Friday, November 4, 2022

Research note: PolitiFact's 'Pants on Fire' bias through October 2022

We continue to update our research project examining PolitiFact's bias in applying its "Pants on Fire" rating.

The project notes that the difference between "False" and "Pants on Fire" ratings on PolitiFact's "Truth-O-Meter" counts as subjective. "False" statements are untrue, while "Pants on Fire" statements are untrue and "ridiculous." "Ridiculous" is a subjective judgment on its face, and PolitiFact has never published a description of the it suggesting otherwise.

Through the end of October 2022, PolitiFact had only given a Democratic Party officeholder/candidate/organization/appointee one "Pants on Fire" rating that counts toward our statistics. Our count omits claims from that attack the claimant's own political party. One of those occurred, published through PolitiFact New York.

As a result, we found PolitiFact nearly six times more likely to subjectively rate (what it views as) false claims from Republicans as "Pants on Fire" compared to such claims from Democrats.

Interestingly, PolitiFact National published its first "Pants on Fire" rating for a Democrat in 2022 not long after we tagged PolitiFact's Editor-in-Chief Angie Drobnic Holan in our tweet about this graph. A graph including the November stats as of today would put the 2022 PoF Bias number near 3.2--not the all-time record but instead solidly among the four highest bias measures taken since 2007.

Of course new ratings may move the numbers greatly by the end of the year.

Readers curious about the trends and details of the chart may wish to look at our explanation for the full chart at the end of 2021.

1 comment:

  1. Apparently somebody wanted to comment but couldn't be bothered to read the rules for commenting (**No "Anonymous." No "Unknown." Etc.**) and also apparently didn't read the material enough to compose a comment that made sense.

    The research is based on finding PolitiFact's "Pants on Fire" rating to be wholly or substantially subjective. That means it's not going to matter who lies more, unless you're trying to excuse the subjective bias by appealing to an objective reality that nobody has scientifically measured. And, good luck with that.


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