Cuts have consequences

I saw this Tweet via Chris Kessel:

My letter I received after I tried out for the SJ select team. I didn’t make it, which led me to then try out for the @medfordstrikers and was determined to not let this failure derail me. pic.twitter.com/FLLEnNyykr

— Carli Lloyd (@CarliLloyd) April 29, 2020

Very cool Carli! Thanks for sharing.

Alex Morgan is another awesome player who famously wasn’t good enough to make the cut at her first competitive tryout.

Michael Jordan is another.

Not being picked is devastating.

But it lights fires in true competitors like nothing else and forces others to think hard about how much they really want it, and maybe realize it’s time to move on.

As a coach, I wondered if I ruined kids’ potentials with too much positive reinforcement. Most great athletes have that story of that one coach that said they weren’t good enough, and they’ve been trying to prove that coach wrong ever since.

After that thought crossed my mind, I then wondered if some of those a-holes coaches had also figured that and said that to every player to see which ones would prove them wrong.

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Does your organization have a good BS detector?

On his regular livestream, Scott Adams said he finally figured out that his expertise is detecting BS. That’s why he’s often right when against supposed experts.

I fancy myself as a good BS dectector, too, though orders of magnitude less prolific. For now.

I realized as he described his BS detecting abilities that BS detecting is a function that organizations can benefit from and often lack.

Organizations have a tendency to silence dissent. I’ve seen that in companies, non-profits, education and government. It even occurs in non-hierarchical environments in the form of groupthink.

The obvious reason dissent is silenced is that leaders don’t like it.

A more subtle reason dissent is silenced is that when allowed, it’s tough to separate the wheat from the chaff and it’s mostly chaff. Everyone’s a critic.

That’s where a good BS detector can come in handy.

Dissent tends to follow a Pareto (80/20 rule) distribution, where 80% is chaff and 20% could be useful. That is, that 20% might come back and bite the organization in the butt and dissenters will go on the evening news and tell the world how they tried to sound the alarm, if only the leaders had listened.

Good BS detectors can help find that 20% that the organization should think about.

Good BS detectors can also help sniff out the leaders’ own BS, which helps make the leaders’ messages even more battle tested and convincing.

At the start of the pandemic, good BS detectors sniffed out early that the WHO’s guidance on mask usage was BS. Adams was one. I also was early to the game on that one.

I think BS detectors could be useful on boards of organizations and in government. But, is not limited to those higher level functions.

I used my BS detecting skills to make a couple of internal company applications that I was responsible for, better and more successful, by sorting through feedback –which was mostly BS — and talking to people to cut through their BS to get to the true heart of their complaints.

A BS detector doesn’t have to be a person. It can also just be an activity, like brainstorming. “Okay, let’s turn on our BS detectors. What BS will people sniff out of this?” Just granting the permission to detect BS will let lots of it be detected and help overcome groupthink.

In the pandemic, it’s not apparent to me that government leaders have good BS detectors and that makes them look foolish.

What I currently believe about Covid-19

Here were my thoughts about Covid-19 on 3/28 & 3/30.

I have not yet seen convincing evidence to change my mind, and I think there is some evidence coming out just recently to support some of what I believed then that was ‘out there’.

My second bullet was “it’s probably more widespread than we think.”

Antibody tests, so far, are validating that. Which means it’s not as fatal as originally thought. This is also consistent with early high estimates of H1N1 that were later revised when a better view of total infections became available.

My 7th bullet was that there were C-19 deaths prior to testing.

That has recently proven true. This might be an indication that it spreads at rate more like a typical virus.

My 8th bullet was that I have little faith in the numbers reported by government or media. I have even less now and I think more people, after hearing Dr. Birx explain the loose criteria for classifying COVID deaths, lost faith, too. I’ve noticed that since then, the interest in the daily numbers has waned, considerably.

Generally, most folks seem to be catching onto the reporting tricks the media plays with numbers. A recent trick is to report a high case or death count for a day, to make it look like the trend is turning bad, but then a few paragraphs into the story note those were numbers that occurred on previous days, but weren’t recorded on those days.

I’d like to give the media the benefit of the doubt, but they almost always gravitate to the most dramatic.

Here’s what I would add to those thoughts now:

• While there are differences in curves from all areas, statistically they look too similar (and/or may be subject to testing/recording criteria) for me to yet be convinced that there is one package of actions that outperforms all others.
  • This means that, likely, basic measures like masks, hand washing, 6 foot spacing, isolating the most vulnerable and canceling big indoor events are likely as good as any.
• The U.S. leads in most categories for one reason: absolute number of tests. This is what I would expect if the virus is making a wave through the population at 5-10% at a time — the more testing you have, the more cases you will find and the more confirmed deaths you will be able to report. That also means that other nations are likely missing large numbers that have been infected in their confirmed case counts, too.
• We still do not have good numbers on how Covid-19 has impacted net deaths. I expect there will be an incremental impact (deaths that would not have occurred for years), a timing impact (deaths that were moved up a few days to a few months) and a categorical impact (deaths that would have occurred due to other circumstances, but were coded as Covid). It will take time to peel these apart.

 

What happened to the curve in Scandinavia?

I saw this CNN article referenced today as support that Sweden’s approach “didn’t work.”

It reported Sweden’s coronavirus deaths are higher than Denmark, Norway and Finland, though not as high as Italy and Spain.

A key missing piece of data, though, is the proportion of each population thought to have had coronavirus in each country.

Since Sweden’s approach was thought to get them to herd immunity faster, is it possible that they are further along their infection curve?

Governor Cuomo recently reported that 20-25% of New Yorkers have likely already the virus. What’s that number for Sweden and these country countries?

Let’s say 50% of Sweden’s population has been infected compared to 10% of Denmark’s.

Would it be fair to compare the death of the two countries at this point?

Do we think Denmark has avoided the deaths that might occur when the next 40% of its population becomes infected, or do we now believe that lockdowns have avoided the eventual spread of the virus to a significant portion of the population?

If so, why? What has changed?

Can we get Covid-19 again? And, spot the ‘no evidence’ trick

Media outlets recently reported that there is no evidence* that people who have already been infected with COVID-19 can’t get infected again.

I believe it is true for all viruses that some people will get infected multiple times.

When we hear reports about people who contract Covid-19 for the second time, as I’m sure we will, we should remember that’s not news.

The news is whether people are contracting it multiple times at a greater, roughly equal or lesser rate than is typical with other viruses and by how much (which is something media has been horrible with during this pandemic).

If the news story does not provide that information, ignore it. It’s tabloid journalism.

*Be wise of media’s “no evidence” parlor trick. When I hear those words in a news story, my antennae go up as I try to figure out how are they trying to trick me.

A good place to start is to ask if there’s evidence to the contrary. In this case, is there  evidence that people do get infected again at rates higher than other viruses that we know about?

If you pay attention, the media likes to use this trick to discredit statements made by folks who they are not fond of.

It looks something like this: “[Person A], without evidence, accused [Person B] of [doing something bad].”

Take note of how that same headline looks for folks who they are fond of:

“[Person B] accused [Person A] of [doing something bad].”

 

 

 

Oklahoma Governor doesn’t let Chris Wallace move the goal posts

Tonight was the first time I watched Chris Wallace. Most likely the last, too.

The only reason I watched him was because there was nothing else on while I was making dinner and he was going to have the governor of Oklahoma on to discuss re-opening and I wanted to hear what the Governor had to say.

The interview went something like this (paraphrased from memory):

Wallace: Governor, as your state sets to re-open, are you worried about a second surge?

This question shows either a total lack of understanding by Wallace for the reasoning behind the lockdowns or a willful moving of the goal posts. Either is enough for me to not be interested in watching his show again.

The governor, instead, answered the question Wallace should have answered and provided a good template for others looking on how to discuss their re-openings and keep the media from moving the goal posts.

Governor: Let’s first remember why the shutdowns were made: to build hospital capacity and get enough PPE for our front-line workers. We’ve accomplished that and we’re ready. At the peak we and 554 in the hospital with covid-19, and no we have 300, statewide.

Lockdown metamorphosis & holding out for a hero

According to the original rationale for the lockdowns — flattening the curve for hospital/ventilator capacity — we should be much further along in the process of re-opening.

Clay Travis, a sports dude, has one of the better write-ups on the WHOLE Covid-19 situation that I’ve seen here. He describes how the lockdown rationale has evolved:

Back in the flatten the curve days the primary argument for the national shutdown was that we didn’t have enough ventilators and hospital beds and many people would die as a result if we overloaded the hospitals with patients. Now that we aren’t in danger of overloading hospitals the argument has shifted from we have to avoid overloading hospitals to we can’t end the quarantine without a vaccine because if we do then infections will spike again resulting in a new need for national quarantine.

I’m not sure I agree about its about waiting for a vaccine. But, it does seem like there’s hope of finding a miracle cure or the virus will die out, without being too specific.

Arnold Kling has also been good on this throughout, and describes the “morphing” of the lockdowns here:

The original purpose of the lockdown was to “flatten the curve.” That meant that, relative to a no-lockdown baseline, we would trade a lower rate of illness now for a higher rate of illness later. The question about a lift-the-lockdown scenario becomes: how many people are out there who as a result will get the disease in May or June who could have been cured with adequate treatment and who cannot get adequate treatment in the near term but who could get adequate treatment in July or August.

I agree.

It may be even worse than what these two gentlemen describe, as I’m not sure “closers,” as Kling dubs them, have any criteria for considering a case for opening beyond their favorite celebrity expert telling them it’s okay to have such thoughts.

Short-version of Marc Andreessen’s “It’s Time to Build”: Can’t Because Regulatory Capture

I enjoyed Marc Andreessen essay, It’s Time to Build, as did others.

I think he does a good job of identifying the key obstacle gumming up the works of America’s innovation engine, but misses the true underlying causes.

He identifies a lot of problems, like shortages of basic stuff during Covid-19, and skyrocketing home prices in San Francisco and pins the blame on regulatory capture.

For example, the folks who want to keep the quaint feel of San Francisco have the power over the zoning regulations which prevents builders from building more housing units to meet high demand. When supply is way less than demand, prices rise.

He writes (emphasis added):

The problem is desire. We need to *want* these things. The problem is inertia. We need to want these things more than we want to prevent these things. The problem is regulatory capture. We need to want new companies to build these things, even if incumbents don’t like it, even if only to force the incumbents to build these things. And the problem is will. We need to build these things.

But, why does regulatory capture exist?

Concentrated benefits and distributed costs.

The regulation is worth a lot more to the folks who fight for the regulations (the benefit of the regulation is concentrated on them) than the folks who are hurt by them (distributed costs), so the latter group doesn’t typically have enough incentive to dig in and fight for it.

I liked these two paragraphs:

The right starts out in a more natural, albeit compromised, place. The right is generally pro production, but is too often corrupted by forces that hold back market-based competition and the building of things. The right must fight hard against crony capitalism, regulatory capture, ossified oligopolies, risk-inducing offshoring, and investor-friendly buybacks in lieu of customer-friendly (and, over a longer period of time, even more investor-friendly) innovation.

I agree. But what would make them willing to give up their regulatory capture (which comes in the forms of crony capitalism)?

You will have to convince voters to vote for politicians who are for limiting their own powers of regulation, so they can’t sell that power back to their friends for really good sounding reasons.

But many voters on all sides want to vote for politicians for the opposite reason. They want their politicians to put in place the regulations that they favor. That empowers both sides to keep writing regulations.

The left starts out with a stronger bias toward the public sector in many of these areas. To which I say, prove the superior model! Demonstrate that the public sector can build better hospitals, better schools, better transportation, better cities, better housing. Stop trying to protect the old, the entrenched, the irrelevant; commit the public sector fully to the future. Milton Friedman once said the great public sector mistake is to judge policies and programs by their intentions rather than their results. Instead of taking that as an insult, take it as a challenge — build new things and show the results!

These folks aren’t into the whole ‘try things’ mindset. It’s all-or-nothing. They, like the crony capitalist, are monopolists. They would rather not have competition to their ideas.

They’re terrified that if given a choice, people won’t choose their solution, so the best thing to do is get rid of the choice.

Many of them think that solving the problem is just as simple doing what sounds good for the whole system and never understanding that competition is the best way to discover what can work better. Without competition, you get what?

Regulatory capture.

It’s a big circle.

Can we learn something from our COVID-19 heroes about the ‘second wave’?

The headline and subtitle of this Atlantic article made me chuckle because it’s true.

Calling Me a Hero Only Makes You Feel Better

I work in a grocery store. All this grandiose praise rings insincere.

 

While reading it, it also made wonder, has anyone looked at the spread of the Covid-19 among our front-line heroes?

Many of them never stopped interacting with large swaths of the population while the rest of us have been cocooned.

It seems like, for all the folks speculating about what might happen when we reopen the economy, we could reduce our guesswork some by looking at the folks who have stayed open the whole time.

Has it spread more or less than folks who have stayed-at-home and by how much?

I’ve seen news articles reporting the cases of front-line workers who die or the case of the meat packing plant in South Dakota (which may be more attributable to their home lives, than their work lives). But, overall it seems like a lot spottier than what I would expect for folks who have continued to interact with others on a daily basis.

If we were to discover that is has been about the same or less than everybody else, folks might point to measures they’ve taken that might be effective like wearing masks (though I haven’t yet seen employees wear masks), hand washing/sanitizing and 6 foot social distancing.

But, if that’s the case, good. We can feel even more comfortable that we can get back to it and doing those things will help.

Random COVID-19 testing in Kansas City area shows 3.8% have it

According to this article, Johnson County in Kansas tested a random sample of people for COVID-19 (not antibodies) and 3.8% came back positive.

Health officials have revealed on April 16 the results of the past six days of randomized community testing.

Tests show that 3.8% of those who participated tested positive.

That doesn’t sound like much.

But, if this is representative of the population in the KC Metro area then about 80,000 people out of a population of 2.1 million (KC and surrounding suburbs in Missouri and Kansas) would have COVID-19 right now.

If percentages about hospitalization (about 20% of confirmed cases) and deaths (1-5%) are accurate, KC hospitals should have about 16,000 COVID patients and 800 and 4,000 deaths.

The KC area currently has about 1,000 confirmed cases and 70 deaths.

It is unclear how many are being treated in hospitals because that has not reported. But, I take that as an indication that they are well below the 16,000. It think it would be big news otherwise.

If we carried that number out to the population of the United States, that implies about 12 million cases of COVID-19 currently.