What Ethnographic Interviews Suggest: The Unwritten Rule

Introduction

In late May, I moved beyond survey responses and spent time in a village in Ratnagiri, speaking with 11 residents, mostly domestic workers and small-scale farmers, along with one retired BMC officer. People were initially hesitant. Rapport emerged through small talk, and only then did stories about schemes begin to surface. Responses were often partial and guarded, but together they outlined a system in which access appeared personal, political, and fragile.

Life and work context

Women between 45 and 75 often described balancing housework with plantation or nursery labor. Men largely described farming. One disabled farmer had never applied proactively; another described waiting months for agricultural support. Welfare frequently appeared as a late supplement to decades of underpaid or unpaid work.

Access pathways: how schemes enter people’s lives

Panchayat officers emerged as the primary gateway in many accounts. Most residents described learning about schemes through personal visits and offline paperwork: Aadhaar, ration cards, land records, thumbprints. Attempts to self-apply often appeared to stall. Changes in local leadership could freeze progress abruptly.

Inclusion and exclusion: who gets in, who is left out

Perceived fairness often hinged on politics and discretion. Several respondents suggested that a change in Nagar Sevak altered outcomes. Eligibility rules felt selectively applied: some households with sturdier housing were said to receive support while poorer families did not. Corruption was suspected, but rarely challenged directly.

Trust in systems and technology

Despite limited digital literacy, many respondents expressed the view that computers might decide more fairly than people.

This created a striking tension: hope in machine neutrality, alongside major barriers to using digital systems directly.

Identity and discrimination

Many Kunbi respondents described little overt discrimination today. Some raised concerns about reverse bias; others sounded resigned, neither strongly expecting nor demanding benefits.

Citizen suggestions and local knowledge

• Better roads, parking, and a dam to manage monsoon water.
• Underground wiring and lower electricity bills.
• Peer learning, with beneficiaries encouraging others to apply.

Four themes that stood out

Closing reflection

These interviews add human texture to the survey material: dependence on officers, politics that bends rules, and a persistent longing for impartiality. Lived experiences complicate the cleaner edges of charts. Beneficiaries often stay quiet, caste may be downplayed yet still present, and resignation can coexist with hope.

Looking ahead: can machines really do better?

If many villagers place hope in computers as fairer than people, what happens when algorithmic systems enter welfare delivery? In Part 4, I explore where such systems may help, where they may harm, and how SARAL was imagined as a transparency layer rather than a human replacement.