igor67

Sling is completely portable. You do need to have decent internet to stream. Netflix is also completely portable and lets you stream a little better with slower connections (since it buffers unlike Sling).

tag or not pretty sure by the laws of physics Baez's foot had to push Haders into the bag first

Amplifying the comments in the JP Breen article, even if the year ends up being a dud for the Brewers I would say it actually enhances the value in not spending big in the offseason. With any long term free agent contract the first couple of years are the most important as they are the ones were you are most likely to still get the performance you are paying for. That isn't exactly happening for anyone this year. I've been here for the entire Brewerfan era and in the hardest sport to even make the playoffs the Brewers have done very well under Stearns in getting there and still are what 1/2 game out a playoff spot right now? Back to 2001 I'm pretty sure most of us would have a happily signed up for the number of playoff appearances we've gotten in the Melvin and Stearns era.

You are at risk of being overly cynical and under appreciating the privacy issues schools are responsible for upholding TPlush. Just on the details posted that would be 2 separate violations of our technology policy (having the phone in class and unauthorized sharing). You also do not know if the student has been disciplined before about related infractions which naturally escalates any punishment. Invariably in any instances like this the school can do very little to properly explain itself because it continually has to safe-guard any students right to privacy (even if the student is broadcasting information). It is very frustrating to live through when you know the real story but can't share it.

I came across this article which maybe more of interest to me, but https://www.buzzfeednews.com/article/stephaniemlee/ioannidis-trump-white-house-coronavirus-lockdowns It digs into the timeline of Jonathan Ioannidis' communications and publications. He was easily the most prominent scientist using antibody testing to get very high prevalence rates of the virus and as a result much lower lethality estimates. The article does not really supply a clear motivation for his behavior, but it does establish that very early on he was very anti-lockdown. So what I think happened is that for some reason or another he came to believe that a lockdown would cause serious devastation. From that given he spent months collecting and looking at data with that in mind, at some point I suspect his ego also kicked in and lead him to keep doubling down. I can't clearly demonstrate that explanation, but it is consistent with other episodes where prominent scientists go off the deep end. What I hope people can take away from this episode is not cynicism or lack of respect for the experts, but a good example of why the cross checking of peer review in science is so critical. This type of mistake is easy enough for anyone to fall into afterall. What makes the entire thing so noteworthy is that Ioannidis is most well known for taking a very hardline stance in methods and rigorous experimental and statistical techniques and standards. Standards he abandoned in this case.

That's helpful. Thanks. I'm sure I'll be getting plenty of questions from students in about a month again.

Our school did a survey as well and it was a complete mess. Lots of 60/40 splits on questions. No one really liked distance learning, but a modest majority weren't feeling like resuming in person either.

Its because Christopher Heyerdahl is really quite something. He played a number of aliens on Stargate Atlantis and Sanctuary so he isn't always recognizable except for the voice. I liked his work on Van Helsing as well.

I was kind of hoping Peach might answer a question. So they are getting ready for a phase III vaccine trial. I'm curious what the failure rate (estimate is fine) for vaccines that make it that far. For drugs it is unpleasantly high, not horrible or anything but it is a huge loss for the company after all the investment.

Science, PE, Music, and Art are all big problems to move around for the teachers.

It's fairly well documented that the death rates are quite low (by comparison to older individuals) for younger people. The various identified risk factors though get to a pretty big percentage of the overall population though. Obesity/overweight by itself already gets you to 20% in teenagers for example. The various other factors push that quite a bit higher. It becomes a large number issue, the relative risk is lower, but when you start to get into the millions being infected you will still rack up a pretty unexciting body count. Here is another one that was young enough she could have been a student of mine. https://www.twincities.com/2020/06/07/st-paul-school-board-chairwoman-marny-xiong-31-dies-of-covid-19/

A few things perhaps Wisconsin has managed to do things differently on the retirement side, but in MN the you can retire after 30 years flat or it's close variations have been gone for quite a while. I worked when I started with a few people who had started early enough they could still just qualify for those rules. I tell my students I never used a planner until I started teaching. Lab research had it's particular challenges, but teaching is definitely harder. Given that the first years are the hardest the low starting pay is particularly problematic. Mid to late career if you like the life style it is OK, but it is not a joke to say that I've worked with teachers who received free/ reduced lunch for their children as well.

Assuming nothing else questionable happening before hand it is worth pointing out that there is generally very little difference in the quality of evidence for a study whose results 'were almost statistically significant' vs. one that was just barely statistically significant. In this case knowing what the disease is and how the drug works, with just one study to go on the results lean very much toward it helps with mortality. But that's a lot like playing poker when your hand is a 2-1 favorite. You will be right a lot, but you'll also wrack up a lot of mistakes, so better proof is ideal. In any event when they first announced Remdesivir results the clearer finding was that it shortened hospital recovery time by 4 days. If you compare 4 days in the hospital to the drug cost I'm guessing it is pretty easy to come out ahead. Which shouldn't be taken to mean I agree with the price exactly, but Gilead did invest a lot of their money as well, but to my knowledge never really made any of it back because the drug ended up not performing super well for Hep-C. It is potentially a good example of how divergent the public vs. private interests are for drugs. Publicly cures are what we all want. Private companies though love treatments, the longer and more chronic the better.

If people give themselves a moment they are actually rather familiar with this type of back and forth in the literature. Think of health/ nutrition science news stories. There are some additional complications like a large amount of vested interested funded studies in nutrition, and it being incredibly difficult to do double blind controlled type studies that make that field even worse at the back and forth. With these studies being primarily statistically designed the large number of studies actually increases the chances of getting 'outlier' type studies just by random chance. The large number of studies rapidly released directly to preprints also probably increases this type of back and forth noise. You might have noticed that I almost always seem a little hesitant sounding when posting about single studies. Some strategies for helping incorporate news like this: 1) Verifying that people involved are qualified and respectable. A number of the things to look for have come up before. 2) Sample size and good design like double blind. 3) What was the consensus before (if there was one)? How strong was the consensus? 4) What is the theory/ mechanism of action? 5) How well does the new idea mesh with existing theory/ how well supported is that theory? The last 3 points can be tricky in areas that are less familiar, but very helpful in preventing you from feeling like experts are just constantly changing their mind (they aren't). When it comes to masks for example while the respiratory droplets where probably a newer idea to many of us, their role in spreading some diseases was well established. Similarly the method by which improvised masks (not the N95's) work is very consistent with the impact of humidity on decreasing the spread of other seasonal respiratory diseases. The only real question at the beginning was to what extent is Covid spread directly through the air vs. surfaces. Similarly the majority of work indicates hydroxychloroquine does not seem to have a positive impact and much of it has been negative enough to force early stoppage of studies. How it would act protectively has always been a stretch at best, whereas other things like Remdesivir clearly target viral replication or other reports of potential benefits with anti-inflammatory drugs tie into the developing understanding that the runaway inflammation tends to be the biggest culprit of damage and death.

I could have sworn that they had stated months ago part of the initial no mask recommendation was based on preserving them for healthcare workers. I can get why enough people might have missed that or I may have read more between the lines. It's extra frustrating because as we have seen in a number of different cases now just slowing the spread is also giving us time to properly test therapies and find some things that actually reduce the death rate, so it isn't just a wait for the vaccine.

A couple of key things about that Ioannidis study. It is using a conglomeration of measurements from other studies. This is a meta analysis, which can be done well, but involves a substantial level of statistical background (beyond my ability). His methods read like something one of my high school students would come up with, not what I've seen other places. Second it is using antibody tests and I have yet to see anyone address how to deal with properly accounting for false positives. If you look at some of the ranges of reported numbers in his collection of studies it goes beyond 'there is substantial variation across groups' to a concerning lack of agreement. I just don't have a lot of confidence in that method. Especially when we have a death total closing in on twice the worst flu season of the last 10 years telling us clearly that there is some substantial additional mortality.

This is probably one of the toughest situations to handle, publishing outside your 'area'. Scientists interest can and do legitimately evolve over time, and theoretically part of earning the PhD is that you demonstrate the skill to move in new directions should you choose. However, it can also signal goofy motivations and questionable behavior. For example a computer science trained individual publishing anti-evolution nonsense. Looking at Stutt's background he is a trained mathematical modeler in epidemiology that had been focused on plants. I would consider that fairly close skill sets. Still worthy of some caution, but not an automatic don't take this seriously.

I have a number of anecdotal sources that also suggest HR folks screening processes don't accurately reflect them being 'desperate'. As an example of them being too selective my son couldn't get an interview at any of these manufacturing places despite reliable jobs in college and a degree. He eventually went the temp agency route, magically a year later when he started applying he got a new job in 2 weeks. I've known other people who run into variations of the 'over qualified' nonsense. Or even looking at some of these posting these days and oddly specific requirements.

Thanks for the appreciation.

Super helpful perspective. And my wife was very much on the frontline during the last measles outbreak in MN, so I am very familiar with that frustration.

I whole-heartedly agree that every step of the estimation is subject to significant swings. Sorry If my last point came off directed toward you I was just trying to concisely restate my original thesis, your request was entirely reasonable. For the sake of discussion 1) Attributing 100% of the life expectancy gap to systematic racism is problematic, but a significant portion of the male female gap also has some clear biological causes like the lower genetic load from having two Xs vs. one, and at a crude level of explanation hormone differences. Trying to extend looking for biological explanations into race of course is fraught with difficulty, leaving only environmental explanations most of which would likely be grouped under systematic racism. 2) That level or granularity could make some significant changes 3) I'm curious how you arrived at 90%, I've tended to use 66% based on the early R0 number and equation. I know that Michael Osterholm has said it might get up to 70% to achieve natural herd immunity. I'm sure a formal immunization campaign would target a higher number than 70%, but that is a slightly different sort of end point.

I'll go for bullet points *police brutality is a central theme and catalyst to the protest, but many of the speakers broaden and speak towards systematic racism. * From a training standpoint in education and from my wife's experience's in healthcare things are generally lumped into systematic racism with police brutality just 1 example, so as a matter of how they think about the the issues it is going to be influenced more by that perspective than just a singular focus on brutality. * I used the life expectancy difference as an estimate for the cumulative impact of systematic factors, an approach I had seen used elsewhere particularly in noticing the decline in rural white America related to the trending economic decline since the 1970's. *It was also they only way I could think of to try and mesh the numbers without a really sophisticated analysis. #overlyhonestmethods * The most recent comparable for Covid I could find is from https://wellcomeopenresearch.org/articles/5-75 and would give you a 12 years lost on average per covid death. Those are not identical measurement types, but in a loose comparison I think it works ok. *So the covid impact is noticeably higher in terms of years, but as an acute problem it is only a 1 time 'cost' whereas the systematic racism accumulates and will continue to accumulate damage over time. * 42 million African Americans * the 3 year life expectancy gap = 126 million years of life lost, 12 years* the current highside estimate of 1% mortality and 2/3 population needed for herd immunity = 26.4 million years lost *Thanks for pushing me to finish making the estimation, on my initial eyeballing I still thought worst case covid was going to come out modestly ahead, but the population size difference between all African Americans and only 1% or so dying from Covid really flips that estimation around. * The initial core argument was only that the 2 would be close enough for a reasonable person in the field to act like they were similar scale problems without resorting to ascribing bias or tribalism as explanation.

So remember when I said multiple times that the simplified messaging was key to communicating. Perfect example here. You are complaining about a double standard, but as the quotes from the healthcare letters indicate they are motivated and arguing for this course of action based on public health needs of the black community (aka a single standard is being used). Were they saying do whatever you want? No. They were arguing for not using 1 public health crisis to prevent improvement on another. Looking at the Life expectancy data we can observe a 3.5 years difference between black and white Americans https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf This now becomes the challenge do you want to sort through and figure out how comparable that is to covid? The chronic vs. acute makes it tricky, but just looking at some numbers makes it clear that these are 2 public health issues of a similar enough magnitude to be comparable. To be clear I don't necessarily think it's the correct call, but it is close enough to recognize it is legitimately debatable. That is the real importance of the free speech right, reminding ourselves to do try and give folks a chance and hear them out.

I would currently put actual insurance costs in the 'fog of war' category as well. Given that large percentage of deaths were coming from high cost insurance groups there is potential lower costs short and medium term as well, but with no direct experience with the numbers and system on that scale I can't even begin to ballpark how that would affect things.

Good question, so the short version some quick skimming indicates that the observation of higher winter death rates exist goes back to early Western medicine, but the overall picture is still only modestly understood. Flu itself is only modestly responsible for the increase, with other respiratory infections causing some more, but cardiovascular disease being the single most identifiable factor. https://www.demogr.mpg.de/books/drm/003/2.pdf https://pubmed.ncbi.nlm.nih.gov/18959541/