TDS, Revisited

I’ve been trying to understand the real causes of Trump Derangement Syndrome for the two years it took to develop a reasonable working theory.

It’s all been swept into the memory hole now, having done the job, but many of us still remember the madness: The fake Steele Dossier, fake Michael Avenatti, fake impeachment, the fake charges against Flynn, the confused Mueller, the weaponization of Coivd19 against Trump, and many others. It’s a little hard now to believe anyone would be fooled by such obvious nonsense, but half the country and a many other counties were. Or pretended to be.

At a more personal level, I watched  seemingly compassionate, moderate, sane people completely lose their everloving minds. This wasn’t a thoughtful objection to policy, or Trump’s erratic behavior, petty vindictiveness, bizarre communication style, casual relationship with truth, or any other of his undesirable qualities. Many of his supporters held their noses at those things.

We know this now because Biden clearly is as petty and vindictive as Trump, and he gets a free pass.

But they didn’t hate him. The TDS people hated him. A mass, visceral hatred I had never seen before. A hatred that was not swayed in the least by facts, or reality. A hatred that made destroying friendships and families a noble cause. A genuinely frightening hatred.

Once the TDS had set in, minds slammed shut to any information that would question the pure evil that was this man. He became an enemy of the LGBTs, and a racist – especially toward blacks. At the peak of the insanity, he was an anti-Semite, despite moving  the embassy, and having a Jewish son in-law and daughter.

To be fair, Trump said hurtful things toward Latin American illegal immigrants while he was running, and a good case could be made that he was a racist toward these groups. I rather doubt it – I think the issue was mass illegal immigration – but I can understand why people think otherwise.

As for the racism toward blacks or animosity toward LGBT, there isn’t a scrap of evidence, and much evidence to the contrary. He passed a long promised and never delivered but overdue  prison reform bill that benefited jailed blacks, mostly. He worked to create jobs for everyone, including blacks, and either did it, and/or took credit for it happening anyway. He seemed indifferent to the LGBT community, which perhaps is bad. But he clearly didn’t have an axe to grind there.

Yet we heard that he was hater. Every. Single. Day.


For a while I thought maybe he projected some sort of creepy Uncle Ernie vibe that women picked up on, but I was missing. Like Biden does now.

So I asked.

The answer was consistent: “Children in cages, and pussy grabbing”.

That was something to work with. Children in cages was silly to anyone without TDS with a modicum of curiosity and reading comprehension, but it was clear that once the disease set in, it slammed the mind shut. Hard. And the only information that got in was anything that kept the hatred going. Accuracy was not important to the TDS afflicted.

Maybe is was an Uncle Ernie thing, or offense at his vulgarity. But on reflection, the many of the TDS crowd were pretty vulgar themselves, in a juvenile attempt to offend imaginary Christians that lived in their heads, and the rest gave them a free pass. I don’t think anyone was actually offended.

But then I thought carefully about the Access Hollywood event, and what he said: “They let you do it.” Now this is certainly not my area of personal expertise, but I have observed over a lifetime that some women do indeed behave this way around famous, rich or powerful people. I assume everyone knows this, and thankfully decorum stops us pointing it out.

He pointed it out.

He’s rude.

But that still didn’t quite explain the magnitude of the TDS wave.

Like most people, I figured he was toast after that event, and I wasn’t sad. There was a good slate of GOP candidates in that election, and a few of them would have made good presidents. Besides, like most people, I assumed he would blow it and we’d get 16 years of Hillarybama.

That’s not what happened.

He apologized, sort of. He didn’t flinch. He didn’t back down.

This is root of TDS. The baby boomer left had been infiltrating every institution for my entire lifetime. They were patient, subtle, determined and very intentional. By the time Obama was elected, they had introduced an insidious form of racism and sexism, which was actually a tool to create structural advance in hiring, pay and promotions for lefties like them, and cleverly disguised it as anti-racism, everywhere. They were influential at the top levels of power, through a carrot and stick strategy best described by the reporter Nina Burleigh, “I’d happy to give [Bill Clinton] a blowjob just to thank him for keeping abortion legal.”, with a side of would you like to keep your job?

Allies = insurance. For a while.

They controlled pop culture, and had a brilliant run at programming people through satire, humor and music.

And Obama was the Messiah. It’s hard to describe this any better than the demi-god himself: “We are the ones we’ve been waiting for.”

Trump was genuinely dangerous. Not like McCain or Romney, who didn’t even need a blowjob but fell for a fake promise to be an honorable lefty, if they played along.

He didn’t back down.

Now the reason that this was bad is that it turns out that half the country wasn’t down for this agenda, and found themselves powerless and mocked. For decades. And getting worse.

Everyone, except me it seems, got it immediately. The entire century long progressive agenda to destroy freedom in the Western world and create a new class of authoritarian ruling royalty was at risk. The pitchforks might come out.

So they crushed him. And then they crushed a handful of goofy people taking selfies in capital. A show execution.

Problem solved. Polite people don’t talk about any of this much, I presume because they are embarrassed at their behavior. And it worked.



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This One Will Likely Get my Nexus Card Revoked

I’ll do it as lovingly as a I can.

Recently, I’ve seen a series of fb memes from my friends in Nova Scotia. They say, basically, don’t be rude to retail employees enforcing Covid19 rules, because they didn’t make them – they are just doing their jobs.

I’ve been on both sides of the counter, and each time I read one of these I thought yes, please. But at the same time, something was bugging me.

I reflected on our 5 weeks stay there this summer. During the 100 or so possible opportunities for retail rage, there were 3 mild occurrences. All directed toward us, and unprovoked. Two at Wal-Mart, and one at The Big Stop. The latter was unpleasant enough that we didn’t eat there again, despite it being one of the better restaurants in the area and a long favorite.

Then I reflected on 35 years of spending summers there. Ignoring  Air Canada, which is a really just an example of why monopolies are horrible for everyone,  there were perhaps 10 retail rage incidents, all minor, and all directed toward us. It’s a polite place.

Each day, about 100 million people trust the auto shutoff on gas pumps to work correctly. Because it does. But try to lock the handle in Nova Scotia and you will be harassed – immediately – by a kid behind the speaker. Object to this, even politely, and the RCMP will be called. You won’t be charged, just threatened. Now, perhaps that’s how it should work. You are breaking the law, after all. But ask that kid or the cops why the law exists, and they won’t have a clue. Because they never thought about it. They just do it.

Ask why this seems to be OK everywhere else on the planet, and people defend the system reflexively.

Over 35 years, we’ve watched as the province, country or town passed seemingly minor laws, no single one being much to get worked up about. Some were silly, like solving the problem of rising gas prices by restricting changes to once a week. Making opaque garbage bags illegal so people could (and did) make sure you were recycling was a little creepy. So creepy that you eventually got a budget of how much trash you could dispose of in secret, and  how much was public. Many were expensive and ineffective, like requiring liability insurance for ATVs as a solution to crash injuries. Lots of new training, permits, inspections, gear – all in the good cause of safety but somehow becoming a powerful tool to cause harm to competition. Plastic bags, straws…

As far as I can tell, most folks there see this as good and natural progress. I think the cumulative effect of all these laws on freedom is under-appreciated.

It has been good for the governing class, with enforcement workers growing in number and wealth. Good work if you can get it.

But it seems to have created a sort of militant busybody army of people who not only enforce the rules, or turn you in, but that seem to love it.

Too much.

But maybe it’s all just very progressive, as the entire rest of the world has adopted the same model during the Covid19 years.

I guess maybe that’s what is bothering  me.


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Late Stage Covid19 Trials of Arrogance Disappointing But Not Ending

Recent news: The CDC has admitted that the vaccine doesn’t stop transmission of the virus, calling into question the strategy of carpet bombing the disease out of existence, and making a mockery of deeply held facebook wisdom that the unvaccinated are a danger to the vaccinated, when the opposite is (also) true.

Natural immunity after an infection and recovery appears to last longer and be much stronger than vaccinated immunity. All immunity fades rather quickly, likely in a 6-9 month timeframe.

The latter two points would make a mockery of firing people who have natural immunity and do not want to get vaccinated.

In a sane world, guided by science.

Like Jen Psaki, l’ll cycle back to these points at the end.

Show me a model with two roughly equal sized reasonably small cycles and a subsequent cycle four times as large as either of those, dropping to near zero in between all of them. For bonus points, show a rapidly moving cycle move through the unvaccinated population after the rate of vaccination had reached 60% in the general population, 4 months after wave 3 was exhausted. Now explain any of this.

Everyone was wrong, and continues to be wrong. Even Professor Neil Ferguson.

Well, everyone in a position of power. I’m almost certain that somewhere in Pfizer or the CDC (and maybe China) there are people emailing spreadsheets titled “COVID19, PLEASE LOOK…”, and being ignored.

For the first time likely ever, everyone had access to the same data at the same time. The data was reasonably clean by big data standards, and enough computer power and modelling software was available that amateurs could try their hand at modelling this thing. I did.

I was wrong. Repeatedly.

The professionals all came out high, and often very high. This is to be expected, as it seems somehow better to be needlessly over-prepared and not need it than to be under-prepared. This is not actually true, as all allocations of resources take from something else. Indeed it remains an open question what could have been accomplished if we had had spent the money and human capital spent on C19 on cancer, heart disease. And politicians will use any convenient real or imaginary thing: war, global warming, a pandemic etc. to secure their jobs and income. It’s easy to understand why the press and the politicians guessed high. Clicks, money, power, vanity.

But curiously most of the amateur models also showed a large bias toward “too large” errors. And many of the errors were inexcusable – not recognizing that disease targets – nearly exclusively and ruthlessly – the elderly in poor health.

Why the bias toward doomsday scenarios? I don’t know. There seems to be a demand for them.

One of the first mistakes I made was hoping that a sharp drop-off in infections after the first wave in many geographically local groups at about the 35% infected (positive PCR-RT) was the end of the virus in that area. While the pattern seemed to be robust and repeatable, wave 3 put an end to any such hope.

The second mistake was not accounting for the time the virus takes to travel geographically. To be fair, lots of people made this mistake, and in Feb-Jul of 2020 I read (and wrote some) many assessments of what was working and not working that were in fact attributing actions – social distancing and masking – that were actually doing little or nothing, with geographic movement of the virus. Indeed the first lockdowns happened around Feb-Apr 2020 globally happened in many places yet to be infected. And some, far too late to help. In a handful, early enough, combined with boarder closings to suppress the virus. At least until Delta.

I continued to model until the news that variants were in the wild, and the data dried up. It became near impossible to attribute a death to a mutation, or not, with publicly available data. This remained true until vaccination rates reached about 60%, and Delta started to rip through every almost every community. The speed that it traveled was visible even in crude data. It was unlike anything else. Also, it wasn’t supposed to happen.

But I was in good company getting Covid 19 wrong:

  • Nancy Pelosi told us that C19 was not dangerous, that it was safe to visit a busy market Chinatown, and that any belief to the contrary was rooted in racism.
  • Remember Two Weeks To Flatten The Curve? Did they actually believe this? Based on what? That ultimately ended when the pain became so high that people finally paid attention and realized it didn’t work.
  • The models were wrong. Tragically, comically wrong. New York reached the status of the state that killed more of its citizens per capita with C19 sooner than any other. But even with that, the modelers convinced Cuomo to send C19 infected people from hospital back to nursing homes in preparation for a wave that never happened. He literally made the choice to kill old people with the hope of saving younger ones, and killed the older ones. Using science. Then he made money off a book he wrote about leadership and good governance in C19 times.
  • Every C19 death on the planet was once the fault of Donald Trump and his idiot followers for failing to take simple, scientific measures. Joe Biden would fix it quickly fix it using science. That was more than a year ago.
  • Masks don’t work. They’ve never worked. The data is beyond overwhelming on this. They know it. At some level, everyone knows it. The politicians ignore their own rules. If this is affront to your common sense, consider what would happen when you exhale a lung full of vape through a mask. (
  • Arresting windsurfers, the grocery dance, “phases”, whatever Australia did. Little evidence it works.
  • Hydroxychloroquine, Ivermectin, monoclonal antibodies, and recently a promising anti-viral from Merck. Why the odd political war to shame therapeutic treatments and promote vaccination as the only option? Why not try all of them, and then in combinations? Conspiracy theorists blame it on BigPharm greed, but there’s something else going on here that’s weirdly religious. Treatments have become somehow good and bad. The things the smart people do, and do not do, without knowing why. Weird science
  • The PCR-RT and “cases” nonsense. It was conspiracy theory stuff until New York Times said it was all true.
  • A little more than a year ago, one got banned from social media for spreading info that C19 came from a lab, not a meat market. Today we know it came from a lab, we know which one, and we know that US was funding this research. The same people guiding policy now always knew it, because they were part of it.


  • Asymptomatic (as opposed to pre-symptomatic) spreaders. Mostly nonsense.

One of the odd things I noticed while travelling the world during C19 was the widespread belief that we were doing it right but someone else was not. There seemed to be a built-in desire to make other people conform, and to mistrust and blame them. An unearned mistrust, in my observation. Most people on the planet were trying the exact same things and everyone was and is highly motivated to survive.

At each stage of this, and in each place, there was an ingroup and an outgroup. The outgroup might be students, tourists, people who don’t stand far enough apart, or don’t wear a dirty cloth over their mouth and nose sometimes, Trump supporters, the unvaccinated, motorcycle drivers, etc. And each time the anger that we should feel toward our bad luck and unfortunately wrong actions we were forced to take by governments was redirected at the outgroup. For the purpose of controlling everyone, I suspect. For our own good.

It’s a brilliant strategy. Indeed people demand it. They demand you tell them who to despise and what to do next. This seems to creates a kind of “selfless-gestalt” among many people that makes them proud to be controllable, for the good of the entire race. The mechanism might be helpful for survival of the species under attack, if used properly.

Where are we now? It’s a very complex system.

Until recently, like most people I think I believed these things:

  • The vaccination reduces hospitalization and death dramatically.
  • The unvaccinated get C19 more often.
  • People who get C19 spread C19.

It seems reasonable from this info to assume that reducing the spreaders and vulnerable hosts to virus should starve it and we can eradicate it. The only reason this hasn’t already happened is lack of participation in the Gestalt Of Not Self. I believed it, three months ago.

Now we know:

  • Vaccine immunity isn’t good as natural immunity (post infection recovery).
  • Immunity doesn’t last that long.
  • Immunity is less effective against mutations.

If it weren’t for mutations, vaccines would be easy.

From an evolutionary adaptation perspective the ideal host does not die from the virus, is healthy enough to move around and disperse it, but does not quickly or completely kill it.

The host who dies is a dead end of a path of spreading. The host who fights off the virus and all its competing mutations quickly and completely is an evolutionary dead end.

If your goal is to eradicate the virus, you want as many of the third, and as few of the first types of hosts possible.

Vaccines that allow almost everyone to completely fight off a pathogen , like Smallpox and Polio, both protect the vaccinated and push the disease toward extinction. Vaccines like the ones we have for C19, that provide only partial protection from infection actually increase the number of the first group, which may make mutations worse.

This is not an accident, or unintentional. If your goal is to reduce illness and death, a “leaky” vaccine works well. The risk of mutations is a variable but presumably one well understood in the development and testing process.

It’s worth noting that evolutionary “need” for the virus to have more host who are only modestly ill and recover (and spread), and fewer seriously ill or dead hosts provides pressure that tends to favor less harmful and lethal mutations over time. This is a good thing.

There is a theory ( that leaky vaccinations increase mutations, and potentially dangerous mutations, by turning vaccinated hosts into “sorting machines” that kill off weak strains and allow more harmful strains to propagate. There is a real world example and study of exactly this from our experience farming at scale.

Some of the factors that determine if a vaccine will contribute to harmful mutations:

  • The rate of mutations (high for C19).
  • The innate genetic code – the dangerous combinations that are possible from mutations (one gene, two genes …). This is related to the complexity of the virus (more complex is good, for us; C19 is more complex than the flu, but less complex than Polio and Smallpox).
  • The degree of vaccine leakiness.
  • The vaccination distribution, specifically how many are / will be infected post vaccination.

The Covid19 vaccines have without a doubt saved lives of the vaccinated. So far. It’s entirely possible the vaccines created Delta. Delta is killing the unvaccinated, mostly. A decision to remain unvaccinated is highly questionable.

Yet facebook wisdom of the day is sure that the unvaccinated are the dangerous ones, and that if we just all push for 100% vaccinations the disease will be eliminated. This is not based on science, and has not been the result so far.

Most of us a now due for boosters, six months later.

It’s worth noting that we “got lucky” with C19, in that it kills only a fraction of the population, and they are easy to identify – old people with diabetes, heart disease, other illnesses and obesity. Sadly, the vaccine has had less of an effect with this demographic that we would hope (

“According to an analysis of British data by the Financial Times, a vaccinated 80-year-old has about the same mortality risk as an unvaccinated 50-year-old, and an unvaccinated 30-year-old has a lower risk than a vaccinated 45-year-old. Even a 42-fold reduction, as was found in King County, would only be the rough equivalent of the difference between an unvaccinated 85-year-old woman and an unvaccinated 50-year-old.“

If a mutation changed this, and the disease attacked the general population equally, like the Spanish Flu did, the results would likely be apocalyptic.


  • We could all stop pretending that we are experts, recognize that the science is complex and a process of unwinding unknowns over time.
  • The “experts” could recognize this too.
  • We could stop blaming others.
  • Politicians could stop using this as weapon to turn us against each other.


Disclaimer: I am not an expert. I read this stuff on the internet. Some of it, maybe much of it, is almost certainly wrong. In the  past when I’ve posted about C19, I’ve been wrong almost all the time.

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Hey Millennials, Quit Yer Griping

So the system is stacked against you?

And you’ve got it all figured: Unfair tax rates allow old white men to steal money that would otherwise make everyone rich. Racism, sexism, indifference to LGBT and immigrant issues and pronouns are they key issues in modern western society; they are a terrible wrong to be righted, and can be fixed by voting the same was as all your friends do.


There might be other issues of concern. Here’s one: The structural stealing of wealth from the future.

Between the end of WWII and the nineties, the USA, as a result of being the last country standing, having a system of free enterprise and private ownership, technological progress and industrial scale experienced a wave of growth unlike anything seen before. Generation after generation correctly assumed a better, longer life than preceding one. Hard work, smart risk taking were often rewarded with success. People were optimistic about the future, and, unlike most of the world, the conditions you were born into were less important to success than hard work.

We could argue about when this ended, but it would be sometime between 1970 and 1990. It ended because the cycle ended – the rest of the world caught up, or better. Communications, travel and global supply chains created the “Flat Earth”, driving the price of labor down, dramatically. The impact of the mainframe and minicomputer tech waves in the 60s and 70s was mostly in allowing already large organizations (and growing sluggish because of it) to grow even larger. And slower. For a few decades. The PC  and communication waves were the first time tech had the potential to really revolutionize every person’s ability and every industry. And they did.

But the tech waves were also highly exclusionary. Not in the least in the ways we think they are exclusionary today (i.e. race, gender, orientation, religion, etc) but simply as result that they needed fewer, highly specialized workers. The tech crowd became the new elite. And the working class began a long slow decline that continues to this day. American society is increasingly class-oriented. Not formally, but structurally. It has never been more important to have the right parents in America that it is now.

Governments took steps to keep the good times flowing. Small ones, at first, with Regan’s “tax cuts pay for themselves” spending increases. The truth is the deficit spending is taking wealth from the future, and spending it now.

You don’t hear much about this in the news, or in classrooms. Perhaps it has been fixed, or will be, when just the right people are elected. Judge for yourself:

The reason you hear about pronouns, micro-aggressions, racism, transgender athletes and global warming is precisely because it has not been fixed, and there’s not enough war to distract you. Nobody even tried. It’s best if you just don’t think about.

We are borrowing so much money that no one will lend us any more at the offered interest rates. Indeed, we are buying our own debt with money created out of thin air, and then spending it. Economic theory tells us that this should have caused massive inflation, yet the government tells us it hasn’t. Looked at the price of a house lately? Do you really think a house built in 1980 for a cost of $60,000 is now worth $750,000. Deficits and inflation are the largest tool the older generations have to steal from the younger, and the unborn. Elon Musk? Dogecoin? 

Here’s one you might not be aware of, despite being in plain view for decades: The Trust Fund Fraud. Indeed, Medicare and Social Security are indeed massive transfers of wealth from the young to the old. Medicare for All would increase this, for the simple reason the old consume most of the health care dollars.

Education” is in on it. Universities, long thought to be the way to escape one’s born into class, have become sorting machines to identify the winners and losers in tech/medicine/finance. And if you are not sorted so, you graduate with a worthless degree, a mind full of nonsense, and an unpayable debt. University professors and administrators, like the ever growing governing class, do quite well for themselves. And government spending and loans, intended to make university more affordable, has done the opposite, do to the inflation these actions created in education.

The Diversity Industry plays a role here too. It’s helpful to the governing class, and the tech/medicine/finance/education class that you not figure any of this out. Diversity Inc. produces mountains of seemingly academic nonsense proving that the US is place where white men have structural advantage, and are meanies, which keeps people at each other’s throats while the system is changed to give structural advantage to other demographics. One of these demographics is not Millennials.

Heard of a “share buyback”? That’s where company leaders issue new debt to buyback existing shares, increasing the price of these shares, making themselves and other shareholders rich. They are taking unearned future revenue, which might be used to fund your pension (via the stock market), and spending it now. Lots of that going on.

Finally, underfunded pensions. This might be the biggest one of all. Pensions owned to retired or soon to be retired workers, without any saved money to pay them.

Perhaps you think the rich just need to pick up the slack here, and pay their fair share. It’s completely academic what their fair share is, the math isn’t remotely close to working.

Politicians know you are angry, and have happy to blame people, take more power, and make the situation worse. It’s hard to know if the governing class ever had any integrity; indeed, if it has always been this bad. But it bad now.


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Real World Covid19 Experiments

For much of last year I used publicly available data and news to attempt to create models that demonstrated which mitigations we were doing were effective, and in what order. In addition to just understanding what was going on, and being bored and confined, I have an interest in complexity theory and the ways we learn, and don’t learn.

I encountered many problems doing so, above and beyond bad data and proving causation, including the PCR-RT false positives, the difficulty of measuring  actual Vs reported Vs mandated behavior, my failure to correct for geographic spread when looking for correlations, and the non-linear nature of the spread of infections. Many measures, including disinfecting, grocery store aisle directions, 6 feet, data was just not available to even attempt to model them.

On return from Fiji in Feb 2020, I was wearing a clean NOOSH N.95 mask during travel back to the USA. At that time the outbreak at LifeCare had just been announced, but I had been watching China since December. When I traveled internationally, multiple times, in the fall of 2020, I was wearing a clean NOOSH N.95 mask all the way.

I did not start out thinking masks don’t work, and I still think that worn correctly, they are likely an effective low cost prophylactic.

During the summer of 2020, there was enough geographic variance in mask wearing that it was possible to find decent A/B comparisons, and control for most other likely important variables. In my models I have a range of “percentage wearing”, prior to late Sept, of 50% to 85%.

I’d like to say I found no difference in outcomes correlated to this variable, but I didn’t. I found a slightly worse outcome based on higher percentage of mask wearing.

After the beginning of October, there was no reason to believe the globe wasn’t masking at about 90-95%, despite widespread unsubstantiated belief that “we’re doing it, but they are not”. And save a few exceptions, the entire western hemisphere experienced the largest, by far, wave of C19 deaths. While masked to the nines.

I don’t postulate that mask wearing caused wave 3, despite the correlation. It’s possible, but seems unlikely. But there’s little evidence it helped in the least. None, really.

There are a couple of counter-arguments I want to address: It would have been worse. I can’t disprove this, but while I did find some variables that seemed dominant throughout the last 12 months, masking wasn’t one of them. And on the decay side of wave 3, there was again considerable difference in behavior between say, California and Florida, with outcomes being worse for mask states. There are few counter examples of this pattern.

Another argument, which might explain apparent success  in South Korea and Japan, is that there is a critical point of mask compliance and hygiene, and anything below that point leads to spread. This is curious and I cannot prove nor disprove it.

Arguments I will not address: I am not a doctor, I am stupid, I am anti-science, I let Trump do my thinking, I don’t care if you die.

So what variables do seem to have an effect? In my admittedly crude models, in order: global travel in/out, local travel (cell phone data), population density, average age.

I gave up trying to model lockdowns. There are just too many variables to attempt to control for. Maybe they delay things, but they don ‘t seem to change outcomes unless you stay in lockdown until a cure arrives.

There are two maybe instructive populations I’m watching now. The first is Israel, who demonstrated that at about 45% vaccinated, the disease – at least in the short to the present term – drops to near zero, and effectively zero at about 60%. But the news is taking about vaccine resistant mutations now, and the Indian variant is in Israel. We shall see in 6-8 weeks if the current crop of vaccines are effective against mutations, at least in this population.

The second is my old home Nova Scotia. After successfully maintaining a basically zero infection curve for 8 months (with travel restrictions, I suspect), the “case” curve over the last 10 days is looking more like the upslope of a wave 3. And the province has already implemented a strict lockdown, which will likely have  a high compliance. Note that there has been, and likely will not be any real change in travel policy, or masking behavior there.

Here’s what we might learn:

“Cases” went up as testing went up (1000/day to 10,000 day). Hospitalizations and deaths have not gone up … yet. If cases grow but health outcomes do not (in proportion), the crisis might be a data ghost. I believe the PCR-RT false positive problem resulted in massive policy mistakes based on not understanding actual cause and effect last year around most of the world. I will note that an increasing % of tests are Antigen, which seem to have a lower false positive rate than PCR-RT, and the government is making access to tests more difficult.

 If testing remains constant, and cases come down in 2-3 weeks, this will argue that lockdowns are effective.

If cases and outcomes grow into a traditional wave 3, until vaccination rates reach maybe 30%, then the argument that masking and lockdowns will be even weaker. Indeed it will show what I actually believe, that we have far less control over this than we think. I have no hypothesis about how to prove/disprove the traveler/student theory which is popular in the press there now, or if C19 was moving undetected all along.

I want to write something insightful about the corrosive effect of politics on science and humanity’s decency, the apparent innate human need to find someone to blame, the ease which which people can be tricked, the complexity on non-linear systems, and our failure to learn despite apparent massive amounts of data.

But I don’t know what it would be.


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Double Mutant Variation

I’m been working diligently toward the goal of someday fluidly but casually interweaving the phrase “Double Mutant Variation” into a dialog.

“While highly efficient, one of the drawbacks to the taking a dependency on a Double Mutant Variation (DMV) in long range propulsion system is that it can’t be safely replaced in situ.”

“The tension between the suits and the DP over the fundamental tone of the production finally came to a boil when the Double Mutant Variation ending was selected.”

“The strange visuals in the sky toward the East were a result of a rare atmospheric phenomenon that occurs when dioxygen bonds chemically with hydrogen in the Cirrocumulus producing a psychedelic fog-like effect known as a Double Mutant Variation”


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Graph Shows Hydroxychloroquine Is Effective Against Covid19 After All

Blue is new cases. Orange, % of population taking Hydroxchloroquine.

Of course it doesn’t. If anything, it shows the opposite of that the post title claims. It seems that HCQ causes increases in cases, rather dramatically in the 3rd wave, rather than decrease them.

There is a lot of information missing: Is % on HCQ it a dominant variable? What are the sensitive variables? How do we prove this? What does the graph look like when we control for other sensitive variables? Is there a control scenario? How are the graphs different than the control?

That’s not even what it’s a graph of. It’s a complete fake. The fake title was chosen to generate interest among the folks most affected by the topic of the post.

This post isn’t about HCQ. It’s about how we learn. And don’t learn. And become more confident of our knowledge at each step, regardless of it’s correctness.

This is a post about selection bias.

Selection bias is a mental process that causes us to not examine information which conflicts with already held beliefs, Most people think of selection bias as a bad thing, but it’s an essential part of managing mental complexity. If you notice in passing that the sun rose in the South today, you can reasonably save yourself a complete re-examination of the layout of the galaxy and the laws of gravity, and quickly file the knowledge away as likely noise. If the same information is recorded by instruments or seen by many people, it deserves more examination. Selection bias, in this case confirmation bias, saves time and energy and reduces confusion.

I chose HCQ because many people have an opinion as to its effectiveness that is not based on pharmacology or any medical science. And they often convicted not only that are correct, but that science supports their position. Often neither is true.

Selection bias is a cause of major judgement errors, that grow larger and more unmovable over time.

The graph is actually the percentage of people reported in a fb study to be wearing masks, and the number of new PCR-RT positive tests each day in the USA.

All the same caveats and questions apply re: Does this show that masks work? Or not? Why?

But this isn’t a post about masks, HCQ, or Covid19. The amount of effort you put into understanding the graph, and your receptiveness to information is likely sharply constrained around if you do or do not already believe that they do.

Simplifying life is critical to understanding it from multiple perspectives, scales and over time. Confirmation bias is a key tool in this effort. Indeed we can’t understand complex abstract concepts without a layering of highly simplified concepts. Bias is critical to learning at scale.

But it is also used by marketing and policy people to change thought patterns broadly using propaganda. And by politicians to stoke mistrust and dislike of groups as tool to win power.

And it is the mental basis for racism.

One of the interesting things about selection bias is that it is at least as strong or stronger among high cognitive function individuals.


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Final Submission, Style As Message 302, Columbia SoJ

Style Pattern 5: All Commercial Airlines Move Many People to Remote Destinations, and Quickly, and That’s What Matters, Experts Say

While flying can be disorienting and makes some people anxious, flying on commercial airlines is a very safe activity, thanks to ever vigilant government oversight of the entire industry.

Plane crashes are rare, and Deep Vein Thrombosis (DVT) even more so. DVH is potentially serious medical event that occurs when blood clots form in the legs. While a sedentary activity can increase the chances that a person might suffer from DVT, the overwhelming  majority of cases do not occur while flying.

Airline seats are designed by airline seat experts and tested and certified by the Federal Government to reduce the risk of DVT to the lowest level possible. Millions of passengers fly every day on these seats without incident.

While people with a genetic clotting, family predisposition, or history of a clotting disorder might intuitively worry about flying, the odds of a DVT occurring on any trip in the flying population are 0.0000532. General management of these diseases and simple lifestyle changes generally allow such people to live a normal life.

DVT while flying among POC, women and the LGBT community – often ignored if not actively shunned by the medical community is a serious concern and highlights the need to keep making progress on social equity.

Style Pattern 11: A Silent Deadly Killer in Every Airplane Takes Life of Mother of Three.

Finley Violet was the first member of her rural Kentucky family to go to college. The young, fit mother of three was texting her spouse Kai on final approach to their home in Oakland, CA.  She was sharing the good news that her bottom surgery in New York had been completely successful, when she noticed a sharp pain near the calf of her left leg.

It went away as soon as she stood up and didn’t think further about it.

That night, Findley and her wife Kai and their three children, Kendall, Morgan and Jaime, were enjoying their first night together as a family in months.  Kai and Finley shared stories until midnight, and then dozed off to sleep.

The next morning Kai woke to the shock of realizing that Findley wasn’t breathing.

The Medical Examiner explained to Ka and the children that a blood clot, known as a Deep Vein Thrombosis (DVT) in Finley’s left leg, likely a result of sitting too long in an airline flight, had broken off and traveled to her lungs and brain. In the middle of the night partially awoke briefly to symptoms of a heart attack and a stroke at the same time.

DVT can happen suddenly, and without warning, to anyone, and research shows that it happens more frequently on long stretches of sitting on airlines.

Experts recommend standing up once every 2 hours and moving your legs regularly while flying.

DVT while flying among POC, women and the LGBT community – often ignored if not actively shunned by the medical community is a serious concern and highlights the need to keep making progress on social equity.

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What Exactly Is A Cloud?

In the early 90s, Microsoft was riding a wave of growth that would propel them to become one of the most valuable companies of all time. At the core of this growth was the Windows operating system. To understand the core value of Windows and explain its stunning success, consider it to have a top and bottom half. The bottom half – the Device Driver Kit (DDK) allowed, and required, hardware vendors to expose their products to Windows, and Windows applications, in a consistent way. The top half – the Software Development Kit (SDK) and Application Programming APIs, also known as Win32, enabled Windows applications to run on a wide range of hardware without adaptation. Combined with Windows global language support (localization), and single worldwide binary, Windows became the glue that enabled an explosion of applications, around the globe, to run on an explosion of hardware. Both Win32 applications and hardware became cheaper as volumes grew exponentially, and Windows to this day is very inexpensive product relative to the value it provides.

This model, while enabling the industry to grow rapidly by decreasing the cost and increasing the value provided by PCs and applications, was not without conflict. Hardware manufacturers frequently wanted to expose unique functionality, and Microsoft restricted this via a certification process. The argument being that unique functionality would not be understood by all applications, and so would break some of them – fragmenting the platform. Over time, Microsoft asserted that a majority of Windows blue screens were actually caused by bugs in “third party” (other companies) code, requiring even more control over it.

As a concrete example, the touch pad on PCs understands click, pinch and drag. Despite the usability of many more gestures on MacBooks, Windows would not easily be able to add more gestures as the operating system abstracts mouse and touch gestures into a narrow set that applications expect.

There were several implications of these design and business decisions. Installations of Windows are measured in the billions. It’s doubtful the world would have experienced the computing revolution that ultimately touched the lives of nearly everyone on the planet. But it also slowed the rate of innovation. Innovation and backwards compatibility, as Apple has demonstrated many times by breaking it, are at odds. Eventually this, combined with a growing hostility toward the degree of control Microsoft exerted on the industry led to other companies winning on the internet and the phone.

Local Area Networking, or the ability for computers to exchange data over office building distances at high speed started to become popular in the mid-80s. As Microsoft and Novell adopted LANs to Windows, their approach was to virtualize remote systems (servers) into models that already existed in Windows, in order to not break applications. Remote servers appeared to be locally attached disk driver and printers, and for the first time could be used by multiple different computers at the same time (sharing).

At the same time, the Unix approach to networking supported virtualization, but also supported simple application to application to application connections made via the sockets API. Unix adopted the TCP/IP protocol, which worked on local area networks but also on networks that spanned the globe. The ability for an application to connect to another application without the operating system understanding and supporting the application produced a wave of innovation on connected application innovation that continues to this day.

Window 95 was not the first version of Windows to support the sockets API, but it was the first commercially successful one. It is unlikely that the internet as it exists today would have grown as fast as it did without the Winsock API in Windows 95. It is unclear if Microsoft really understood the implications of this decision at the time – although in reality TCP/IP and sockets would likely have eventually been adopted globally, regardless of what Microsoft did. This was the beginning of the series of innovations that would break the grip that Windows had on the application ecosystem.

The most disruptive of the TCP/IP and sockets based applications was the browser and web server, starting to catch on in the mid-90s. The very first browsers were not much more than document directories and viewers, but they laid some important groundwork. Much of what we would come to think of as “the application” in a browser environment was downloaded immediately, from the remote server, upon looking a page. From the customer’s perspective, this was a zero-install application, and from the publishers perspective they could update the code of the application, across the globe, a single action. This value proposition remains to this day, and separates browser applications from mobile, Windows and MacOS applications.

Two other transformative browser features were the first global “application directory”, the Uniform Application Locator (URL). The URL was a readable identifier for a site/application, that had one part ( that was centrally administrated, and another part ( completely under the control of an organization. Unlike existing application directories, this enabled massive growth without collisions, or any central clearing house.

Finally, hyperlinks enabled a new kind of application that referenced parts of other applications, without coordination (or even agreement, as current events in Australia are highlighting). A web of applications. The page/click/link model, which many people assumed to be an overly simple first version, has proven to be useful to this very day.

Microsoft had several responses to the explosion of growth on the internet. The company initially cancelled its competing investment based on the doomed X.25 standard, and invested in a browser called Internet Explorer.  Later, the company would “internet-enable” Windows and Office in way that would be come to be known as software+services.

But at that point Microsoft had grown accustomed to defining what would be successful, and what wouldn’t, simply as a side effect of the volumes of Windows being shipped. It is very difficult to displace a product once it has reached global scale. The company took two swings at making the browser standards effectively Windows standards, in a strategy known at the time as embrace and extend.

The first was ActiveX, introduced in 1996. This was a repurposing of a technology called COM/OLE II, which existed on the Windows desktop, and to some extent in Win32 applications, into Internet Explorer. This allowed browser applications to access functionality in the underlying Windows operating system. There is no doubt that this created customer value, as the subsequent popularity of Shockwave Flash for games and video demonstrated, but had the perhaps not entirely coincidental side effect of making web pages that ran ActiveX incompatible with all other operating systems, and put Microsoft in control of a piece of Internet technology.

ActiveX eventually was discontinued primarily because of real and perceived security flaws in ActiveX itself, and more so in the most popular ActiveX plug-in, Flash.

By the end of the late 90s, Microsoft’s control of the computing platform, not unlike Google’s control of web search, and Apple’s control of applications today, was starting to be understood from a technical / strategy perspective, externally, and actively opposed. In 1998 The DOJ under Clinton filed an antitrust suit against Microsoft, egged on by Sun Microsystems, Netscape and other competitors. The actual premise of the suit, that Microsoft held an unfair advantage because they could include their own browser with Windows, and that that customers wanted choice in operating systems on PCs, was quite weak. Unlike Apple today, which simply decides what application vendors will be allowed to compete, and which will be driven to bankruptcy, it was never difficult to load an application onto a Windows PC. And using Internet distribution, achieving scale and dominance quite possible, as Google’s Chrome has demonstrated. It turns out that customers did want choice in operating system, in the from of iPhone, iPad, Android, MacOS and Linux, but they didn’t not want an alternative to Windows – that would have simply not run Windows apps. The market took care of the problem the DOJ thought they were solving.

The suit did distract Microsoft for many years, and slowed innovation at the company. Likely this was the goal all along, at least in the minds of competitors informing the government.

I’ll only briefly mention Microsoft’s second attempt to control the browser standards, Windows Presentation Framework. Had this succeeded, it would have forced every web application developer to choose standards (sorry, enabled them with choice) that ran across all browsers, or a Microsoft standard that ran only on Windows. It was arguably a better technology than HTML at the time, but failed.

Somewhat ironically, the one important standard that is still running the web today, Jscript, was fully supported by Microsoft browsers from the beginning, ,and Microsoft only recently gave up on their own browser core and adopted Google’s WebKit. “Control” of the browser was a losing strategy from day one.

The first “cloud” companies were web hosters like GoDaddy is today. They ran Microsoft’s Internet Information Server (IIS) on Windows Server, or open source Apache on Linux in large datacenters, and leased “instances” to customers. It is quite difficult to manage 100 servers exposed to the internet in a datacenter, but not incrementally more difficult to manage 1000, or 10,000. Customers, who initially thought of themselves more as publishers and less application developers in the beginning, found hosted solutions to be compelling. This remains true today.

Over time, as web and browser technology became more powerful, more and more applications moved to the web, primarily because of no touch install, global single gesture updates, telemetry, and operating system independence.

In the mid-90s, the important large scale off the shelf business applications were from SAP, Seibel and Oracle. Most of these systems were installed and ran on customers’ hardware, and were complex and expensive to operate and upgrade. In 1999, Salesforce was founded on the idea of delivering enterprise grade applications entirely as a  browser application plus a hosted (by Salesforce itself) “backend” component. The model was referred to at the time as an [internet] service, or Software as a Service (SaaS), and proved to be highly disruptive. It was much easier for customers to try before buy, to deploy, manage instances, and for Salesforce to update and manage the backend. Over time, Salesforce enabled 3rd parties to extend their application even running the datacenter. Applications tend to command more margin ( than raw infrastructure, and applications with a 3rd party ecosystem even more so. Salesforce continues today as cloud provider of enterprise applications, with sales of $14B in 2019.

Amazon launched Amazon Web Services (AWS), specifically Elastic Cloud Compute and Simple Storage in 2006. Unlike (cloud) web hosters, and (cloud) hosted applications, AWS offered customers instances of entire (virtualized) computers to do as they wish. At the end of 2020, AWS reported $13B in profit on $45B in annual revenue. This model eventually became known as Infrastructure as a Service (IaaS).

As all of this was happening, a new model of application, enabled by large numbers of inexpensive servers hosted in the cloud. These applications ran on many computers, often 10s of thousands and now 100s of thousands or more in order to perform jobs like internet search. Google took the lead on search, with profit of $34B on revenue of $160B in 2019. Unlike existing licensing models, Google, and later Facebook’s revenue source was selling advertisements.

Consumer distributed systems evolved through many models including messaging, cloud drives, photo browsing, blogging, file sharing, but Facebook emerged as the winner. Initially Facebook solved the “permissions problem” (how do I control who can see my stuff) with a simple gesture – become my online “friend”. Unlike MySpace they were closed by default (the world can’t see my stuff), and they had an innovative way to continue to draw you back into the site via customized “feeds”.  As the application evolved, Facebook integrated instant messaging, persistent threaded messaging that hung off individual topics, persistent email style messaging, photo and video storage and promotion, and web links into a highly immersive experience. Facebooks profit in 2020 was $29B on revenue of $86B.

Both Google and Facebook pushed the envelope of assumed privacy by actively reading customer data and aggregating it to sell to advertisers. Microsoft was an early developer of consumer distributed systems, with SkyDrive, Messenger, and Hotmail, and at the peak had very impressive adoption numbers. The company was not comfortable changing the privacy model customers had assumed with the personal computer, which likely led to poor revenue in this space, but increased enterprise customer’s trust in the company.

Microsoft launched an AWS competitor, Azure, in 2010. Microsoft does not disclose Azure revenue.

Microsoft and Apple also pursued the model of software+(cloud) services. The iTunes, iCloud, Office 365 and Windows experiences are now backed by often very large cloud services, that provide storage, sharing, email hosting, music fingerprinting, messaging, and many others.

Despite Apple proving to the world that ordinary web browsing was possible on a mobile phone with the iPhone, and despite the fact that a lot of it is done today, mobile applications+services are the dominant application model on phones, as the apps can break out of the page and click model, work offline, and leverage the unique input models of the phone.

Today, nearly all new systems are browser applications against a cloud backend and mobile app based against possibly the same cloud backend. Windows and Office are not new systems, but service-enabling these things has allowed them to provide new value in a cloud world. SAP other enterprise application vendors are working to move their backend systems from customer installed, to hosted by them, and have all provided browser applications even against their existing pre-cloud backends.

So what is the cloud? And who is winning, in the cloud?

Microsoft, Oracle and IBM seem to want to be cloud vendors, in part chasing new growth streams, but also to be and be seen as current and innovative. I’m sure someone knows what IBM and Oracle are doing in the cloud, but I don’t. Microsoft has both an IaaS offering (Azure) and a software+service offering with Office 365. It’s hard to gauge or even define how much of their 2020 profit of $44B on revenue of $143B is “cloud” revenue, as their “intelligent Cloud” segment includes “Server products and cloud services, including Microsoft SQL Server, Windows Server, Visual Studio, System Center, and related CALs, Microsoft Azure, and GitHub”, according to their financial statements.  Sometimes they use the term “Commercial Cloud” in press (but not financial statements), and it seems to include Office 365, the largest value proposition of which is the Win32 Office applications themselves.

Salesforce is a cloud vendor.

Other than Android, all of Google’s systems run in the cloud. And they have an IaaS offering, which they refer to as Google Cloud. They do not generally talk about bulk of their revenue and income which comes from ads, as cloud revenue.

Other than a few mobile apps, all of Facebook’s systems run in the cloud.  They do not generally talk about being a cloud vendor.

Netflix is a large software+services company that does not refer to itself as a cloud vendor.

Cloud doesn’t really mean anything at all.


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Rep. Maxine Waters, Chairwomen Financial Services Committee Vs. Ken Griffin, Smart Rich Person

[ Waters ] Mr. Griffin, Americans feel the system is stacked against them, and Wall Street always wins. The Gamestop, er, thing put a spotlight on this. What say you?

[ Griffin ]  We at Citadel take this seriously. Our innovative business model with Robinhood has enabled, for the first time, free stocks trades to be available to millions of young investors.

[ Waters ] And what is that model?

[ Griffin ]  We are one of the pioneers of a technique that moves information over a special light. This is much faster than the old system, which uses sound. This allows us to provide Robinhood with the information needed to build a very responsive and engaging mobile application, making stock trading not just available to many more people of modest means, but to make the whole experience fun. The high speed of the whole system allows us to true-up prices in realtime, making for more trued-up prices.

[ Waters ] Um, retail investors are mad. Get in their faces, retail investors, in the bars, at the shopping mall, at the gas stations.

[ Griffin ] Excuse me?

[ Waters ] I demand – demand – that you tell this committee of which I am Chairwomen what you did to make these people mad.

[ Griffin ] What happened is this: Some good news on an out of favor stock, Gamestonk, sorry, Gamestop, caused Robinhood  trading volumes to spike – remember, this is free trading app and a fun one too! This caused an overload on the light system, and we had to fall back on the older sound system.  I blame reddit, specifically the subredditors.

[ Waters ] Save the Wall Street jive for your white boy club buddies, Kenny. The people are mad, and I demand you tell me what you did to make them so mad.

[ Griffin ] An overload is rather like when you put too many clothes in your washer, and it gets unbalanced. Eventually an alarm trips and the washer shuts down. Had we done nothing, a single overload would have become what’s called a cascade failure. That’s when you take the clothes from one overloaded washer, and add them the next washer, causing that one to overload. And so on. This would have quickly overwhelmed the entire electrical grid of the USA, had we not taken action with Robinhood, facebook and google to shut down the dangerous overloaded Reddit. Even with out quick action, much of Texas grid eventually failed. It’s all Trump’s fault.

[ Waters ] Thank you Mr. Griffin. BTW, if one was thinking, hypothetically of buying the recently cancelled Learjet 75, would you go Gulfstream or that Brazilian company?

[ Griffin ] G650, without a doubt. Would you like travel in one, as a try before buy? DM me.

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