otacust

Though one could argue that it does stop congressional insider trading, or at least reduce it: https://www.citizen.org/wp-content/uploads/migration/case_do...

Though this article makes some good points: - There's always an excuse: someone else made the trade, or it was just really lucky, or it was smart use of public information. - There are ways for members of congress to influence the markets that disclosures under the STOCK act won't prevent; e.g. many members of congress trade tech stocks and hold hearings about big tech companies, which can move the markets. - Trading related to one's congressional duties could be insider trading...or it could be trading on the basis of subject matter expertise. It's not always easy to tell them apart. - Compliance to the STOCK act isn't great, so the data are incomplete. - The data are presented in difficult-to-use form. If not for https://senatestockwatcher.com/, we'd be looking at a hard-to-navigate site full of scanned PDFs. Converting those to usable data is probably something the government should be doing!

I'm not sure I agree with everything in this article, but it does make a good point that a lot of the current reporting is decidedly ahistorical. "Record numbers of resignations" don't mean much once you know records were reached in several recent years. What makes this time different? Why the understaffed stores?

It depends heavily on the job, particularly on management. I will work more if I have a selection of tasks to work on and some choice throughout the day on what to work on. This is especially true if I was part of the decision-making process that led to being assigned those tasks in the first place.

But if I have just one thing to work on, and it's something I'm not interested in and don't particularly want to work on? Yeah, probably not putting in a particularly full week.

The Washington Post article referenced in this post is really interesting: https://www.washingtonpost.com/climate-environment/interacti...

The yearly revisions of the GHG emissions estimates are really striking.

I used fastai quite a bit with PyTorch and ended up feeling the same way. Great for spinning up an effective model in a few lines, but really tough to make it do exactly what you want it to do.

I agree. Trust has a very limited place when dealing with data, and I don't think you can extend the benefit of the doubt to sources that are not consistently reliable.

Though in this case, it looks like the U.N. is aggregating self-reported country-level emissions data, so I guess the situation is a little different.