Who counts in poverty research?

Area of Science:

• Social Sciences
• Poverty Studies
• Sociology

Background:

• Mainstream poverty analysis in high-income countries creates social hierarchies, valuing some deprivations over others.
• Existing methods obscure the prevalence of deep poverty and the experiences of those most affected.

Purpose of the Study:

• To examine how poverty analysis hierarchies corrupt social scientific understanding.
• To highlight the exclusion of hyper-marginalized groups from income surveys.
• To demonstrate how data practices lead to policy blindness regarding deep poverty.

Main Methods:

• Critical analysis of conventional poverty measurement approaches.
• Examination of data quality and coverage issues in income surveys.
• Focus on the UK context to illustrate gendered, racialized, bordering, and ableist practices.

Main Results:

• Conventional approaches obscure deep poverty and its victims.
• Hyper-marginalized groups are missing from surveys, skewing poverty estimates.
• Data quality improvements can worsen the representation of low-income groups.

Conclusions:

• Current data practices systematically exclude marginalized populations, leading to epistemic erasure.
• This exclusion results in policy blindness to severe poverty and exploitation.
• Addressing deep poverty requires a fundamental rethinking of data collection and analysis.