Evaluating Sources

Using the SIFT Model

Mike Caulfield created the SIFT acronym to describe four moves that writers should make to evaluate their sources:

Stop: When you first hit a page or post and start to read it — STOP. Ask yourself whether you know the website or source of the information and what the reputation of both the claim and the source is.

Investigate the Source: You want to know what you’re reading before you read it. Take sixty seconds to figure out where the media is from before reading it. This will help you decide if it is worth your time, and if it is, help you to better understand its significance and trustworthiness.

Find Trusted Coverage: Sometimes you don’t care about the particular article or video that reaches you. You care about the claim the source is making. You want to know if it is true or false. You want to know if it represents a consensus viewpoint or if it is the subject of much disagreement.

In this case, your best strategy may be to ignore the first source that reached you and look for trusted reporting or analysis on the claim. Or, you may want to scan multiple sources and see what the expert consensus seems to be.

Trace Claims, Quotes, and Media Back to the Original Context: Much of what we find on the internet has been stripped of context. Maybe there’s a video of a fight between two people with Person A as the aggressor. But what happened before the video that you see? What was clipped out of the video and what stayed in? Maybe there’s a picture that seems real, but the caption is misleading. Maybe a claim is made about a new medical treatment based on a research finding — but you’re not certain if the cited research paper really said what the article claims. In these cases, we’ll have you trace the claim, quote, or media back to the source, so you can see it in its original context and get a sense if the version you saw was accurately presented.

Other Notes on Credibility: 

Be sure to consider the following characteristics of your source when deciding if it is reliable:

• Author and/or publisher background
• The degree of bias
• Recognition from others
• Thoroughness of the content