- About Us
- FairVote Projects
- Electoral Rules and the Representation of Women and People of Color
Electoral Rules and the Representation of Women and People of Color
With the support of the Women Donors Network, FairVote has launched two ambitious research projects that explore the impact of electoral systems on the representation of women, people of color and women of color:
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Electoral Rules and Representation in Counties: The Who Leads Us databases, created by the Women Donors Network, record the gender, race and ethnicity of candidates and elected officials from the local county to national level of public office in 2012 and 2014. Utilizing these extensive databases, FairVote is exploring the impact of different electoral rules on the representation of women, people of color and women of color. We will explore the impact of multi-winner districts, proportional representation and many other electoral rules on the reflectiveness of a county’s elective government. By the end of 2016, we will publish:
- A full dataset containing variables for multiple electoral rule features (including election dates, the size of county commission, the use of partisan elections, the use of multi-winner districts)
- A report that summarizes the findings of the research and main recommendations for achieving a more equitable representation of women, people of color and women of color.
- Interactive visuals that rank and provide data on each county.
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Fair Representation and Representation In this project, we explore reflective representation in proportional systems in the American context. We will study all the jurisdictions that use Fair Representation voting systems. The existing literature indicates that proportional representation systems, including Fair Representation voting, lead to better representation of women and people of color.
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RCV and Representation in the California Bay Area: In this project, FairVote is quantifying the impact of RCV on the representation of women and people of color in the Bay Area. We use an extensive database of candidates dating back to 1992 and a rigorous difference in differences method. We anticipate completing our project in 2016.