Active Society, Politics & Law History, Languages & Philosophy

Understanding Society Waves 17-19 (Fieldwork Grant 1)

In plain English

AI plain-English summary

Every five years, the UK government and researchers rely on a single, massive survey to track how people’s lives actually change—and this grant pays for the next round of that data collection. Understanding Society follows tens of thousands of households over time, asking about income, health, employment, housing, and family life. Without it, policymakers would have to guess whether a new benefit system actually lifts people out of poverty, or whether a housing policy reduces homelessness. The survey fills a critical gap: it captures real-world outcomes, not just intentions or projections. If this fieldwork succeeds, the resulting data will shape decisions across government departments—from the Treasury to the NHS—for years. It will help design more effective social policies, target public spending where it works, and reveal hidden inequalities that cross-sectional snapshots miss. The project is primarily a data infrastructure investment, not a single experiment. Its impact is indirect but profound: every major UK social policy evaluation in the coming decade will likely draw on these waves.

View original technical description
This grant is for the fieldwork costs for waves 17-19 of the main survey and waves 18-20 of the innovation panel of Understanding Society: the UK Household Longitudinal Survey (2024 to 2029), as approved in grant ES/Y003071/1.

View the original record at the funder ↗

Researchers

Michaela Benzeval (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Understanding Society Waves 6 to 8
Understanding Society: The UK Household Longitudinal Study: Waves 9-11
Understanding Society: The UK Household Longitudinal Study extension for Wave 12
Understanding Society Waves 17-22 - centre activities
UK population lab innovation development grant

Original classification

Research Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.