Great, health insurance companies can also inadvertently share your protected health information (PHI) with Google and offer basically nothing to help you.
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Patrick Cherry
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@pcherry
I'm still working though this article. While the bottom-third v. top-third graph is telling, the values are correlated over time.
Something really telling is the Vanguard hires vs. JOLTS hires, which reverse direction during the Mar-Apr 2020 recession.
Companies were adding workers with no 401(k) while pulling back on workers who would have gotten a 401(k).
To all my friends who feel like they aren't good enough to get a job right now: it's not you. Alternative economic metrics suggest a bifurcation of the job market, with higher-earning jobs hiring less and more slowly.
"But among those who make more than $96,000? ... Hiring has slowed to a dismal 0.5%, less than half the peak it reached in mid-2022. Excluding the dip in the early months of the pandemic, that's the worst it's been since 2014."
Really into the word “enshittocene,” as in the geologic epoch dominated by widespread and ever-progressing enshittification.
https://fy.blackhats.net.au/blog/2024-04-26-passkeys-a-shattered-dream/
I customized the themes and code syntax highlighting on my blog, and I love it. I think the themes really go well together, both light and dark modes. 😍
The results can be presented many different ways. I do like the heat map. But I think the most useful for a regular user is the searchable, sortable table of political org clustering distances.
This makes it easy to see how similar (low number) or different two political orgs' ballot measure endorsements are.
I think my favorite part of this exercise was that the clustering analysis worked well, and added some order to the ballot measure yes/no plot: