When the government of India passed the three “Farm Laws” in 2020, it could scarcely have expected the scale of the protest that was to follow. The laws were an expression of a free-market logic applied to agriculture: Buyers and sellers could now transact with minimal middlemen, set market-determined prices, and gradually open up alternatives to the government’s Minimum Support Price (MSP) regime. In crafting the laws, policymakers took for granted two seemingly obvious caveats: first, that middlemen and informal social networks were hindrances to farmers, and second, that the flexibility available would lead to expected gains in an open market.
The government worked in some critical protection mechanisms in Clauses 5 to 8, including the guarantee of a minimum price to be paid (not, however, the MSP – a guaranteed price paid to farmers each year to procure their produce), protection of sharecropper rights, advance payment stipulations, and protections against land takeovers. The laws appeared to represent the harmonious marriage of market-driven gain and the welfare state’s watchful oversight. Although no projections on expected gains were offered, the Farm Laws were meant to drive the government’s goal of doubling the income of farmers by 2022.
So what happened? The protests revealed the strength of the formal and informal social networks binding arhtiyas (middlemen) and farmers, the distrust of large-scale privatized farm models, the importance of the Minimum Support Price as both a financial and psychological standard, and the unambiguous reality that farmers knew what regime they wished to work under. A series of miscalculations, including the rushed passing of the laws and the government’s paternalistic statements on farmer welfare, aggravated the protests and led to an eventual repeal of the laws.
Herein lies an informative lesson on the perils and drawbacks of the government’s policy approaches – understood independently of their connected political choices, which, one could argue, played a greater role in the chaos than the actual laws themselves. The first error was to presume that the lure of exponential gains driven by the free market would override all other financial and social considerations. The government had completely misread the importance of such factors as trust, informal kinship, skepticism, and subjective appraisals of the existing regime. In fact, it appeared that these issues had never been considered in the first place, ostensibly because they could not be measured. Instead, a simple financial target – double the income – was married to an accelerating logic – the free market – to push the laws through. Measurement and target-setting, two lynchpins of quantitatively-driven policymaking, proved useless.
The second error lay in viewing “stakeholder consultation” as a figurehead exercise, designed to force through the government’s thinking. It was clear that the government’s position – introducing “private investment” to the agriculture sector – was unpopular not because it was inherently unjust, but because farmers distrusted the specter of large corporations who could, in the long term, force them to accept disadvantageous margins without the safety net of government procurement. Understanding this chimera, and finding equally subjective, empathetic ways to address it, proved beyond the capacity of the government’s advocacy machinery.
The classic pitfall of policymaking is that it is inherently a top-down affair. Such terms as “stakeholder-centric,” “locally empowering,” and “impact-driven” lose their meaning at critical junctures, revealing their hollow subjectivity. The question is: Why must we shy away from subjectivity? Why must policy be an objective, inflexible monolith, driven by objective targets and goals that have no appeal to subjective, emotional actors? With the Farm Laws, could it have helped the government to dive into these subjective considerations, dismiss the apparently unimpeachable benefits of the free market, and address farmers’ fears with empathy and transparency?
Under the classical top-down model of policymaking, where there exists both an objective and subjective difference between policy-makers and policy-takers, we would never have unearthed these concerns. No matter how well-intentioned, when policy is drafted without adequate attention to the subjectivities on the ground, it runs the risk of falling into a gap – specifically, a gap in perception, not outcome. Overcoming this gap within the chaos of the farmers’ protests would have required more time, more empathy, and, crucially, far more humility. In other words, it would have required policymakers to think like an average farmer, perhaps even to become one. This is the juncture at which qualitative research methods come in.
Qualitative research methods are often misunderstood as being far too subjective, descriptive (as opposed to prescriptive), and time-consuming to be used as policy tools. For example, ethnography, which involves the researcher “embedding” themselves into the research context, analytically observing their subjects, and noting the dynamics seemingly between the lines, seems far too granular to service the lofty, multi-scalar aims of policymaking. Yet, one might argue, just one ethnographic study conducted over a few weeks in mandis (wholesale depots) in Punjab and Haryana would have uncovered the subjective considerations that eventually led to the downfall of the Farm Laws.
Qualitative methods, dismissed far too often as being too nebulous and unrealistic for policy, can in fact be revolutionary analytical tools. The core understanding behind qualitative methods – that an analytical approach can be brought to bear on a research arena in harmony with its subjective social dynamics – is hardly revolutionary. Yet a true understanding of the power of this subjectivity, and the pitfalls of seeing people and stakeholders as units who think and operate linearly, is screamingly obvious. If outcome gains are expected – confirmed, even – they still do not speak to the fears and expectations underlying how people interpret them. That would require us to start from the bottom and move upwards, embodying the centricity of the stakeholder in spirit, not just practice.
Investing in qualitative methodological innovations for policymaking is of paramount importance. In fact, within illiterate, poor, and underserved populations, there is no way to ascertain how the policies that affect them are being interpreted outside of investing genuine time and energy into understanding their subjective concerns, however irrational they might seem to even the most well-intentioned of bureaucrats.
There are several examples of such attempts to track subjectivities. These can help both uncover and generate innovative policy efforts. In India, David Mosse’s well-known observational study of a typical Development Project – involving donors, local actors, contractors and professionals – received much interest because it laid bare the dry, cynical realities of formalized development efforts. These, he argued, were driven primarily by “organizational exigencies and the need to maintain relationships,” not robust policy itself. This is not, in itself, a surprising observation – aid agencies look for structured, explicit output measures, including progress reports, change trackers, and year-on-year comparisons. It stands to reason that disadvantaged communities – even entrepreneurial and well-organized ones – may not have the resources and the literacy to make development “legible” to foreign donors. Therefore, as Mosse found, development is enacted via a more streamlined, frustratingly bureaucratic path, much to the chagrin of the focus communities.
Stefan Ecks, an anthropologist, used ethnography as a tool to understand how Kolkatans respond to medical treatments for psychological ailments. He found that psychopharmacology in Kolkata embodied a range of patient-healer relations, and that doctors would often resort to local idioms and less-than-scientific vocabulary to ensure patients were given the care and medicines they needed. Such insights, while situated in Kolkata, could help mental health practitioners all over India. Given that the National Mental Health Survey of India found in 2016 that 10.6 percent of India’s adult population suffers from some form of mental morbidity, a deeper grasp of patient fears and subjectivities could go an enormous distance toward providing adequate mental health care. If one considers contemporary issues, such as vaccine hesitancy, the potential gains are all the more palpable. Researchers have already considered and investigated some of these possibilities.
There are real lessons to be learned from these research approaches, as complex and effort-intensive as they are. Of course, because public policy and the academic disciplines that most frequently utilize interpretive approaches – sociology and anthropology – are pedagogically distinct and often mutually suspicious, problems arise. Ethnographic observations and interview transcripts can often appear frustratingly dense, obscuring the “heart” of the issue that policy practitioners are looking for. They are also often grounded in theoretical frameworks that can seem prohibitively verbose and labyrinthine. On the other hand, impersonal and quantitatively grounded top-down policy approaches may continue to miss their mark, worsening the rift between the two streams of thought.
There are at least two ways to address this gap. The first is to place those who will benefit from a given policy front and center, and avoid theoretical or argumentative deviations that obscure their relevance. The second, even simpler, approach is to know one’s audience. If an anthropologist writes for an audience interested in policy outcomes – and not the intricate theoretical webs woven by existing academic literature – they will by necessity pay attention to remaining accessible, clear, and specific. Policymakers, on the other hand, might do well to introduce their understandings of field subjectivities and variations into policy documents, instead of attempting to identify clear, consistent causal chains. The “rift,” so to speak, is artificial. Policymakers have much to tell ethnographers, and vice versa. In a country as diverse, populous and complex as India, those conversations could spark new, innovative approaches to policy.