After Sen. Ted Cruz needled mainstream fact-checker PolitiFact by calling it “a wholly-owned subsidiary of the Democratic Party,” PolitiFact responded with a hilariously tone-deaf article PolitiSplaining why it was not, in fact, a wholly-owned subsidiary of the Democratic Party.
The conservative media criticism site Newsbusters piled on with an article intended to show PolitiFact’s partiality to the political left. But its evidence substantially misfires:
In February, I noted that in 2017-18, PolitiFact fact-checked President Trump 25 times more often than Nancy Pelosi and Chuck Schumer, the Democrat leaders in Congress…combined (297 to 21). He had more “Pants on Fire” fact checks (33) than all their fact checks combined.
Trump serves as president. Presidents will always tend to draw more attention for their political statements. Newsbusters should choose an apples-to-apples comparison to fairly make its point.
As for the number of “Pants on Fire” statements, that means little without putting forward a specific case that the number of “Pants on Fire” ratings shows bias. Many have suggested that Republicans like Trump simply lie more, therefore nothing is amiss if they receive the harshest ratings.
The next evidence similarly misfired:
Ted Cruz and Elizabeth Warren were both elected to the Senate in 2012. Cruz was assessed for truth on 135 occasions by PolitiFact through 2018, but Warren? Only five.
Cruz serves the state of Texas in the U.S. Senate. Texas has a PolitiFact affiliate, PolitiFact Texas. About half of Cruz’s PolitiFact ratings come from PolitiFact Texas. Plus Cruz ran for president in 2016. Presidential elections draw extra attention from fact checkers.
In comparison, Warren serves the state of Massachusetts in the U.S. Senate. Massachusetts has yet to host a PolitiFact state operation, and Warren did not make a presidential run in 2016.
PolitiFact’s ratings do offer pretty strong evidence of an ideological bias. But not using apples-to-oranges comparisons like the ones Newsbusters tried.
Those count as poor measures.