This is a really good critique. I would not have thought to read this article as critically as you did, and likely would have accepted it at face value. But now

This is a really good critique. I would not have thought to read this article as critically as you did, and likely would have accepted it at face value. But now that you mention it, there's more issues I see: "This is the highest mass resignation the U.S. has seen since 2019, pre-pandemic, and the numbers are still rising. In June, 3.9 million quit. In July, it was another 3.9 million. In August, 4.3 million." The [3.9M, 3.9M, 4.3M] sequence seems cherry picked. It could just be normal noise for all we know. To me this kind of argument could be easily summarized with simple data visualization, i.e. a line graph with more datapoints (expand 3 month range to a full year, stack more years for context). A histogram of monthly resignations to attach a %-ile to it would also be great, but may not be as intuitive and there's a lot of complexity involved in trying to understand significance. The author follows the monthly resignation numbers with: "The numbers are even more notable for young workers: in September, nearly a quarter of workers ages 20 to 34 were not considered part of the U.S. workforce—some 14 million Americans, according to the Bureau of Labor Statistics, who were neither working nor looking for work." You interpret this as them saying 14M is a big number, but I think based on the preceding sentence, it's actually trying to say 14M is "more notable" than the ~3.9M in the preceding argument. I kind of think this is the case, as its a really common data mistake I see in articles: mixing up units. In this case of course, out-of-labor/month cannot be compared to cumulative out-of-labor-young/month. That being said, I disagree with you on your attribution of this to activist journalism. And for context, I'll just say that unlike the vast majority of HN, I actually have a lot of respect for most modern journalism, and think most people complaining about journalism aren't comparing state of affairs in countries like China/Russia/Sri-Lanka without press freedom. My more generous interpretation is that another underlying cause for these kinds of mistakes is simply a lack of familiarity with math, and especially statistics. A journalist with good intentions can still make these kinds of errors if they aren't familiar with good practise in statistics. Finally, I just wanted to say, there are quite a few journalists that are pretty good at data-based journalism. I think Kevin Drum[1] is a particularly good example, since he'll often refute other articles by digging up more data and illustrating how marginal some percieved effect is in context. 1. https://jabberwocking.com/ https://jabberwocking.com/ ETA: Fixed unit confusion critique mistake, it's not resignation but out-of-labor.