Active Society, Politics & Law Public Health & Healthcare

QUALREP: The Quality Of Women's Political Representation

In plain English

AI plain-English summary

In five European countries, researchers are tracking how well women from different backgrounds—including the most marginalised—are actually represented in politics, not just how many of them hold seats. This matters because even where women are elected, many still receive poor representation. Minoritised women, in particular, often find their interests ignored. At the same time, populist movements increasingly use anti-feminist rhetoric to undermine gender equality, and crises such as climate change and pandemics risk pushing women’s concerns further down the agenda. The project fills a gap: there is little systematic evidence on what “good” representation looks like for diverse groups of women, or what conditions produce it. If successful, QUALREP will produce a conceptual framework and methodology that can be applied globally. This could give advocacy groups and policymakers a concrete evidence base for demanding reforms—not just in parliaments, but in how policies are designed and who gets heard. The research is fundamentally about democratic accountability: understanding when representation actually works, and for whom, so that political systems can be held to a higher standard.

View original technical description
Achieving women's equal political participation and representation is formally recognised as a key global priority by the international community, yet there is enhanced recognition that representative democracy has failed to deliver political equality for all women. Descriptively under-represented in the world's democracies, women, especially minoritised and marginalised women, experience something far short of 'good' representation. These are moreover 'troubled times': we face potentially devastating natural and human-made crises (climate change, global pandemics, and economic inequality and insecurity). The rise of populism not only contests the value of representative democracy to respond to these but does so frequently by deploying anti-feminist and antigender claims that threaten women's rights and undermine gender equality. Evidence outlining how and when women in their diversity are well represented in politics is needed to sustain the necessary political will on behalf of domestic and global actors to counter anti-democratic and anti-gender equality ideas and practices; and to enable political and civil society actors to build genuine relationships between women and democratic politics, whereby women's political equality is fully realised. QUALREP redresses this need by conducting a theoretically rich, comparative empirical analysis of the quality of women's political representation, attentive to their intersectional and ideological diversity and with particular concern to the most marginalised women, across five European nations: Belgium; Britain; Poland; Portugal and Sweden. In so doing, it develops a conceptual framework and methodology applicable in the future to global research across diverse democracies that can help establish the features of, and conditions for, high quality women's political representation providing an essential evidence base for advocacy and policy making that advances gender equality in politics and beyond.

View the original record at the funder ↗

Researchers

Sarah Childs (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Feminizing Politics and Power in the UK: Voice, Access and Accountability
Understanding The Political Representation of Men: A Novel Approach to Making Politics More Inclusive
From Suffrage To Representation: Women, Suffragists and Politicians upon Enfranchisement in the U.S., U.K, Norway and Chile
Representation matters: an intersectional feminist rethinking of descriptive representation.
Fostering Queer Feminist Intersectional Resistances against Transnational Anti-Gender Politics

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.