More than 00.21% (what Roger MacBride won in the 1976 election)

More than 00.25% (what David Bergland won in the 1984 election)

More than 00.28% (what Andrew Marrou won in the 1992 election)

More than 00.32% (what Michael Badnarik won in the 2004 election)

More than 00.36% (what Harry Browne won in the 1976 election)

More than 00.40% (what Bob Barr won in the 2008 election)

More than 00.47% (what Ron Paul won in the 1988 election)

More than 00.50% (what Harry Browne won in the 1996 election)

More than 00.56% (what Ralph Nader won in the 2008 election)

More than 00.71% (what Ralph Nader (Green Party) won in the 1996 election)

More than 00.99% (what Gary Johnson won in the 2012 election)

More than 01.06% (what Jill Stein won in the 2016 election)

More than 01.18% (what Jo Jorgensen won in the 2008 election)

More than 00.04% (what Kanye West won in the 2020 election)

More than 02.74% (what Ralph Nader (Green Party) won in the 2000 election)

More than 03.27% (what Gary Johnson won in the 2016 election)

More than 00.15% (what Darrell L. Castle (Constitution Party) won in the 2016 election)

This market exists for two main reasons: I think a cumulative-independent approach is the most useful format for markets like this, and I also wanted a market where people could directly compare their predictions about Cornel West's bid to previous 3rd party election bids.

Dave Leip's numbers will be used to resolve this market: 

Note that if it gets close, the answers that refer to a specific candidate should be taken as not the exact number listed in the answer, but the actual percentage of the popular vote that the candidate got in that election according to Dave Leip's numbers - e.g. the Jo Jorgensen answer should not be taken as 1.18% exactly, but instead as the percentage of the vote total she actually got according to Dave Leip's numbers (e.g. in that case 1,865,926/158,594,895)

Please ask any questions in the comments if you have any.