“Rules Are Rules”—the Deep State and Left Are Responsible for Many Coronavirus Deaths

To be sure, many coronavirus deaths in 2020 are due to comorbidities of the elderly in the 80-plus age range. But the failure to test early and abundantly and to rapidly develop and deploy treatments for the virus, not to mention vaccines, falls on the “rules are rules” mentality and seemingly limitless red tape and foot-dragging of the government’s bureaucracy and politicians.

Then, the inherently risk-averse bureaucrats and politicians imposed oppressive measures shutting down the economy and giving leftists, who for decades have wanted and now have gotten, totalitarian control of our entire society.

Economists are too narrow in their description of socialism as “government ownership of the means of production.” The correct description, as we have all experienced recently, is “government ownership and control of us,” of every person, of every person’s desires and behavior.

And to blame our current president for coronavirus deaths is typical leftist, Orwellian propaganda, which by definition and built into their theory is disingenuous.

After enjoying two takeout meals that were in fact as good as their counterparts in the restaurants, I found myself longing for the opening of speakeasy restaurants—in the rebellious spirit Americans have always exhibited, going back to the era of Prohibition and the American Revolution.

I recall a classmate at my university in the late 1960s who stood up in front of a demonstration at the school’s administration building and pumped his fist, shouting leftist slogans for “power to the people” and “it’s time for revolution.” That event made think we were on the verge of a new Bolshevik Revolution.

Well it is time for revolution today—an intellectual revolution to throw off the chains of government and its deep state that enjoys controlling us.

Power to the people—to each one of us as individuals to make our own decisions about how to handle the present situation.

How would a free market in health care have handled this coronavirus “crisis”? John Goodman of the Goodman Institute has answered the question. With no government bureaucracy telling us what we can and cannot do, initial doctor/patient contact would likely be by telephone or internet to rule out serious symptoms.

“In the face of coronavirus indications,” continues Goodman, “a doctor or nurse would arrive at the home (within an hour), take a swab sample and perform a coronavirus test—with results in, say, 10 minutes.”

Patients with serious symptoms would be greeted at the emergency room (no wait, of course) by a team to escort them “to isolated rooms with appropriate equipment and safeguards to protect other patients and hospital personnel.” Personal protection equipment would be abundantly available, if not immediately, then within a matter of days, as entrepreneurs would work around the clock to meet demand, likely including innovative improvements. Panic buying by consumers or providers, assuming there would even be a panic like we are experiencing today, would be discouraged by increased prices.

And, I might add, anyone who wants to know on a regular basis whether or not they have the virus would have access to an inexpensive at-home test. In a free society, anyone who is afraid of being infected would not be prevented from staying home for an extended period.

Fantasy? Only to those who do not understand classical liberalism and laissez-faire capitalism. The projection gives us a goal to strive for and a standard by which to evaluate the present.

Today, we have a “mixed economy,” or rather, as we should more properly call it, a “mixed society of freedom and dictatorship.” The dictatorship part—the massive central planning and price controls—comes from deep state bureaucrats and politicians who mistakenly (or willingly) defer to the medical czars. And the czars think nothing of imprisoning an entire nation because it is, after all, “for our own good” even though the lockdowns impoverish everyone in the process.

Yet we have evidence from other countries—South Korea, Singapore, Honk Kong, and Taiwan—that the shotgun approach to contagion control is not the best path to take. Test and treat precisely, promptly, and extensively (“rifle style,” to complete the metaphor) is what is effective and saves lives. These four countries, it must be admitted, do have severe surveillance techniques in place to make sure the infected don’t wander far from home. Japan, on the other hand, seems to be doing well with face masks, according to Willis Eschenbach. See this on South Korea.

Who is at fault for our pathetic situation today? The deep state Centers for Disease Control and Food and Drug Administration, our alleged protectors, both of whom committed a not-at-all funny comedy of errors for six weeks delaying the development and approval of tests and treatments (1, 2, 3). And the pace now of testing and approval of treatments, in April 2020, is still deplorably slow.

And then there are the statistical models that have done as much as the less-than-honest press to fan the flames of panic and uncertainty.

Such models, like their climate cousins, are bundles of assumptions used for forecasting, and those assumptions may or may not be correct. Forecasting just means extrapolating from the recent past to predict the near future. We do it all the time, whether it’s company sales, the local weather next week, or what our spouse or children might do tomorrow and the day after that.*

Predictions of the future can be highly inaccurate. In the case of virus models, they have huge margins of error, which means their creators will be heroes wherever the final number falls. With coronavirus, we don’t even know the denominator, which will no doubt be extremely large, thus reducing the fatality rate  (deaths divided by total cases) possibly to the level of seasonal flu, or lower. (See interview with Jay Bhattacharya.)

Does the word “irresponsible” come to mind when medical czars and front page headlines blast “millions of deaths ahead”?

So how do we handle uncertainty? We each weigh the risks and decide for ourselves. Some of us may like to skydive three times a week. Others may prefer to stay home during a contagion. That is a decision that should be left to each one of us.

Cass Sunstein speaking as a believer in mixed-economy policy states that he has “long been a critic of the precautionary principle, which calls for potentially expensive precautions against bad outcomes in the face of scientific uncertainty.” The “potentially expensive precautions” that he is referring to? Our current bureaucratic decisions, made in a seemingly unaware and unacknowledged manner, of destroying lives and businesses, which the left, of course, viciously characterizes as “just dollars and cents.”

Sunstein’s “precautionary principle” goes by another name, argumentum ad ignorantiam, the logical fallacy called appeal to ignorance. “We don’t know what’s going to happen and you can’t prove that disaster won’t occur! It’s better to be safe than sorry.”

So what if some people get hurt in the process? It’s all for the good of “society.”

God forbid the bureaucrats and politicians would allow each one of us as individuals to decide for ourselves how to handle the uncertainty.

Power to the people! It is time to man the barricades of freedom.


* NOAA Scijinks, from the National Oceanic and Atmospheric Administration, a government agency, has substantial data on weather predictions: 90% accuracy for five days, 80% for seven, and 50% for ten or more days. How many millions of deaths are now being predicted by the climate models? And how soon will Florida be under water? Wasn’t that supposed to happen five years ago??


A Note about Comments. Due to spam, "anonymous," and "unknown" comments, I have eliminated the ability to post remarks. If you have a comment, email me, signing your first and last name, and I will post it. Paraphrasing advertising man David Ogilvy, "anonymous" and "unknown" are diseases of social media and the internet.

Statistical Projection vs. Scientific Generalization

When my daughter was quite young, before she was able to walk, she saw a ball bounce and  roll. She laughed heartily. I don’t think she needed to observe a sample of five hundred round, spongy things bounce and roll in order to conclude that round, spongy things bounce and roll.

Similarly, neurologist V. S. Ramachandran, proponent of the value of individual cases to science, has remarked (quoted in Doidge, p. 178):

Imagine I were to present a pig to a skeptical scientist, insisting it could speak English, then waved my hand, and the pig spoke English. Would it really make sense for the skeptic to argue, “But that is just one pig, Ramachandran. Show me another, and I might believe you!”

The skeptical scientist, typical of nearly all scientists today, insists that the only way to establish knowledge is to observe five hundred cases, or a thousand, or two thousand. Anything less is an isolated instance, often denigrated as anecdotal evidence. In the absence of a sound theory of universals—because David Hume failed to find a necessary connection between cause and effect, and logical positivism picked up the banner of science, followed by Karl Popper’s notion of falsificationism—statistical “generalization” is said to be the only valid method of science.

It is this premise that allows modern psychologists to dismiss the entire Freudian psychoanalytic corpus, including the concept of repression, as unscientific, or worse, as pseudoscientific. Why? Because Freud’s evidence is “anecdotal” and the experimental methods of the physical sciences cannot validate his ideas. It is this premise that allows nearly all scientists to dismiss the notions of consciousness, free will, and introspection.

There is, however, a sound theory of universals: Ayn Rand’s theory of concepts, which I have summarized in my two books (In Defense of Advertising, pp. 147-52, and Montessori, Dewey, and Capitalism, pp. 82-86). Conceptualization is a process of universalization. It is based on Aristotle’s formal cause, which says that an entity’s actions are determined by its identity. Identifying universal relationships between entities and their actions give us principles and laws.
Concepts identify the nature of entities. Their essential distinguishing characteristics are universal. It is not that hard.

Thus, my daughter’s laughter at witnessing the round spongy thing bounce and roll was her conceptualization of that entity, by observing its essential distinguishing characteristic. Of course, she did not have words to describe the process at the time, but her mind, nonetheless, was processing her perception. The same can be said about Ramachandran’s English-speaking pig (assuming no tricks of ventriloquism). One does not need a sample of five hundred English-speaking pigs to conclude that something quite unusual has just happened.

Statistical projection—and the correct word is “projection,” not generalization—has its place in our search for knowledge, but it does not replace scientific (inductive) generalization.

Statistical inference, as it is also correctly called, projects a finding from a sample to a population. Thus, if data in a sample of 500 American men show that two percent have red hair, and the research did not commit any flagrant methodological errors, then a projection (or inference) can be made, within a margin of error, that two percent of men in the entire country have red hair.

A projection moves from some to some—from two  percent of the sample to the same two percent in the population.

A scientific generalization, on the other hand, when, for example, forming a concept of round, spongy things as something that bounces and rolls, or of human beings who possess the capacity to reason, moves from all to all.

All of the balls I have observed bounce and roll; all humans that I have observed possess the capacity to reason. Therefore, all balls, past, present, and future, by their very nature,  bounce and roll. The same conclusion is drawn for all humans.

The place of statistical projection? As I wrote in In Defense of Advertising (p. 157), “Statistics is a branch of mathematics and, as such, is a method of measurement. Statistical inference . . . is used only in contexts in which we do not know—or there do not exist—universal laws that could explain the causal relations of the variables.”

Meteorology represents the former, because of the large number of unknowns and difficult-to- measure variables in constructing weather forecasts (all of which, though given many different names, are forms of statistical projection).

Predictions of people’s behavior, because free will precludes the existence of universal laws governing all of our behavior, represents the latter; we make statistical projections, albeit not based on randomized samples, unless we are professional researchers, of what others will do in the future based on our current and past knowledge of them.

Statistical projection assists scientific research. It is not a substitute for it.

And one does not have to accept everything Freud said to acknowledge his accomplishments, not least of which is his presentation of the first comprehensive theory of psychology.

Freud was looking for universals, and he found a few: repression, defense mechanisms, and the significance of the subconscious to influence our present behavior.

They may not be round, spongy things, but I am laughing heartily—at my discovery of these Freudian universals!