Introducing “Red Ink” from The New Center
Today, The New Center is excited to launch our new “Red Ink” feature, in which we will call out and contextualize the bias that is increasingly seen in mainstream news stories, as well as outlets that push an explicitly liberal or conservative worldview. “Red Ink” is modeled on the red pen editors traditionally use to mark up a reporter’s story. Unlike many fact-check sites, which police politicians and public figures for getting statistical minutiae wrong, New Center Red Ink will highlight the omissions, biases, and selective sourcing that increasingly make news articles read like opinion essays.
At a moment when public trust in the media is at an all-time low, The New Center hopes Red Ink will begin to make people aware of the subtle, not-so-subtle, and specific ways that media outlets are abdicating their responsibility to be fair arbiters of the truth.
Specifically, we will be highlighting examples of bias that fall under the following categories:
- Misleading anecdote — Framing of an isolated incident as representing an occurrence or trend that is more widespread than it actually is.
- Author’s unattributed opinion — Making unfounded assumptions about how someone mentioned in the article is feeling or thinking
- Omitted key fact — Leaving out crucial contextual information
- One-sided narrative — Overemphasizing one side of a two-sided story
- Biased sourcing — Citing biased sources to support a biased narrative
- Twisted context — Quoting someone without providing all the information necessary to understanding that person’s intended message
- Outdated stats — Using outdated information or statistics to argue a point—e.g., making a point about health care access using information published in 2018, which collected data from 2017.
- Biased labeling — When a reporter fails to correctly label a source “liberal” or “conservative” when citing it. Or, when a reporter labels a person or group with positive or seemingly nonpartisan labels, such as “an expert” or “advocacy organization”, when it is a lobbying, party or industry organization.
- Shaky statistics — Mathematically incorrect sourcing of statistics—e.g., saying “10 percent increase” when they mean a “10 percentage point increase”.
- Shaky statistical interpretation — Using legitimate statistics, but coming to an unfounded conclusion
- Questionable anonymous sourcing — Over-reliance on anonymous sourcing in an article or giving vague attribution when more specificity is required.
- Questionable statistical sourcing — Citing a biased or unreliable source of statistics
- Misleading headline — When the headline presents a sensationalized or otherwise inaccurate overview of what is actually written in the article