Gang Triangulation | Estimating Gang Firearm Homicide Extent | Gun Facts

While I'm not saying you are wrong, I am saying you have not posted anything to say you are correct

So, a good way to tell whether something is BS propaganda is to read it the opposite way. Rather than convincing yourself it might be true, try starting out sure that it is wrong, and forcing the article to convince you it is right.

You will see the glaring discrepancies: In the gang / homicide distribution chart, they account for 100% of gangs. Good job. but then they account for 119.3% of homicides. wait... what?

They start by (essentially) saying "don't trust the FBI, they are rubbish." Wait.... what?

They state that "This brings home the point that any homicide detective in a major metropolitan area will make: most of the homicides there are gang related in some fashion" with absolutely no evidence to support the claim.

Count the number of times the author(s) "assume" facts not in evidence. Count the number of "ifs." Count the number of times they use an unsourced (i.e. they made it up or provided no information on where it came from) or unverified (i.e. Wikipedia, Netflix, random interview of a guy on the street) data point. Count the number of times they pulled a data point out of context and put it with another data point (usually also out of context) to create a narrative.

Look at the level of "narrative" voice vs. level of "statistical" voice. Is the author telling you what the numbers are, or what the numbers *mean*?

Finally, as you read, consistently ask yourself if there is data that is not being included or is being ignored. When looking at the correlation between gang location (mostly urban centers) and homicide rate (mostly urban centers) the author concludes that this *must* mean that most homicides are gang related. Wait...what? The fact that this is where the most people are might have something to do with it. Or other things, like urban decay, community watches (or the lack thereof), policing, community resources (or the lack thereof), poverty, etc.

And then you have things like 5.5% is basically the same as 6.5%. Um, no. It is 20% off.

The article is taking unrelated numbers from separate data sources and throwing them together. That is a no-no. The article is taking small sample sizes and extrapolating out to entire populations. That is a non-no. The author is taking unknowns and simply guessing, or assuming. That is a no-no. It is a WHOLE LOT of "what if" and almost no "what is." But it is certainly presented as "what is" or at least "what I think it is."