Short Abstract

How do statistical models shape what becomes visible in African policy, and whose experiences remain unrepresented? This panel examines data gaps, model choices and missing voices across health, development and public services.

Long Abstract

Across Africa, decisions in health, development and public services increasingly rely on surveys, censuses, administrative records and statistical models. These sources can reveal inequalities, geographical patterns and changes over time. However, the evidence they produce depends on whom researchers count, what they measure, how they classify people’s experiences and which analytical methods they apply. Populations omitted from sampling frames, respondents unable or unwilling to participate, and experiences that do not fit standard categories may remain poorly represented.

This panel aims to examine how data and statistical models shape understandings of African societies and influence policy decisions. It invites papers addressing survey coverage, missing data, measurement error, model assumptions, spatial aggregation, algorithmic exclusion and the use of quantitative evidence in allocating services and resources. Contributions may also explore how qualitative research, local knowledge and community participation can identify gaps in official statistics and improve the interpretation of results.

The panel asks: Whose experiences become visible through data? Who remains absent? How do national averages conceal regional and social inequalities? How do researchers’ methodological choices affect the conclusions presented to policymakers? Bringing together statisticians, demographers, public-health researchers, social scientists and policymakers, the panel seeks approaches that produce credible, locally informed evidence while recognising the limits of measurement.

Keywords: Africa, statistical models, survey data, missing voices, measurement, data gaps, knowledge production, inequality, public policy.

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