For most of my life, I’ve heard people say things like:

  • My ancestors immigrated here because they were skilled laborers and sought after.
  • My ancestors came here the “right” way.
  • My ancestors weren’t “illegal.”

First, it is HIGHLY unlikely that your immigrant ancestors were skilled laborers. If they were, they wouldn’t have been trying to escape their terrible homeland. People don’t just up and leave everything and everyone they know to move to a different county if they have a good life. Would you?

Second, if you’re of European or Asian descent, OF COURSE, your ancestors likely came here the “right” way, because they had to come on a ship.

Third, if you’re using “illegal” to talk about anyone coming across the border to apply for asylum, then, yes, your ancestors were likely “illegal.”

So, I took a Wikipedia page and modified it to discuss the History of Mares (Martians) in America. It’s not too difficult to figure out where this came from originally, but if you read most Wikipedia pages about European immigrants you’ll see the same basic story. Plus, the people the Martians are based on are likely some of your ancestors too.

Enjoy reading about how your ancestors were basically no different than the El Salvadorans, Haitians, Nicaraguans, etc. you think are going to ruin this county and try to turn it into what they left. Really, the ONLY difference is the color of their skin.

Note:  I wrote this on August 29, 2020, but never made it public, because I never finished it.  However, it is now April 2022, and I am still hearing this same crazy argument, so here is the incomplete version. Since February 2020, there have been one million more deaths in the U.S. than would be expected.  Because expected deaths are very consistent from year to year, something has killed an extra one million people.  You can decide for yourself what it might be, but I’m putting my money on COVID-19.

As the death toll from COVID-19 rises, I keep hearing from people that the count is exaggerated because places were essentially counting all deaths as caused by COVID-19. There appears to be some anecdotal evidence for this, but mostly just hospital staff claiming this was happening. I’ve not seen any proof of this, although I’m sure it’s likely happened. I am also certain that the increase in deaths attributed to pneumonia just before the disease was known to be spreading was mostly due to COVID-19. Thus, there has likely been some over- and under-counting.

The thing that really cannot be faked is the total number of deaths this year. The number of people dying in a year is fairly consistent and the CDC tracks this. The number of people dying from common causes is also fairly consistent. The CDC tracks what it calls “excess deaths” that try to better understand if there’s an epidemic or pandemic. They have a great web page that allows you to explore this data (CDC Excess Deaths). The data is updated weekly but, as noted on the web page, the most recent few weeks are likely not accurate as death certificates have not been submitted and/or entered into the database. As of August 20, 2020, the graph of all deaths in the US is shown below.

The yellow/orange line in this chart is what the CDC calls the “excess death threshold.”

This line gives a limit beyond which the number of extra deaths for a week could possibly be due to normal variations. This is based on data from 2013 to the current date. The average (from 2013) is not shown on this chart but is available in the data on the page. If deaths for a week exceed this threshold we can be very certain that something is killing people besides the usual causes. You can see the 2017-2018 flu season was particularly bad for about a month but the 2018-2019 season was not nearly as bad. Note, that it is usually excess pneumonia deaths that contribute to excess deaths during flu season. The 2019-2020 flu season also was quite mild and well within what we would expect to see. 

As an example of the data shown in this chart, let’s look at the week of June 14, 2020, which is the low point of the excess deaths since the pandemic started.  During this week, the threshold for excess deaths was about 54,600 deaths.  The average since 2013 for this week is about 52,700.  The number of deaths recorded was about 58,300, or 3,700 above the epidemic/pandemic threshold and 5,600 above the average.

For the weeks before the pandemic hit, January 5th through March 8th, the country had slightly fewer deaths (2,500) than average, i.e. the flu season was not particularly bad.  However, from March 8th until August 2nd, there have been 214,800 more deaths than normal for that date range and 174,100 more than the epidemic/pandemic threshold.  Thus, it is very clear that something is causing many more people to die than would be expected.  This also makes it clear that the death toll from COVID-19, which at the time was about 160,000, is probably too low.

You might attribute some of the extra 50,000 deaths (between those attributed to COVID-10 and those over the average) to an increase in suicides.  However, the number of suicides in that period would have had to more than double–about 4,000 people kill themselves each month.  Plus, the number of deaths from workplace and vehicle accidents have been reported to be significantly down–about 9,000 people die in accidents each month.  My best guess is that the increase in suicides is probably offset by the decreases in accidental deaths and COVID-19 has at least contributed to the majority of those 50,000 extra deaths.

We can chart the number of deaths each week compared to both the average and the epidemic/pandemic threshold.

The chart clearly shows the large number–over 10,000 in most weeks–of deaths above both the average and the threshold from the end of March until the beginning of May.  The excess deaths then decreased to a minimum around the middle of June and have increased slightly since.  Note that the last couple weeks shown are very likely incorrect due to the time it takes to process death certificates and record cause(s) of death.  What’s interesting to note here is that number of excess deaths each week is roughly in line with, but generally greater than, the weekly totals for deaths attributed to COVID-19.  It’s not clear why this would be and I cannot imagine it could possibly be the result of suicide rates going up by over 50%.  If this were the case, I would hope the CDC would be providing some data for that.  However, the CDC is primarily concerned with diseases and the deaths caused by those diseases.

Thus, if you believe the death toll of COVID-19 is greatly exaggerated, you need to somehow explain how more than 200,000 extra people have died this year.  To understand this in terms of other causes of death, it could be explained by a 200% increase in deaths from other respiratory diseases, a roughly 50% increase in deaths from heart disease or cancer, or a 1000% (10x) increase in the number of suicide deaths.  It is simply extremely hard to explain how 200,000 deaths above normal over a six month period could possibly be explained by an increase in any particular cause.  In that time frame, the TOTAL death rate has increased by over 20%.  It’s hard to imagine a 20% increase in one cause of death, nonetheless in all causes of death.

Once it’s clear that something is causing these extra deaths, people will then often say that it’s “just” old and/or sick people that are dying and that these people were going to die soon anyway.  Looking at the data, the average age of a person dying from COVID-19 is around 73 years old for men and 79 years old for women, which makes it look like it’s just killing off the old people.  Note that there is not data for COVID-19 deaths for each age, just age ranges.  I took the middle of the range to determine the numbers above.  I also calculated deaths from other diseases in this way and doing so shows that the group-age average is generally a couple of years older than the true average.  For example, for heart diseases, the grouped averages are 77 and 83 for men and women, respectively, while the true averages are 74 and 81.  The data also shows that the average number of comorbidities listed when COVID-19 was the primary cause is 2.6.  However, it’s good to try to get some points of reference for these numbers.  Thus, I looked at deaths from all respiratory illnesses, and pneumonia in particular, all cancer deaths, all deaths from heart disease, and all deaths from firearms to determine the average age of death and comorbidities for these causes.

Let’s first look at pneumonia deaths as that disease is very similar to COVID-19.  The average age of a person dying from pneumonia in 2018 was 79 years old–77.1 for men and 80.9 for women.  Thus COVID-19 is killing slightly younger people than pneumonia does.  For pneumonia, the average number of comorbidities listed is 1.8.  It’s not really clear why this is significantly lower than for COVID-19, especially considering the value for all respiratory diseases provided below.

The images in the gallery (click to enlarge) above show how the ages breakdown for pneumonia and COVID-19 deaths for men and women.  The first chart shows the age distribution of pneumonia deaths for men, women, and both in 2018.  The peak for women occurs at 91 years old, for men at 88 years old, and for both combined at 91 years old.  The second chart shows the number of deaths in the age groups the CDC tabulates for COVID-19 for each category.  Note that these are pneumonia deaths for all of 2018 and COVID-19 deaths for about six months.  Clearly the death rate for COVID-19 is much higher than that for pneumonia.  The ages for pneumonia deaths also clearly skew higher, particularly for men.  My first thought when I saw the curve for COVID-19 deaths for men was that the drop was simply the result that the population of men over 84 years old was much less than that from 75 to 84 years old.  However, that drop is not present for pneumonia deaths.  The next chart shows the percentage of deaths in each age group and in each category.  This makes it very clear that COVID-19 is killing people quite a bit younger than pneumonia.  The age difference is especially pronounced in men.  The final chart shows the same data spread out so the percentages for the younger age groups can be seen.  Even in the younger age groups, although the percentages are much smaller overall, it is clear that COVID-19 is killing people, both at a higher total number and higher percentages, younger than pneumonia typically does.

The average age of a person dying from any respiratory disease in 2018 was 77.1 years old–75.9 for men and 78.3 for women.  Again, this is older than for COVID-19 deaths and these ages are a couple of years greater if we find the average from grouped ages.  For all respiratory diseases, the number of comorbidities listed (i.e. in addition to the main cause of death) is 2.5 which is very similar to that of COVID-19.  In general, it appears that respiratory disease deaths typically have more comorbidities listed than for deaths from other diseases.  I suspect this is because deaths from a respiratory disease often involved multiple respiratory issues.  This is why it is so surprising to me that the comorbidities for pneumonia are so low since pneumonia is frequently what kills people with immune diseases.

The images in the gallery (click to enlarge) above show how the ages breakdown for respiratory diseases and COVID-19 deaths for men and women.  The first chart shows the age distribution of respiratory disease deaths for men, women, and both in 2018.  The age range when the majority of people die from respiratory disease is large, between 75 and 90.  The second chart shows the number of deaths in the age groups the CDC tabulates for COVID-19 for each category.  Note that these are half the respiratory disease deaths for all of 2018 and COVID-19 deaths for about six months.  The death rate for COVID-19 so far is fairly close to the death rate of women from all respiratory diseases in 2018.  It appears that COVID-19 is much deadlier for younger men than all other respiratory diseases combined.  The next chart shows the percentage of deaths in each age group and in each category.  This makes it very clear that COVID-19 is killing people quite a bit younger than people dying from all respiratory diseases in 2018; this is especially true for men.  The final chart shows the same data spread out so the percentages for the younger age groups can be seen.  Even in the younger age groups, although the percentages are much smaller overall, it is clear that COVID-19 is killing people, both at a higher total number and higher percentages, younger than other respiratory diseases typically do.  (The labels are incorrect.)

Turning our attention to heart disease we can clearly see that it is much more deadly to men at a younger age than it is to women.  The average age of death from heart disease for men is 74 years old, and for women it is 81 years old.  Note that both of these are older than the average age of a COVID-19 death.  In fact, if you calculate the average for heart disease as I am forced to do for COVID-19, you get 77 years old for men and 83 years old for women.  The average number of comorbidities for heart disease deaths is 2.3.

The images in the gallery (click to enlarge) above show how the ages breakdown for heart diseases and COVID-19 deaths for men and women.  The first chart shows the age distribution of respiratory disease deaths for men, women, and both in 2018.  Again we can see the clear difference in the ages when heart diseases kill men and women.  The second chart shows the deaths grouped by ages so we can better compare with the COVID-19 data.  Note that these are half the heart disease deaths for all of 2018 and COVID-19 deaths for about six months.  For people (men and women) younger than 65 years old all heart diseases and COVID-19 kill at about the same rate.  As a percentage of the total deaths, heart disease clearly kills people that are much older than those dying from COVID-19.  For example, 25% of COVID-19 deaths for men have occurred for men 54 years old and younger.  About half this percentage, 12.5%, of men dying from heart disease are younger than 55 years old.  The data for women is again much different although relatively very similar.  About 12.5% of women dying from COVID-19 are younger than 54 years old.  Again, the percentage of women dying from heart disease who are under 55 years old is about half this.  The bar chart breaks things out for each age group so the percentages for the younger ages are discernible.

Cancer of course kills younger people, and we see that the average age for both men and women dying of cancer is about 71 years old and that is roughly the age at which most deaths occur.  The number of comorbidities is 2.0 and, not surprisingly, less than for respiratory diseases.

A private (or public as Twitter is) is free to respond to someone’s post and to a limited degree delete posts and accounts, but only if they seek protection under the Communications Decency Act. Companies do it all the time. 
While the legal maneuver is to try to undermine the protections given to social platforms, the previous posts were also referencing the tweets Trump made about Twitter limiting free speech. 
While AG Barr has said the DOJ had been looking into that particular section 230(c) of the Communications Decency Act, and there are some good arguments that it should be altered, I believe the timing of this is simply a result of Trump’s vindictiveness.
The executive order is really not that complex and could have easily been written in a couple of days and even a matter of hours by someone versed in the particular law under scrutiny. It also clearly shows the vindictive nature that he’s expressed in tweets following Twitter replying to his tweet. See https://www.whitehouse.gov/presidential-actions/executive-order-preventing-online-censorship/, which I have embedded for reference below.  What I find truly amazing is the introduction to the executive order which clearly shows its vindictive origins.  They actually use “whataboutisms” in it referencing Adam Schiff and the “Russian Hoax”.  I’m not exactly sure what Schiff tweeted but I doubt it had anything to do with Trump colluding with Russia.  I suspect it was about Russia’s attempted interference in the 2016 election.  If so, then that has clearly been proven if you read any of the warrants issued for Russians.  They really didn’t even try to hide it and left a very clear digital trail back to them.  Just read the indictment for yourself; it’s quite interesting once you get into the details.
Of course, the executive order will need to withstand legal scrutiny of the courts, but I think that is part of the ploy–make social media platforms “waste” money in drawn-out legal battles in which it seems lawyers are typically the only winners.
There is a lot to debate about section 230(c) of the Communications Decency Act but I believe it actually allows free speech more than it hampers it. Without it, say, Lori Klausutis’ husband could sue Twitter about the posts the president made concerning her death. That just does not seem right to me. Plus, if Lori Klausutis’ husband sued Twitter, would Twitter not then sue Trump?  Who wins then besides lawyers?
It would be like a store being sued because someone besides the owners posted inflammatory material on a bulletin board they’d set up for public announcements. If you want to go even more extreme, I don’t think it’d be right to allow a business to be sued because someone spray-painted inflammatory things on their building. Are all blogs that allow comments now going to have to worry about being sued for something a commenter might say?  If so, I think a lot of places that once offered platforms for discussion will simply shut down, or ban that discussion.
Social platforms need to maintain a balance between allowing people to express their opinions and the need to prevent misinformation, and harmful and/or indecent material from spreading, and maybe they go too far sometimes; the law is not clear on the line of what is okay and what is not.  However, what Trump is doing is essentially trying to kill or hamper the platform that gives him so much of his voice.  It is honestly quite strange and a very perplexing move.

By the authority vested in me as President by the Constitution and the laws of the United States of America, it is hereby ordered as follows:

Section 1.  Policy.  Free speech is the bedrock of American democracy.  Our Founding Fathers protected this sacred right with the First Amendment to the Constitution.  The freedom to express and debate ideas is the foundation for all of our rights as a free people.

In a country that has long cherished the freedom of expression, we cannot allow a limited number of online platforms to hand pick the speech that Americans may access and convey on the internet.  This practice is fundamentally un-American and anti-democratic.  When large, powerful social media companies censor opinions with which they disagree, they exercise a dangerous power.  They cease functioning as passive bulletin boards, and ought to be viewed and treated as content creators.

The growth of online platforms in recent years raises important questions about applying the ideals of the First Amendment to modern communications technology.  Today, many Americans follow the news, stay in touch with friends and family, and share their views on current events through social media and other online platforms.  As a result, these platforms function in many ways as a 21st century equivalent of the public square.

Twitter, Facebook, Instagram, and YouTube wield immense, if not unprecedented, power to shape the interpretation of public events; to censor, delete, or disappear information; and to control what people see or do not see.

As President, I have made clear my commitment to free and open debate on the internet. Such debate is just as important online as it is in our universities, our town halls, and our homes.  It is essential to sustaining our democracy.

Online platforms are engaging in selective censorship that is harming our national discourse.  Tens of thousands of Americans have reported, among other troubling behaviors, online platforms “flagging” content as inappropriate, even though it does not violate any stated terms of service; making unannounced and unexplained changes to company policies that have the effect of disfavoring certain viewpoints; and deleting content and entire accounts with no warning, no rationale, and no recourse.

Twitter now selectively decides to place a warning label on certain tweets in a manner that clearly reflects political bias.  As has been reported, Twitter seems never to have placed such a label on another politician’s tweet.  As recently as last week, Representative Adam Schiff was continuing to mislead his followers by peddling the long-disproved Russian Collusion Hoax, and Twitter did not flag those tweets.  Unsurprisingly, its officer in charge of so-called ‘Site Integrity’ has flaunted his political bias in his own tweets.

At the same time online platforms are invoking inconsistent, irrational, and groundless justifications to censor or otherwise restrict Americans’ speech here at home, several online platforms are profiting from and promoting the aggression and disinformation spread by foreign governments like China.  One United States company, for example, created a search engine for the Chinese Communist Party that would have blacklisted searches for “human rights,” hid data unfavorable to the Chinese Communist Party, and tracked users determined appropriate for surveillance.  It also established research partnerships in China that provide direct benefits to the Chinese military.  Other companies have accepted advertisements paid for by the Chinese government that spread false information about China’s mass imprisonment of religious minorities, thereby enabling these abuses of human rights.  They have also amplified China’s propaganda abroad, including by allowing Chinese government officials to use their platforms to spread misinformation regarding the origins of the COVID-19 pandemic, and to undermine pro-democracy protests in Hong Kong.

As a Nation, we must foster and protect diverse viewpoints in today’s digital communications environment where all Americans can and should have a voice.  We must seek transparency and accountability from online platforms, and encourage standards and tools to protect and preserve the integrity and openness of American discourse and freedom of expression.

Sec2.  Protections Against Online Censorship.  (a)  It is the policy of the United States to foster clear ground rules promoting free and open debate on the internet.  Prominent among the ground rules governing that debate is the immunity from liability created by section 230(c) of the Communications Decency Act (section 230(c)).  47 U.S.C. 230(c).  It is the policy of the United States that the scope of that immunity should be clarified: the immunity should not extend beyond its text and purpose to provide protection for those who purport to provide users a forum for free and open speech, but in reality use their power over a vital means of communication to engage in deceptive or pretextual actions stifling free and open debate by censoring certain viewpoints.

Section 230(c) was designed to address early court decisions holding that, if an online platform restricted access to some content posted by others, it would thereby become a “publisher” of all the content posted on its site for purposes of torts such as defamation.  As the title of section 230(c) makes clear, the provision provides limited liability “protection” to a provider of an interactive computer service (such as an online platform) that engages in “‘Good Samaritan’ blocking” of harmful content.  In particular, the Congress sought to provide protections for online platforms that attempted to protect minors from harmful content and intended to ensure that such providers would not be discouraged from taking down harmful material.  The provision was also intended to further the express vision of the Congress that the internet is a “forum for a true diversity of political discourse.”  47 U.S.C. 230(a)(3).  The limited protections provided by the statute should be construed with these purposes in mind.

In particular, subparagraph (c)(2) expressly addresses protections from “civil liability” and specifies that an interactive computer service provider may not be made liable “on account of” its decision in “good faith” to restrict access to content that it considers to be “obscene, lewd, lascivious, filthy, excessively violent, harassing or otherwise objectionable.”  It is the policy of the United States to ensure that, to the maximum extent permissible under the law, this provision is not distorted to provide liability protection for online platforms that — far from acting in “good faith” to remove objectionable content — instead engage in deceptive or pretextual actions (often contrary to their stated terms of service) to stifle viewpoints with which they disagree.  Section 230 was not intended to allow a handful of companies to grow into titans controlling vital avenues for our national discourse under the guise of promoting open forums for debate, and then to provide those behemoths blanket immunity when they use their power to censor content and silence viewpoints that they dislike.  When an interactive computer service provider removes or restricts access to content and its actions do not meet the criteria of subparagraph (c)(2)(A), it is engaged in editorial conduct.  It is the policy of the United States that such a provider should properly lose the limited liability shield of subparagraph (c)(2)(A) and be exposed to liability like any traditional editor and publisher that is not an online provider.

(b)  To advance the policy described in subsection (a) of this section, all executive departments and agencies should ensure that their application of section 230(c) properly reflects the narrow purpose of the section and take all appropriate actions in this regard.  In addition, within 60 days of the date of this order, the Secretary of Commerce (Secretary), in consultation with the Attorney General, and acting through the National Telecommunications and Information Administration (NTIA), shall file a petition for rulemaking with the Federal Communications Commission (FCC) requesting that the FCC expeditiously propose regulations to clarify:

(i) the interaction between subparagraphs (c)(1) and (c)(2) of section 230, in particular to clarify and determine the circumstances under which a provider of an interactive computer service that restricts access to content in a manner not specifically protected by subparagraph (c)(2)(A) may also not be able to claim protection under subparagraph (c)(1), which merely states that a provider shall not be treated as a publisher or speaker for making third-party content available and does not address the provider’s responsibility for its own editorial decisions;

(ii)  the conditions under which an action restricting access to or availability of material is not “taken in good faith” within the meaning of subparagraph (c)(2)(A) of section 230, particularly whether actions can be “taken in good faith” if they are:

(A)  deceptive, pretextual, or inconsistent with a provider’s terms of service; or

(B)  taken after failing to provide adequate notice, reasoned explanation, or a meaningful opportunity to be heard; and

(iii)  any other proposed regulations that the NTIA concludes may be appropriate to advance the policy described in subsection (a) of this section.

Sec3.  Protecting Federal Taxpayer Dollars from Financing Online Platforms That Restrict Free Speech.  (a)  The head of each executive department and agency (agency) shall review its agency’s Federal spending on advertising and marketing paid to online platforms.  Such review shall include the amount of money spent, the online platforms that receive Federal dollars, and the statutory authorities available to restrict their receipt of advertising dollars.

(b)  Within 30 days of the date of this order, the head of each agency shall report its findings to the Director of the Office of Management and Budget.

(c)  The Department of Justice shall review the viewpoint-based speech restrictions imposed by each online platform identified in the report described in subsection (b) of this section and assess whether any online platforms are problematic vehicles for government speech due to viewpoint discrimination, deception to consumers, or other bad practices.

Sec4.  Federal Review of Unfair or Deceptive Acts or Practices.  (a)  It is the policy of the United States that large online platforms, such as Twitter and Facebook, as the critical means of promoting the free flow of speech and ideas today, should not restrict protected speech.  The Supreme Court has noted that social media sites, as the modern public square, “can provide perhaps the most powerful mechanisms available to a private citizen to make his or her voice heard.”  Packingham v. North Carolina, 137 S. Ct. 1730, 1737 (2017).  Communication through these channels has become important for meaningful participation in American democracy, including to petition elected leaders.  These sites are providing an important forum to the public for others to engage in free expression and debate.  CfPruneYard Shopping Center v. Robins, 447 U.S. 74, 85-89 (1980).

(b)  In May of 2019, the White House launched a Tech Bias Reporting tool to allow Americans to report incidents of online censorship.  In just weeks, the White House received over 16,000 complaints of online platforms censoring or otherwise taking action against users based on their political viewpoints.  The White House will submit such complaints received to the Department of Justice and the Federal Trade Commission (FTC).

(c)  The FTC shall consider taking action, as appropriate and consistent with applicable law, to prohibit unfair or deceptive acts or practices in or affecting commerce, pursuant to section 45 of title 15, United States Code.  Such unfair or deceptive acts or practice may include practices by entities covered by section 230 that restrict speech in ways that do not align with those entities’ public representations about those practices.

(d)  For large online platforms that are vast arenas for public debate, including the social media platform Twitter, the FTC shall also, consistent with its legal authority, consider whether complaints allege violations of law that implicate the policies set forth in section 4(a) of this order.  The FTC shall consider developing a report describing such complaints and making the report publicly available, consistent with applicable law.

Sec5.  State Review of Unfair or Deceptive Acts or Practices and Anti-Discrimination Laws.  (a)  The Attorney General shall establish a working group regarding the potential enforcement of State statutes that prohibit online platforms from engaging in unfair or deceptive acts or practices.  The working group shall also develop model legislation for consideration by legislatures in States where existing statutes do not protect Americans from such unfair and deceptive acts and practices. The working group shall invite State Attorneys General for discussion and consultation, as appropriate and consistent with applicable law.

(b) Complaints described in section 4(b) of this order will be shared with the working group, consistent with applicable law. The working group shall also collect publicly available information regarding the following:

(i) increased scrutiny of users based on the other users they choose to follow, or their interactions with other users;

(ii) algorithms to suppress content or users based on indications of political alignment or viewpoint;

(iii) differential policies allowing for otherwise impermissible behavior, when committed by accounts associated with the Chinese Communist Party or other anti-democratic associations or governments;

(iv) reliance on third-party entities, including contractors, media organizations, and individuals, with indicia of bias to review content; and

(v) acts that limit the ability of users with particular viewpoints to earn money on the platform compared with other users similarly situated.

Sec6.  Legislation.  The Attorney General shall develop a proposal for Federal legislation that would be useful to promote the policy objectives of this order.

Sec7.  Definition.  For purposes of this order, the term “online platform” means any website or application that allows users to create and share content or engage in social networking, or any general search engine.

Sec8.  General Provisions. (a)  Nothing in this order shall be construed to impair or otherwise affect:

(i)    the authority granted by law to an executive department or agency, or the head thereof; or

(ii)   the functions of the Director of the Office of Management and Budget relating to budgetary, administrative, or legislative proposals.

(b)  This order shall be implemented consistent with applicable law and subject to the availability of appropriations.

(c)  This order is not intended to, and does not, create any right or benefit, substantive or procedural, enforceable at law or in equity by any party against the United States, its departments, agencies, or entities, its officers, employees, or agents, or any other person.

A collection of great articles about capitalism, cronyism, and counterfeit-capitalism… They’re all quite interesting.  From September 2019:


I really wonder how the gig economy is going to shake out after things open back up. Will people continue to get stuff delivered and/or pick things up curbside more? All these were options BC-19 (before COVID-19) but I’m sure more people have tried them now. What’s the consensus?



A private (or public as Twitter is) is free to respond to someone’s post, and to a limited degree delete posts and accounts. They do it all the time. See my follow-up post about the actual order. Of course, that’s the legal maneuver.

I’m talking here about his follow-up tweets about the situation and his general sense that what Twitter did somehow violated his right to free speech.

While Barr has said the DOJ had been looking into that particular section of the law, and there are some good arguments that it should be altered, I do believe the timing of this is simply a result of Trump’s vindictiveness.

The document is really not that complex and could have easily been written in a couple of days and even a matter of hours by someone versed in the particular law under scrutiny. It also clearly shows the vindictive nature that he’s expressed in tweets following Twitter replying to his tweet. See: https://www.whitehouse.gov/presidential-actions/executive-order-preventing-online-censorship/

Of course, this will need to withstand legal scrutiny of the courts, but I think that is part of the ploy–make social media platforms “waste” money in drawn-out legal battles in which it seems lawyers are typically the only winners.

There is a lot to debate about section 230(c) of the Communications Decency Act but I believe it actually allows free speech more than it hampers it. Without it, say, Lori Klausutis’ husband could sue Twitter about the posts the president made concerning her death. That just does not seem right to me. It would be like a store being sued because someone besides the owners posting inflammatory material on a bulletin board they’d set up for public announcements. If you want to go even more extreme, I don’t think it’d be right to allow a business to be sued because of someone spray-painting inflammatory things on their building.

Social platforms need to maintain a balance between allowing people to express their opinions and the need to prevent misinformation from spreading, and maybe they go too far sometimes.

I believe Trump’s original travel ban from Arab counties did not pass the legal challenges, but the revised version did by a party-line vote in SCOTUS. But the debate over the courts becoming too political is for another time.

I guess he went through with it. If it has any effect it will only stifle the ability to express oneself. You allow Twitter to be sued over what users post and you think they wouldn’t immediately take down many of Trump’s tweets, especially the ones about Scarborough. Honestly, I think Twitter should in response simply delete his account saying it’s too much of a liability for them now.


I seriously wonder how courts will rule on this… if they rule for Trump our society will be permanently altered, for the worse I believe. Trump is trying to limit Twitter’s freedom of speech. Can he possibly not see that? Are the “advisers” he has surrounded himself with too afraid to point out the obvious inconsistency? Does he think his followers will not see this obvious inconsistency?
No newspaper is under any obligation to publish every letter they receive, and Twitter is under no obligation to publish every tweet they receive. Likewise, a newspaper is free to publish a letter and then respond to it. Twitter is free to do the same.
Please, SOMEONE, rent a room in a Trump hotel and hang a banner critical of Trump from the window and see what happens.


It appears that our president’s vindictiveness towards anyone that he perceives as disagreeing with or slighting him goes even deeper than I previously thought.  He also clearly does not understand that companies, public or private, are under no obligation to protect free speech.  Do you think Trump would not have banners hung from the windows of his hotels saying “Trump Sucks” removed?  Companies are also under no obligation to not have an opinion.  Twitter did not remove his tweets; they only officially responded to them with counterpoints.  Is it not THEIR right to do so?  We have a narcissistic, vindictive bully as a president that is willing to use all the power we’ve given him and power we did not give him to protect his ego, belittle and oppress his opponents, and take revenge on anyone that disagrees with him.

We cannot allow this man to continue dismantling the government we have so he can take revenge on his enemies.  He and the Republican party are establishing some dangerous precedents that can and likely will be used by both parties in the future.  To those that applaud him for taking these actions, please remember that future presidents will also take advantage of these precedents and implement policies through executive orders and/or with no oversight that you may very much not like.

I have updated the plots with the data up to May 24, 2020, and highlighted Wisconsin since people seem to be interested in what’s happening there.

While I haven’t lived in Michigan in 27 years, I still have many friends and family members that live there, and I go there fairly regularly.  It seems many people are upset with how their governor has handled the shutdown and enforced social distancing, although it appears from polls that the majority of people support her policies.

Besides simply being upset that small business owners are being hurt by this, it seems that many people are upset that they were/are not allowed to go to vacation properties that are usually located in rural areas of northern Michigan.  I suspect the thought here was that this was part of an overall limiting of travel.  I can understand this from a health perspective as it would keep the spread in areas where there are far more healthcare resources.  I can also understand that at a time when people are social distancing, they would like to be able to get away for a bit, and in many ways increase social distancing.

I have also heard many complaints about not being able to go out in boats, and I have to say I really do not understand the reasoning for this.  Maybe it’s to limit the number of people that need to monitor boating and/or needing to respond to emergencies.  While boating isn’t a huge thing in Pennsylvania, I don’t think there are any limitations here, and I’ve not heard of this in other states; but I may be wrong.

Finally, it seems people are particularly concerned with barbershops and salons.  I’m not sure what the particular concern is with these places other than that many are indeed small businesses.  However, there are all kinds of other small businesses that are also being hurt.  I can understand the government’s stance to keep them closed to enforce social distancing which is hard to do when you’re getting your hair cut.  If we’d have built up our testing capabilities faster, then maybe barbers and beauticians could be regularly tested and given some certificate to ensure customers of this.  It also seems like barbers and beauticians have made very public statements about their feelings.  However, it seems to me that there are just as many small gym owners and personal trainers as there are barbers and beauticians.  I don’t hear about them complaining, although I’m sure they are, at least privately.

So, let’s take a look at the data (with all the caveats attached) for Michigan.  First, let’s look at the ratio of day-to-day changes in the number of infected; this is often called R.  The plot below shows this for all states with four highlighted for comparison.  The points above 1.45 at the start that aren’t highlighted are from Missouri.  It’s clear that things started off in Michigan with the virus spreading very fast, and there’s plenty of speculation on why that was.

If we look at the new infections each day averaged over a week, we see that, as suggested by the plot above, the infections spread in Michigan very fast.  Sometime in the first half of April things changed dramatically, as they did in Louisiana.  New infections have now steadied for both states.  Note that Michigan’s population is about twice that of Louisiana’s and slightly more than New Jersey’s.  Although the infection rate seems to be increasing slightly in the last couple weeks, I suspect the attitude is from a healthcare perspective, “Whatever we’re doing is working, so let’s keep doing it.”  From an economic perspective it’s really hard to say, but it’s certainly realistic to think that there could be another explosion in the number of cases.  If there is one I suspect it’d be less severe than the first time because people are simply more away and taking precautions.  Illinois now has the most new infections of any state, and California is catching up to New York.

Linear scale
Logarithmic scale

Now let’s take a look at deaths each day, again average over a seven day period.  I think this is the one that got the Michigan government/governor very concerned.  While the number of daily new infections mirrored that of Louisiana closely, the number of deaths each day was more than double for many days.  It’s hard to determine why this was besides maybe an older and less healthy population.  Louisiana’s infections were concentrated around New Orleans like Michigan’s were concentrated around Detroit.  I doubt the medical care in the Detroit area is any better or worse than in the New Orleans area.  Likewise I would think that per capita the capacity would likely be the same.

Linear scale
Logarithmic scale

I have no idea if the actions Michigan’s governor took and is taking are the best strategy overall.  It certainly seems to be from a healthcare perspective.  The big questions that will never be answered are:  How many people would have died or gotten severely ill without the actions taken?  And, how much better would the economy be without those actions?  My personal feeling is that a couple thousand more people would have died and the economy would probably not be a whole lot better.  New data from Politico says that “…that Georgia now leads the country in terms of the proportion of its workforce applying for unemployment assistance. A staggering 40.3 percent of the state’s workers — two out of every five — has filed for unemployment insurance payments since the coronavirus pandemic led to widespread shutdowns in mid-March, a POLITICO review of Labor Department data shows.”

I’m not really sure of a good way to look at the life versus economy tradeoff.  Maybe the best way is to think that we (you) saved 2,000 lives but lost 2,000 small businesses.  That’s still a hard one to judge, but I would think many small business owners would trade their business for the life of a loved one.

There has been quite a bit of debate about the “dire” predictions that COVID-19 models have made and are making for infections and, especially, deaths, and how those predictions are being used to scare people.  I can say with a great deal of certainty that scientists making these models and doing the simulations are not intentionally trying to scare anyone.  (The only “scientists” I am skeptical of are the ones trying to sell books or market themselves for something.  The “Plandemic” woman is in this category.  She’s been peddling false hope to people with chronic illnesses for a long time.)  On the other hand, in the hands of the media and politicians the predictions can be used in many different ways.  I think many of the early models used a few different scenarios:  we do nothing, we socially distance and/or shutdown, we discover a vaccine, etc.  If you want to scare people, the predictions from the models in which we do nothing can certainly be used, and I believe that if we had done nothing we would be in a very serious situation.

I’ve spent most of the last 30 years developing and analyzing models, mostly trying to predict how physical systems will respond.  Physical system models are not hard to develop if you understand the physical laws that govern them (and the mathematics needed to study them).  There have been very few advances in modeling physical systems at scales visible to humans in nearly a century.  That is why physicists rightly say that most of what engineers do is classical physics.  One nice thing about physical systems is they are not alive to change their behaviors to something not included in the model.  (Note, “smart” materials on which I did a lot of research are not actually smart. [1])  Another nice thing is you can do controlled experiments to validate your model.  Finally, you have a lifetime of experience and intuition to use to see if the results make physical sense.  However, I think the best results are the ones that do not initially make intuitive sense and require you to adjust your intuition.  See footnote [2] for a great example of this and footnote [3] for my experience trying to get engineering students to use their intuition and common sense.

The basic model for disease spread is what’s called the SIR (susceptible/infected/recovered) model; there are many variations and extensions of this.  There are also many good explanations of this model online so I won’t go into details about it here.  I would recommend watching the YouTube video I’ve embedded at the end.  One thing to know about these models is that they are statistical and have many parameters that people can “tweak” and many “features” that can be added.  Being statistical, they will only give you an “average” sense of what might happen.  Likewise, you can adjust the parameters to get almost any prediction.  This is where so-called fitting comes in.  Scientists will tweak the parameters until they fit known cases and hope those parameters will predict what will happen in the future.  When scientists share these models they usually provide the parameters they’ve used and what “ingredients” have been included.  Although some people want to keep their models proprietary, and I would be skeptical of them.  The problem here is that by the time the predictions hit the media and politicians all those details have been stripped away to make it more digestible for the general public.

Statistical models have been used in physics for over a century, and from basically the time we realized matter was made of atoms but we could still measure properties of matter without having to keep track of every atom.  For example, the temperature of something basically measures on average the energy contained in the atoms/molecules comprising the material.  We don’t need to track every atom to get this average.  Likewise, the pressure from the air you feel is the forces of all the molecules in the air hitting you.  If the wind hits you from one side you notice a net force acting to push you in the direction the wind is blowing.  This is simply because more molecules are hitting you on one side than the other creating a net force that wants to move you.  Again, we do not need to keep track of every molecule/atom to determine what this force is.

Statistical models in physics (a subject called statistical mechanics) work extremely well and are used extensively.  Like SIR models statistical mechanics models can be more or less complicated by adding or removing ingredients.  For example, the “ideal gas law” that relates pressure, temperature, and volume was known long before we understood anything about atoms, and we now know that it can be completely derived by averaging the motion of atoms and molecules modeled as balls bouncing around.  However, there are cases when the ideal gas law doesn’t work well.  For example if the gas is made from molecules you can include the rotation of the molecule as an ingredient.  It turns out that under “normal” conditions this ingredient isn’t needed, but under extreme conditions it helps explain why the ideal gas law fails.  The other time statistical models don’t work well is when you don’t have enough particles (i.e. atoms or molecules) to average over.  If you only have, say, one thousand atoms bouncing around in a box, statistical averaging starts to not work so well.  Fortunately, with modern computing power, we can model billions of atoms moving around using molecular dynamic simulations.

One reason statistical models and molecular dynamic simulation work so well is that atoms do not have free will, i.e. under the same situation they will all act the same.  People on the other hand are very different.  It’s this behavior and the feedback causing that behavior that makes modeling populations so hard.  If you have millions of people you can try to estimate how the average person will behave and include that in a statistical model.  Most of the variations of the SIR are doing just that, but modeling behavior even on average is very difficult.  While we could theoretically model every person in the United States acting in an average way, we know this would provide the same results as the statistical model.  We could include some randomness in the every-person model, but again with enough people you’re still going to get the average result.  What an every-person model may help predict is how a very non-uniform population density plays a role.  However, SIR models can be adjusted for this too.

To help explain the SIR model, the creator of the two videos below basically does molecular dynamics simulations with people replacing the atoms and behaving in different random ways.  Note the Twitter screenshot he includes around the 2:14 mark with someone responding to him, “Im not a gas in a box :'(”  Because he is only using around one thousand people walking basically randomly he makes many runs and averages the results.  To try to model the variation in people’s behavior he uses various percentages and looks at how these percentages change the results.  For example, he varies the percentage of people infected that get quarantined or the percentage of people traveling from one community to another.

When you’re modeling things with algorithms instead of equations you can play around with all kinds of probable behaviors and actions.  Things can get extremely complicated and often you have no idea what the result might be.  There is actually a scientific/mathematical buzzword for this called “emergent behavior.”  According to Wikipedia, “emergence occurs when an entity is observed to have properties its parts do not have on their own.”  You can think of your body as the emergence of all the individual cells doing their own thing.  Scientists and mathematicians are enamored with emergent behavior because you often see very interesting and realistic behaviors emerge from very simple models of how the parts interact.

While I am certainly biased, I believe the scientific community is doing a great job simply trying to keep people informed.  Unfortunately, their messages can get distorted and used politically.  Plus, scientists usually avoid words like “never” and “always” so when someone asks them if it’s possible 10 million people will die, they’ll simply answer, “Yes.  It’s possible.”



[1]  Playing with a dielectric elastomer “smart” material water balloon in the lab of my former student Nakhiah Goulbourne at the University of Michigan during the summer of 2010.  What makes this material “smart” is a crazy-stupid 5,000V being applied across the membrane, although there is very little current so not much power.


Wrinkled mylar balloon.

[2] A great example of needing to adjust your intuition based on strange results from a model is a model/simulation I worked on with Elaine Serina when we were graduate students.  Elaine wanted to understand how forces on your fingertip get transferred to tension in the skin and stresses on the bone as part of a larger study on carpal tunnel syndrome.  As a simple first step, we decided to model the fingertip as an ellipsoid (think of a plain M&M) inflated by water and then compressed between two plates.  We wanted the initial inflation because there is usually tension in your skin (unless you’ve been soaking in water and are all “pruney”).  However, when Elaine took the equations I derived and wrote code to solve them she kept getting strange results that we were both convinced couldn’t be correct.  The simulations were showing that when you inflated the skin membrane you would get compressive stresses.  Our intuition said, “You can’t inflate something and get compression.”  We spent at least a month trying to figure out what was wrong with the model and/or the code to no avail.  After a meeting with our thesis adviser in which he concurred with our intuition that something must be wrong, we were walking back to our lab through the student union and noticed the inflated mylar balloons.  One of us (likely me because I was the one studying wrinkling caused by membrane compression) realized that all the mylar balloons were wrinkled around the edges, just where our model was predicting compressive stresses.  The only way you get wrinkles is when you have compressive stresses.  Thus, we realized our intuition was wrong!  As you inflate a mylar balloon the edges want to pull in towards the center.  This creates the compression.  If you have a rubber balloon of this shape, adding more pressure will eventually cause the wrinkles to disappear.  However, because mylar is so stiff you can’t pressurize it enough to remove the wrinkles without it rupturing.

[3] I was always a bit disheartened with how many mechanical engineering students did not seem to have this intuition when they got to the junior-level class I regularly taught.  To address this, part of every homework problem was a statement about why they felt their answer was correct or incorrect.  Early in the semester I would get answers like, “Because I followed all the steps and checked the math.”  I was constantly shocked at how many mechanical engineering students did not come into the class with the skill of looking at the result they got and evaluating if it made physical sense.  Every semester I talked a lot about “sanity checks.”  Plus, I wanted to know if they suspected their answer was not correct, as it’s much better in the real world to know a result is likely not correct than to think it is.