@unpublished{praninskas2026enfranchisement,
  author = {Praninskas, Gailius and Munroe, Ellen},
  title = {Did Enfranchisement Lead to Representation?},
  year = {2026},
  note = {Job Market Paper}
}

Did enfranchisement make Parliament more representative of the population? If so, was it because politicians from poorer backgrounds were elected and advocated different policies, or because politicians of every background responded to what the new voters wanted? We study Britain’s democratisation, from a property franchise to universal suffrage, combining biographical records of Members of Parliament (MPs) with over 17 million probate (wealth-at-death) records to place politicians, their fathers and enfranchised voters in the same wealth distribution from 1858 to 1990. In the 1860s the typical MP’s father was 3,100 times as wealthy as the typical man; by the 1980s, 10 times. In parliamentary debates, MPs from poor families advocated for policies benefiting the poor, and spoke on issues poor voters cared about. We attribute at least one third of the change in MPs’ background wealth to the franchise — among MPs who entered Parliament at the same election, those who started their political careers under a wider franchise came from poorer families. The parties that fielded poorer candidates won more seats where more of the electorate was poor, and their gains after enfranchisement were largest in the constituencies with the most new poor voters. MPs already in office did not advocate more for the poor when their electors grew poorer; the change came from newly elected MPs from poor families. The costs of standing limited the effectiveness of early enfranchisement acts. The poor entered Parliament only once the unions and the Labour party paid for their candidacies. Enfranchisement helped Britain transition from plutocracy toward a common-interest state primarily by changing who sat in Parliament.

• 2026: Linnaeus Inequality Summit; KIZ Political Economy Workshop; HYRCE Liège; 2nd Warwick–LSE Political Economy PhD Conference; LSE SPEECH
• 2025: Royal Economic Society Annual Conference; Danish Historical Political Economy Workshop; 14th Annual Lithuanian Conference on Economic Research; Warwick–LSE Political Economy PhD Conference; Oxford University Political Economy Work in Progress; LSE Political Science Political Economy Work in Progress; LSE SPEECH
• 2024: LSE Workshop on Institutions and Political Economy; LSE SPEECH

Do political dynasties matter? This depends on how such dynasties are transmitted. Political dynasties sustain themselves by passing on two assets: economic and political capital. We merge the family trees of British MPs and other elites with individual wealth-at-death records since 1858 and show that both assets predict whether a dynasty continues. Over time the relative risk of entering Parliament has fallen for the sons of the rich and risen for the sons of MPs and other elites. The two assets have different consequences for competence and accountability. The sons of MPs enter Parliament earlier and more often than the sons of equally rich men, are more likely to reach government. Once there, they speak less. The sons of the rich, in contrast, take different positions from other MPs but are promoted no more often.

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Human uplift studies, or studies that measure the effects of AI access on human performance via randomized controlled trials (RCTs) or similar methodologies, increasingly inform frontier AI governance and deployment decisions. While RCT methods are robust in other fields, their interaction with the distinctive properties of frontier AI systems remains underexamined, particularly when results are used to inform high-stakes decisions. We present findings from interviews with 16 expert practitioners with experience conducting human uplift studies in domains including biosecurity, cybersecurity, education, and labor. Across interviews, experts described a recurring tension between the standard causal inference assumptions upon which human uplift studies rely and the object of study itself. Rapidly evolving AI systems, shifting baselines, heterogeneous and changing user proficiency, and porous real-world settings strain assumptions underlying internal, external, and construct validity, complicating the interpretation and appropriate use of uplift evidence. We contribute (1) a synthesis of methodological challenges in human uplift studies, mapped to risks to study validity and classified by their degree of specificity to large language model (LLM) systems, and (2) a mapping from challenges to proposed solutions.