Results from the United States’ midterm elections are still pouring in, but a handful of candidates with backgrounds in science or technology have already nabbed seats in the US House of Representatives.
They include Elaine Luria, a US Navy veteran and nuclear engineer in Virginia, and Chrissy Houlahan, a former business executive with degrees in engineering, in Pennsylvania. Illinois saw victories by registered nurse Lauren Underwood, a former senior adviser to the Department of Health and Human Services, and clean-energy entrepreneur Sean Casten, who has degrees in engineering and biochemistry.
The four — all Democrats — are among roughly 50 candidates with science backgrounds who ran for the House in 2018, sparked in part by opposition to President Donald Trump; fewer than half of these novice politicians made it past the primaries to the general election.
The wave of interest is “indicative of people’s desire to get involved, and a recognition that it’s no longer okay to sit on the sidelines and watch,” says Benjamin Corb, director of public affairs at the American Society for Biochemistry and Molecular Biology in Rockville, Maryland.
The victories came as Democrats regained a majority of seats in the House, taking the chamber back from Republicans — who still control the Senate and the White House.
“We’re watching the House pretty closely,” says Jennifer Zeitzer, director of the office of public affairs at the Federation of American Societies for Experimental Biology in Bethesda, Maryland. The change in control from Republicans to Democrats is a “game-changer,” she says, in part because it means that leadership of key committees will change hands come January.
That Democrats recaptured the House is “no small feat”, says Elizabeth Gore, senior vice-president for political affairs at the Environmental Defense Fund, an environmental-advocacy group based in New York City. “It is going to change the dialogue in Washington, and will certainly change the dynamic around science and the environment.”
Holding even a slim margin in the House will give Democrats the power to investigate the Trump administration’s policies. Gore says that this is likely to translate into congressional hearings on the scientific justification behind the administration’s efforts to roll back a variety of climate and environmental regulations.
“Some of the oversight that we will see in a Democratic house will be focused on reestablishing scientific integrity and highlighting the failure of the Trump administration to use scientifically based information for policymaking,” Gore adds.
Here are results from some of the other races and ballot measures that Nature has been watching. We’ll continue to update this story today with election reaction and analysis.
Washington state carbon-tax proposal
Voters in Washington rejected Initiative 1631, a ballot measure to establish the first US carbon tax. It would have imposed a US$15-per-ton fee on carbon in 2020, raising the price by $2 annually until 2035. A similar ballot measure failed to pass in 2016.
Representative John Culberson (Republican, Texas), a space enthusiast who heads the House spending panel that oversees NASA, the National Science Foundation and the National Oceanic and Atmospheric Administration, lost his battle for re-election. Culberson’s stalwart support for a NASA mission to Jupiter’s moon Europa became a campaign issue this year.
Culberson’s opponent, Democrat Lizzie Fletcher, accused him of favouring pet projects such as the Europa mission and neglecting local issues in his district near Houston — such as the severe floods caused by Hurricane Harvey in 2017.
Efforts to stop gerrymandering
Three states approved proposals to address gerrymandering, the act of drawing voting districts to favour one party over another. Ballot measures passed by voters in Colorado, Michigan and Utah will establish independent commissions to draw electoral boundaries, rather than leaving the task to politicians. In recent years, mathematicians have joined the fight against gerrymandering, developing computer models and algorithms to reveal bias in electoral maps — and to propose how to redraw them with fairer boundaries.