TRIGGER WARNING: Potty language.
For John, BLUF: Read the news with a question mark on your shoulder. Nothing to see here; just move along.
From the international news organization, Vice, we have Mr Ryan Faith advising us on "How to Cut Through the Bullshit and Read the News Like a Defense Analyst". While I don't much care for the use of the term "bullshit", the article is useful. Here is the lede and following:
Leading up to the midterm elections in 2014, the FBI published a report that cited statistical evidence to make the claim that mass shooting incidents were dramatically on the rise in the US. The overall impression was that bloody rampages like the Sandy Hook massacre and the Colorado movie theater shooting could be expected to occur more frequently in the coming years.The author suggests:
Several major news outlets ran with the story, reporting without much skepticism on findings that happened to dovetail nicely with a push by the White House and Democrats to enact stricter gun control measures and boost voter turnout. You can probably guess what happened next.
As noted recently by the Wall Street Journal and others, the authors of the study — Texas State University academics J. Pete Blair and M. Hunter Martaindale — have been forced to backpedal, acknowledging that their data was "imperfect" and asserting that the media coverage of their findings "got it wrong."
There are basically two ways of reading the news and consuming any kind of information. Sometimes people read to confirm their beliefs. The other way of consuming news is to scrape it for tidbits of data and information. In practice, people usually do a bit of both.Even the Old Gray Lady, The New York Times, our newspaper of record, is not immune from publishing information that should not be taken at face value.
So, how can you tell if you're being spoon-fed bullshit? It starts with second-guessing yourself. If you accept or reject data, ask yourself if you're doing it because the data is accurate, or because it confirms your biases.
People tend to reflexively assume that quantitative data is axiomatically bullshit-free, but be beware that those numbers you're looking at might be "advocacy research" — purely political opinions dressed up with data.
Regards — Cliff