from the BJP and the Congress. Their husbands were at the forefront, greeting voters and managing everything. Even the one time that the INC candidate came, she stood several steps behind her husband and the man was introduced. Voters were told that the gentleman, Dhanraj (name changed) would take care of all their needs. I only saw and met the independent candidate. Of course, this may be because the campaign split up and the candidates were in other parts of the ward. However, the area I research in constituted more than 50% of the votes in that ward. Local leaders gleefully told me the women were ‘dummy’ candidates.

These aspects must give us pause. Of course, there is evidence in some states that the number of women voters is steadily increasing, a very different ‘silent revolution’ than Jaffrelot contemplated.  During my fieldwork, many women I interviewed told me that they would listen to the patriarch. Yet, some others told me, as I left after the interview, that they would do what they pleased in the privacy of the voting booth. Thus, in the absence of insightful research into the dynamics of political decision-making within households, the silent revolution is likely to remain one of turnout and not participation. Next, the issue of women’s candidature and participation is something to consider. Even in a reserved ward, women candidates are ‘absent’. The consequences of such absence renders reservation policies nugatory and perhaps parties and civil society need to take steps to ensure that reservation translates into continued election of women into positions of power.


There are a few things to think about in the context of these findings. First, the geographical patterns in the outcome is noteworthy and warrants further investigations with more rigourous quantitative and qualitative work. My fieldwork suggests that there are differences in the local forms of mobilisation and political information flows in the centre versus the peripheries. This is perhaps more pronounced among poor voters in the centre versus the peripheries. Second, the causes for the seeming turnaround of the unauthorised households is also something that warrants more interrogation. What is happening on the ground? Are parties targeting voters differently; is it the youth? Next, the singular lack of emphasis on performance issues is noteworthy and troubling. In a city that is grappling with multiple issues, this disengagement and apathy is something to be discussed. Last, the gender dimension of participation must be discussed and debated further.

* The link to the Janaagraha website seems to be broken. I am currently away from home and unable to verify the proper interpretation of the WQS data.

** I have excluded JD(S) from this analysis. I also do not debate the components of the score or the process used to arrive at it.

*** I sorted these manually by scrutinising the name to determine gender. This has some weaknesses, and if someone has an updated list of gender, I would be grateful.

Bangalore’s catch-22

The struggle for an official identity
(This post appeared in identical form in the Asia and the Pacific Policy Society blog ‘Policy Forum’ on Aug 12, 2015. http://www.policyforum.net/bangalores-catch-22/. Many thanks to the team for the many edits and feedback.)

In Bangalore, there’s a cheery greeting– address illa! It literally translates to “no address”, but is a reference to not having known where someone was for a while. As I began my doctoral fieldwork in the city, a lot of people greeted me this way.

It became a metaphor for the work I was doing. My quest to understand politics among rural-urban migrants in Bangalore revealed something startling – entire communities in many parts of the city do not possess any form of identification because they lack an address, a city address being something migrants have great difficulty obtaining. For the poor, access to state utilities and program entitlements is contingent on having one.

In the decade since the 2001 census, the urban population in India has grown faster than the rural population, though urban fertility rates have remained lower. Urban growth has therefore arguably come from internal migrants, both rural and from smaller urban towns. While Bangalore’s migrants in the 1960s and 1970s came from large-scale government enterprises and the growth of small-scale industries, more recent numbers have been spurred by the growth of the Information Technology (IT) and IT enabled Services (ITeS) sectors, which in turn spurred a construction and real-estate boom. This industry relies significantly on cheap and plentiful migrant labour.

Image supplied by author.

The most recent (2011) Census data on migration is not yet publicly available, but 2001 data reveals that Bangalore has the third highest number of migrants after Delhi and Mumbai. Some 45 per cent of these are from other states. Perhaps Bangalore’s proximity to two state borders (Andhra Pradesh and Tamil Nadu) is an explanation.

Elites who migrate to work in the IT and ITeS sectors settle into plush apartment buildings. In stark contrast, poor migrants who come into Bangalore live in tenuous living arrangements with no security or documentation, in visibly poor conditions. Many are squatters on public land under litigation or ‘no-persons’ land, such as land near railway lines or dried-up lakebeds. Some are able to “rent” huts from private landowners, with no prospect of access to legitimate “address proof’’ documents, while others live on construction sites; there is increasing evidence of large construction companies having a captive workforce.This shadowy existence implies that poor migrants are unable to produce any acceptable proof of their residence in the city.

Access to almost any form of identity documentation is predicated upon address proof. This includes, ironically, the Aadhar card, one of the proposed features of which is the emphasis of biometric markers at the expense of markers like address.

Having a proof of address is a pre-requisite for securing a range of identity documents which certify that the bearers and their households are entitled to specific public programs. For instance, the ration card represents access to the public distribution system. Access to programs for subsidised food, gas, and even applications for housing is predicated upon having identity cards, which, in turn, require “address proof”.

The most basic and direct consequence of migrants’ tenuous living arrangements is therefore the inability to receive certification for public programs. It is also hard to find formal or permanent employment if one lacks identification.

Image supplied by author.

The lack of legitimacy does not just have consequences for individual migrant households. Even in long-term settlements, state agencies are unwilling to supply water or electricity as these provide security and become the basis of claims for regularization, which comes about when residents with access to essential services approach state authorities for the allotment of titles and regularization of their occupations. In the absence of these services, occupants are more easily moved. Consequently, entire communities lack access to vital public utilities like water and sanitation. In Bangalore, migrants end up paying INR 3-5 (AUD 5c-11c) for a two-litre pot of poor-quality water  – and they have to walk some distance to get it. Similarly, communities lack sanitation or access to waste disposal systems, compounding public health vulnerabilities.

Besides the economic and social exclusion that results from inhibited access to social protection and public goods, migrants also face political exclusion. Internal migrants are affected by the political choices they make (or not make) as they remain within India. Of course, like all state-authorised identification, the voter ID card also requires proof of address.

Though the rules relating to preparation of electoral rolls do provide a neat little exception – in the case of a “homeless person”, a Booth Level Officer can visit the place where the person sleeps to ascertain if that is the “address”. Although most voters and local leaders I interviewed do not seem to be aware of this provision. The consequence is the absence of a significant proportion of the voting age population from the electoral rolls in urban areas, in positions of power, and ultimately, in the decisions of elected bodies.

It all comes down to an address, and here’s the rub – the “good proofs” of address, perhaps those such as the Aadhar card, themselves require a “good proof” of address, such as registered rental agreements or sale deeds. So, in order to get a card that acts as a proof of address you need proof of address. If there is a Catch-22 set in Bangalore it could be titled Address illa.

For any benefits of the inevitable urbanisation to reach all Indians, public policy “wonks” and scholars have to wrap their heads around the direct issues of lack of access to programs and labour markets, as well as broader notions of social, economic and political exclusion that migrants face in cities. But first of all, it is necessary to ask what social programs mean if migrants have no identity.