According to a new IPS briefing paper, the richest .01 percent of Americans, about 33,000 lucky souls today, now pay just one-sixth of what they used to pay in tax, when measured as a percentage of their total wealth.
This suggests that “tax the rich” has a long way to go, but also that it may have a political opening.
On the other hand, we tend to tax income, and do not in the main do wealth taxes other than on real property, so to the extent this wealth increase is unrealized capital gains after a huge surge in the market it is maybe not surprising that there is such a large untaxed body of wealth out there.
Excessive amounts of close-up eye contact is highly intense.
Seeing yourself during video chats constantly in real-time is fatiguing.
Video chats dramatically reduce our usual mobility.
The cognitive load is much higher in video chats.
But Zoom, they argue, could make design changes to fix or ameliorate these:
[M]any of these problems could be solved with trivial changes to the design of the Zoom interface. For example, the default setting should be hiding the self-window instead of showing it, or at least hiding it automatically after a few seconds once users know they are framed properly. Likewise, there can simply be a limit to how large Zoom displays any given head; this problem is simple technologically given they have already figured out how to detect the outline of the head with the virtual background feature. Outside of software, people can also solve the problems outlined above with changes in hardware and culture. Use an external webcam and external keyboard that allows more flexibility and control over various seating arrangements. Make “audio only” Zoom meetings the default, or better yet, insist on taking some calls via telephone to free your body from the frustrum.
What I like best about all this is the suggestion that I’ll do better as a Zoom listener if I do other things while listening from time to time. Depending what the other thing is, it might be right. But it’s so Millennial!
Interesting Twitter thread about the following question: If you plot the US state-by-state COVID infection rates since Sept 1, 2020–i.e. the recent and now receding surge–which is a better predictor:
The percent of the population infected before Sept 1, or
The margin of Biden’s victory in the state?
You might expect that states which had lots of COVID before Sept. 1 would have more of it after Sept. 1 for the same reasons they were getting it earlier. Or, I suppose, you might expect the reverse: states learn from their mistakes, and if infection rates were higher earlier then more people have immunity, so there’s a negative relationship between earlier infection rates and later infection rates.
According to Youyang Gu, both of those expectations are broadly wrong:
Instead, the single variable with the most predictive power is how strongly states voted for Biden.
As commenters in the thread note, at an R-squared of about 0.5, this is not a fully explanatory variable–there’s a lot going on, no doubt. Youyang Gu’s suggestive claim is only that as single-variable explanations go, this is the most powerful.