They build our cities and infrastructures yet are invisible to us while hiding in plain sight.
Case Study-“The Labour Chowks” of Delhi
In the evening, the four-way crossing outside the Sikandarpur Metro station seems like any other in the National Capital Region (NCR). Cars honk, vendors sell their wares, and a Metro train hums on overhead tracks that bisect the intersection. But between 7 and 11am, the crossing is transformed. Hundreds of men, and a handful of women, crowd on to the pavement, jostling for space. They have travelled great distances, mostly from Uttar Pradesh and Bihar, but also from Jharkhand, Chhattisgarh, and West Bengal. For a few hours every morning, this crossing functions as one of the NCR’s largest informal labour markets or chowks. Migrants assemble in the hope of finding temporary employment, primarily at construction sites that dot India’s expanding urban landscape.
Most of these migrants have not permanently relocated their families to the city. Instead, they circulate between village and city several times a year. Such circular migrants are an important population in India, with estimates suggesting they number between 60 million and 90 million.
However, surveying of these populations has been hampered by their high mobility, the informal nature of their urban worksites and residences, and their lack of official city-based IDs. Absent systematic information, our portrayals of these communities remain premised on stereotypes or anecdotes, and broadly fall into two camps. Most often, migrant communities are assumed to replicate village society in the city, and stay tightly wedded to their caste communities. Alternatively, they are described somewhat romantically as breaking with caste and adopting class-based identities and attitudes practically upon arrival.
Will caste or class prove more important within poor migrant communities in India?
To address this question, extensive fieldwork conducted at labour chowks across Delhi-NCR and Lucknow. And a large survey of 3,018 migrants, sampled from 58 chowks across both cities. The survey revealed striking insights about these populations, including that the close correspondence of caste and class in village life is broken within them.
Instead, the sample showed them to be ethnically heterogeneous yet economically homogeneous. On the one hand, 27% were from Scheduled Castes, 44% from the Other Backward Classes, 18% from the upper castes, and 12% were Muslims.
On the other hand, the average income of these social groups was practically identical—75% earned less than $2 per day. Also, 77% had no secondary education, and 74% had no household electric connection in their home villages. Such homogeneity sharply contrasts with survey data from the rural regions from which respondents came, in which the economic well-being of these same groups varied sharply.
Given the unique nature of their urban communities, circular migrants frequently engage with equally poor migrants of different caste backgrounds. The survey sought to understand whether class or ethnicity (caste or region) proved more important in such interactions across four key arenas of migrant life in the city.
First, whether ethnic divisions exacerbated competitive animosities at work. At labour chowks, competition manifested in the practice of wage-cutting, when one migrant undercut another to gain employment from prospective employers. Did migrants feel more negatively towards wage-cutters who come from a different ethnic group?
Second, if ethnic differences impeded willingness to share rented rooms with another migrant. Contrary to popular opinion, most respondents did not have prearranged roommates from their home villages. Instead they found roommates at the chowk itself.
Third, if migrants were less willing to support informal “market leaders” of their chowk who were from dissimilar ethnic backgrounds.
Finally, how much caste and region mattered in shaping migrant preferences for political candidates running in destination city elections, and in their rural regions of origin.
These attitudes were tested by an experiment in which migrants were presented with four short vignettes about a fictitious migrant wage-cutter, a migrant seeking a roommate, a migrant aspiring to be market leader, and a political candidate. The caste and regional profile of the fictitious migrant/candidate was randomly manipulated by varying their name and the state from which they had come. Respondents were then asked to evaluate the fictitious migrant/candidate. This protocol allowed to assess if these evaluations varied if the migrant/candidate was from the same or different caste or regional background as the respondent.
The results of this experiment push against portrayals of migrant populations as either completely retaining or discarding village-based ethnic ties. Respondents did sharply discriminate against migrants from other castes or regions when picking roommates, informal chowk leaders, and political candidates from their rural region of origin. However, ethnic differences did not exacerbate animosities towards wage-cutting migrants or reduce support for urban political candidates.
Why do poor urban migrants sometimes divide along caste lines, and sometimes unite across them?
Follow-up interviews suggested migrant attitudes are sharply affected by the presence of urban elites. Wage-cutting was seen as a practice engineered by exploitative employers who “make us cut each other’s rates so they can pocket more”. Importantly, migrants believe these elites perceive and treat them in class (and not ethnic) terms, noting “you think these maliks know I am a Brahmin? We are all just labour (to them)”. Such uniform mistreatment helped unite migrants when evaluating wage-cutters among them.
A similar logic informed the low salience of caste in evaluations of urban political candidates. Much of the motivation for voting on caste lines stems from expectations that politicians will disproportionately reward their co-caste supporters.
Such beliefs hinge on politicians actually knowing the caste of their supporters, as migrants believe rural candidates do. Respondents believed urban politicians viewed them as an undifferentiated lump of “labour log”. By contrast, decisions about whom to select as a roommate or chowk leader take place within migrant communities, away from the unifying presence of urban elites. In such decisions, ethnic differences continued to divide poor migrants of the same class.
Clearly, the simplified folk wisdom serving as our basis for understanding complex and multifaceted migrant communities is inadequate. Far more research is needed on these so-called “invisible” populations who build our cities, while hiding in plain sight.
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In a diverse country like India, where each State is socially, culturally, economically, and politically distinct, measuring Governance becomes increasingly tricky. The Public Affairs Index (PAI 2021) is a scientifically rigorous, data-based framework that measures the quality of governance at the Sub-national level and ranks the States and Union Territories (UTs) of India on a Composite Index (CI).
States are classified into two categories – Large and Small – using population as the criteria.
In PAI 2021, PAC defined three significant pillars that embody Governance – Growth, Equity, and Sustainability. Each of the three Pillars is circumscribed by five governance praxis Themes.
The themes include – Voice and Accountability, Government Effectiveness, Rule of Law, Regulatory Quality and Control of Corruption.
At the bottom of the pyramid, 43 component indicators are mapped to 14 Sustainable Development Goals (SDGs) that are relevant to the States and UTs.
This forms the foundation of the conceptual framework of PAI 2021. The choice of the 43 indicators that go into the calculation of the CI were dictated by the objective of uncovering the complexity and multidimensional character of development governance
The Equity Principle
The Equity Pillar of the PAI 2021 Index analyses the inclusiveness impact at the Sub-national level in the country; inclusiveness in terms of the welfare of a society that depends primarily on establishing that all people feel that they have a say in the governance and are not excluded from the mainstream policy framework.
This requires all individuals and communities, but particularly the most vulnerable, to have an opportunity to improve or maintain their wellbeing. This chapter of PAI 2021 reflects the performance of States and UTs during the pandemic and questions the governance infrastructure in the country, analysing the effectiveness of schemes and the general livelihood of the people in terms of Equity.
Growth and its Discontents
Growth in its multidimensional form encompasses the essence of access to and the availability and optimal utilisation of resources. By resources, PAI 2021 refer to human resources, infrastructure and the budgetary allocations. Capacity building of an economy cannot take place if all the key players of growth do not drive development. The multiplier effects of better health care, improved educational outcomes, increased capital accumulation and lower unemployment levels contribute magnificently in the growth and development of the States.
The Pursuit Of Sustainability
The Sustainability Pillar analyses the access to and usage of resources that has an impact on environment, economy and humankind. The Pillar subsumes two themes and uses seven indicators to measure the effectiveness of government efforts with regards to Sustainability.
The Curious Case Of The Delta
The Delta Analysis presents the results on the State performance on year-on-year improvement. The rankings are measured as the Delta value over the last five to 10 years of data available for 12 Key Development Indicators (KDI). In PAI 2021, 12 indicators across the three Pillars of Equity (five indicators), Growth (five indicators) and Sustainability (two indicators). These KDIs are the outcome indicators crucial to assess Human Development. The Performance in the Delta Analysis is then compared to the Overall PAI 2021 Index.
Key Findings:-
In the Scheme of Things
The Scheme Analysis adds an additional dimension to ranking of the States on their governance. It attempts to complement the Governance Model by trying to understand the developmental activities undertaken by State Governments in the form of schemes. It also tries to understand whether better performance of States in schemes reflect in better governance.
The Centrally Sponsored schemes that were analysed are National Health Mission (NHM), Umbrella Integrated Child Development Services scheme (ICDS), Mahatma Gandh National Rural Employment Guarantee Scheme (MGNREGS), Samagra Shiksha Abhiyan (SmSA) and MidDay Meal Scheme (MDMS).
National Health Mission (NHM)
INTEGRATED CHILD DEVELOPMENT SERVICES (ICDS)
MID- DAY MEAL SCHEME (MDMS)
SAMAGRA SHIKSHA ABHIYAN (SMSA)
MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE SCHEME (MGNREGS)