CRITICAL EDITING
Finding the red flags in copy that need to be fact checked
Gerri Berendzen, Knight Visiting News Editor,
Columbia Missourian, University of Missouri School of Journalism
A no cat presentation
Who said that?

Verification begins with asking questions,
no matter what you are editing. Being a
skeptical editor is a plus.

Always ask:
How do we know this?
Who said this, and how do they know?
What is the source of this information?
What to check?
Red flags aren’t always just the big
information.
Check anything that raises a red flag, but
spot check other information as well (even
information that is CQ’d.)
Start here:
1.
If you read something and a question
immediately pops into your mind, run
with it. Don’t ignore it.
Start here:
1.
2.
If you read something and a question
immediately pops into your mind, run
with it. Don’t ignore it.
If it seems too good to be true (or too
big to be true or too unusual to be
true), it probably is. Question it.
Start here:
1.
2.
3.
If you read something and a question
immediately pops into your mind, run
with it. Don’t ignore it.
If it seems too good to be true (or too
big to be true or too unusual to be
true), it probably is. Question it.
Very few things can be chalked up to
coincidence. If something seems like a
coincidence, check it.
What types of information
should raise red flags?

Information or visuals that do not ring true. Build and trust
your BS detector.
What types of information
should raise red flags?
Information or visuals that do not ring true. Build and trust
your BS detector.
 Numbers — including dollar amounts.

What types of information
should raise red flags?
Information or visuals that do not ring true. Build and trust
your BS detector.
 Numbers — including dollar amounts.
 Data and polls, especially data that seems to be cherry
picked.

What types of information
should raise red flags?
Information or visuals that do not ring true. Build and trust
your BS detector.
 Numbers — including dollar amounts.
 Data and polls, especially data that seems to be cherry
picked.
 Inconsistency and repetition.

What types of information
should raise red flags?





Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
What types of information
should raise red flags?






Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
Out-of-context examples and references.
What types of information
should raise red flags?







Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
Out-of-context examples and references.
Visuals that are meant to distract or misrepresent or
seemingly are selected to prove a particular point.
What types of information
should raise red flags?








Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
Out-of-context examples and references.
Visuals that are meant to distract or misrepresent or
seemingly are selected to prove a particular point.
Innuendo.
What types of information
should raise red flags?









Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
Out-of-context examples and references.
Visuals that are meant to distract or misrepresent or
seemingly are selected to prove a particular point.
Innuendo.
Biased sources.
What types of information
should raise red flags?










Information or visuals that do not ring true. Build and trust
your BS detector.
Numbers — including dollar amounts.
Data and polls, especially data that seems to be cherry
picked.
Inconsistency and repetition.
Hearsay.
Out-of-context examples and references.
Visuals that are meant to distract or misrepresent or
seemingly are selected to prove a particular point.
Innuendo.
Biased sources.
Absolutes. Look for “the only,” “the best,” “the number one,”
“highest,” “worst” statements.
Too big to be true?
Too big to be true?
In 2011, the Morning Bulletin in Australia
had this headline: Pigs float down the
Dawson. It said “more than 30,000 pigs
were floating down the Dawson River.”
I’d read that story; wouldn’t you?
Someone should have asked …

“Wow, 30,000 pigs. That’s a lot of pigs

A number that big should have raised a
red flag. Questioning that red flag would
have saved a correction.
Even the Bulletin realized that eventually, having some fun with this graphic that
shows how many pigs 30,000 is.
NUMBERS: Always ask …
1.
How could someone count (or
determine) that?
NUMBERS: Always ask …
1.
2.
How could someone count (or
determine) that?
Where did the number come from?
NUMBERS: Always ask …
1.
2.
3.
How could someone count (or
determine) that?
Where did the number come from?
What was the original source?
NUMBERS: Always ask …
1.
2.
3.
4.
How could someone count (or
determine) that?
Where did the number come from?
What was the original source?
What was the original context?
NUMBERS: Always ask …
1.
2.
3.
4.
5.
How could someone count (or
determine) that?
Where did the number come from?
What was the original source?
What was the original context?
Is the number still true?
NUMBERS: Always ask …
1.
2.
3.
4.
5.
6.
How could someone count (or
determine) that?
Where did the number come from?
What was the original source?
What was the original context?
Is the number still true?
How was the figure calculated. Was the
study, poll or survey scientific?
NUMBERS: Always ask …
1.
2.
3.
4.
5.
6.
7.
How could someone count (or
determine) that?
Where did the number come from?
What was the original source?
What was the original context?
Is the number still true?
How was the figure calculated. Was the
study, poll or survey scientific?
Was the source biased?
Use common sense
Does a number just seem too big?
These types of number errors happen in news stories, press release,
books, corporate … anything that is written. Questioning numbers is
always a good thing.
SUPERLATIVES AND
ABSOLUTES
An editor should question anytime that
something is called the best, top ranked,
highest earning, first.
 Demand the source.
 In many cases, superlatives and absolutes
are not necessary to the understanding of
the information being presented. So the
best way to deal with them is to delete
them.

Would you question this
information if you saw it in copy?
Would you question this
information if you saw it in copy?
• One red flag: the ranking wouldn’t be 6th or 7th.
That’s a tipoff that the information might be wrong.
• Check it out; quote the correct number; then link
to a reliable source for transparency.
VISUALS THAT DISTRACT
OR MISREPRESENT
VISUALS THAT DISTRACT
OR MISREPRESENT
VISUALS THAT DISTRACT
OR MISREPRESENT
Submitted copy
Source: Romenesko.com
Internal inconsistencies and
coincidence

Internal inconsistencies. Check dates and
ages especially.
Would having a college student say he was
born in 2002 set off alarms?
Internal inconsistencies and
coincidence
Internal inconsistencies. Check dates and
ages especially.
 Things that seem unlikely to you are
probably unlikely.

If a story says a tea party representative is
in favor of gun control, check it out. Even if
it’s right, there’s probably a bigger story
there.
Internal inconsistencies and
coincidence
Internal inconsistencies. Check dates and
ages especially.
 Things that seem unlikely to you are
probably unlikely.
 Improbable geography.
Would you check if a story mentioned a snow
storm in San Diego.Yes. But there can be
subtler geography red flags.

Other red flags to check

Copy in which the lead or nut graph is
not supported by the rest of the story.
Other red flags to check
Copy in which the lead or nut graph is
not supported by the rest of the story.
 Critical quotes. The statements may be
fair, but we owe it to reader to check it
out.

Other red flags to check
Copy in which the lead or nut graph is
not supported by the rest of the story.
 Critical quotes. The statements may be
fair, but we owe it to reader to check it
out.
 Partial quotes: Would all of the words
said by the person change the meaning of
the excerpt.

Other red flags to check
Copy in which the lead or nut graph is
not supported by the rest of the story.
 Critical quotes. The statements may be
fair, but we owe it to reader to check it
out.
 Partial quotes: Would all of the words
said by the person change the meaning of
the excerpt.
 Generalizations and unnamed sources.

Other red flags to check

Unusual or little used words and terms
Accuracy checks
Many publications have an accuracy check
policy, but many do not.
Set one up. It should cover:
1. What needs an accuracy check.
2. How much of an article a source can see.
3. When will you let a source change words
you have proof they said.
But don’t rely on the AC. Copy editors still
need to do fact checks on AC’d copy.
Resources:
Some digital sources that can help you track down
claims (find more at verificationhandbook.com):
 SearchSystems.net: an international directory of free
public records.
 Snopes.com: a site dedicated to debunking Internet
hoaxes, which can be used to cross-check UGC.
 Verily platform: allows users to ask specific questions
and provide UCG evidence for and against.
 Emergent: A real-time digital rumor tracker.
 The National Council on Public Polls has an excellent
article.
More resources:

The National Council on Public Polls article“20
Questions A Journalist Should Ask About Poll
Results.”

Associated Press conditions for accuracy.

My checklist for the copy editor
(http://gberendzen.com/2015/02/02/a-check-listfor-copy-editors/)
Bye