Christians Shouldn’t Be Dismissive of Scientific Modeling
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Projections from an IHME model.
Over the last several weeks I’ve encountered a range of negative views toward the models epidemiologists have been using in the struggle against COVID-19. Skepticism is a healthy thing. But rejecting models entirely isn’t skepticism. Latching onto fringe theories isn’t skepticism. Rejecting the flattening-the-curve strategy because it’s allegedly model-based isn’t skepticism either.
These responses are mostly misunderstandings of what models are and of how flattening-the-curve came to be.
I’m not claiming expertise in scientific modeling. Most of this is high school level science class stuff. But for a lot of us, high school science was a long time ago, or wasn’t very good—or we weren’t paying attention.
What do models really do?
Those tasked with explaining science to us non-scientists define and classify scientific models in a variety of ways.
The Stanford Encyclopedia of Philosophy, for example, describes at least 8 varieties of models, along with a good bit of historical and philosophical background. They’ve got about 18,000 words on it.
A much simpler summary comes from the Science Learning Hub, a Science-education project in New Zealand. Helpfully, SLH doesn’t assume readers have a lot of background.
In science, a model is a representation of an idea, an object or even a process or a system that is used to describe and explain phenomena that cannot be experienced directly. Models are central to what scientists do, both in their research as well as when communicating their explanations. (Scientific Modeling)
Noteworthy here: models are primarily descriptive, not predictive. Prediction based on a model is estimating how an observed pattern probably extends into what has not been observed, whether past, present, or future.
Encyclopedia Britannica classifies models as physical, conceptual, or mathematical. It’s the mathematical models that tend to stir up the most distrust and controversy, partly because the math is way beyond most of us. We don’t know what a “parametrized Gaussian error function” is (health service utilization forecasting team, p.4; see also Gaussian, Error and Complementary Error function).
But Christians should be the last people to categorically dismiss models. Any high school science teacher trained in a Christian university can tell you why. I’ve been reminded why most recently in books by Nancy Pearcy, Alvin Plantinga, William Lane Craig, and Samuel Gregg: Whether scientists acknowledge it or not, the work of science is only possible at all because God created an orderly world in which phenomena occur according to patterns in predictable ways. For Christians, scientific study—including the use of models to better understand the created order—is study of the glory of God through what He has made (Psalm 19:1).
Most of us aren’t scientists, but that’s no excuse for scoffing at one of the best tools we have for grasping the orderliness of creation.
Should we wreck our economy based on models?
The “models vs. the economy” take on our current situation doesn’t fit reality very well. Truth? The economy is also managed using models. A few examples:
- Calculating the unemployment rate
- Unemployment forecasting (also this)
- Business forecasting
- Cost Modeling
Beyond economics, modeling is used all the time for everything from air traffic predictions to vehicle fire research, to predictive policing (no, it isn’t like “Minority Report”).
Models are used extensively in all sorts of engineering. We probably don’t even get dressed in the morning without using products that are partly the result of modeling—even predictive modeling—in the design process.
Christians should view models as tools used by countless professionals—many of whom are believers—in order to try to make life better for people. Pastors have books and word processors. Plumbers have propane torches. Engineers and scientists have models. They’re all trying to help people and fulfill their vocations.
(An excellent use of predictive mathematical modeling…)
Why are models often “wrong”?
An aphorism about firearms says, “Guns don’t kill people; people kill people.” Implications aside, it’s a true statement. It’s also true that math is never wrong; people are wrong. Why? Math is just an aspect of reality. In response to mathematical reality, humans can misunderstand, miscalculate, and misuse, but reality continues to be what it is, regardless.
The fact that the area of a circle is always its radius squared times an irrational (unending) number we call “pi” (π) remains true, no matter how many times I misremember the formula, plug the wrong value in for π, botch the multiplication, or incorrectly measure the radius.
The point is that models, as complex representations of how variables relate to each other and to constants, are just math. In that sense, models are also never “wrong”—just badly executed or badly used by humans. That said, a model is usually developed for a particular purpose and can be useless or misleading for the intended purpose, so, in that sense, “wrong.”
When it comes to using models to find patterns and predict future events, much of the trouble comes from unrealistic expectations. It helps to keep these points in mind:
- Using models involves inductive reasoning: data from many individual observations is used in an effort to generalize.
- Inductive reasoning always results in probability, never certainty.
- The more data a model is fed, and the higher the quality of that data, the more probable its projections will be.
- When data is missing for parts of the model, assumptions have to be made.
- Changes in a model’s predictions are not really evidence of “failure.” As the quantity and quality of data changes, and assumptions are replaced with facts, good models change their predictions.
- True professionals, whether scientists or other kinds of analysts, know that models of complex data are only best guesses—and they don’t claim otherwise.
- The professionals that develop and use models in research are far more tentative and restrained in their conclusions than people who popularize the findings (e.g., the media).
In the case of COVID-19, one of the most influential models has been one of IHME’s (Institute for Health Metrics and Evaluation). Regarding that model, an excellent Kaiser Family Foundation article notes:
Models often present “best guess” or median forecasts/projections, along with a range of uncertainty. Sometimes, these uncertainty ranges can be very large. Looking at the IHME model again, on April 13, the model projected that there would be a 1,648 deaths from COVID-19 in the U.S. on April 20, but that the number of deaths could range from 362 to 4,989.
Poor design and misuse have done some damage to modeling’s reputation. Some famous global-warming scandals come to mind. But in the “Climategate” controversy, for example, raw data itself was apparently falsified. The infamous hockey stick graph appears to have involved both manipulated raw data and misrepresentation of what the model showed. Modeling itself was not the problem.
(XKD isn’t completely wrong … there is such a thing as “better garbage”)
Why bother with models?
Given the uncertainty built into predictive mathematical models, why bother to use them? Usually, the answer is “because we don’t have anything better.” Models are about providing decision-makers, who don’t have the luxury of waiting for certainty, with evidence so they don’t have to rely completely on gut instinct. It’s not evidence that stands alone. It’s not incontrovertible evidence. It’s an effort to use real-world data to detect patterns and anticipate what might happen next.
As for COVID-19, the idea that too many sick at once would overwhelm hospitals and ICUs, and that distancing can help slow the infection rate and avoid that disaster, isn’t a matter of inductive-reasoning from advanced statistical models. It’s mostly ordinary deduction (see LiveScience and U of M). If cars enter a parking lot much faster than other cars exit, you eventually get a nasty traffic jam. You don’t need a model to figure that out.
You do need one if you want to anticipate when a traffic jam will happen, how severe it might be, how long it might last, and the timing of steps that might help reduce or avoid it.
Leaders of cities, counties, states, and nations have to manage large quantities of resources and plan for future outcomes. To do that, they have to make educated guesses about what steps to take now to be ready for what might happen next week, next month, and next year. It’s models that make those guesses educated ones rather than random ones.
Highly technical work performed by exceptionally smart fellow human beings is a gift from God. Christians should recognize that. Because we’ve been blessed with these people and their abilities (and their models) COVID-19 isn’t killing us on anywhere near the scale that the Spanish Flu did in 1918 (Gottlieb is interesting on this). That’s divine mercy!
(Note to those hung up on the topic of “the mainstream media”: none of the sources I linked to here for support are “mainstream media.” Top image: IHME.)
Aaron Blumer 2016 Bio
Aaron Blumer is a Michigan native and graduate of Bob Jones University and Central Baptist Theological Seminary (Plymouth, MN). He and his family live in small-town western Wisconsin, not far from where he pastored for thirteen years. In his full time job, he is content manager for a law-enforcement digital library service. (Views expressed are the author's own and not his employer's, church's, etc.)
- 180 views
What would bias Trump to prefer that people die rather than that they live?
That is what the media uses these models for.
I know, they don’t really rhyme…
[Aaron Blumer]To refocus, let me ask this: what ideology would bias scientists to prefer that people die rather than that they live?
There are a few very very far left folks who believe that we should all die so the planet will be saved/restored to it’s primal perfection. This is a minority fringe view at best… And these aren’t the sort of people who dedicate their careers to medical science.
So other than the far fetched notion that all these independent and competitive medical data modelers colluded to defeat Trump, what bias could their be that would actually make any difference in this kind of work?[Throwaway paragraphs, borderline straw-man arguments.]It’s all well and good to talk about bias in climatology and anti-creation bias in biology and physics. But what sort of bias would make make career healers want to rig their models so that they crash economies all over the world and cause a lot of people to die who wouldn’t have if they’d told the truth?
It’s great spy thriller movie stuff, a great story, but it’s not anything close to probable.
Two.
First, the bias that scientists have against the Trump administration. Liberal politicians everywhere hate Trump with such extreme vitriol that they have been doing everything possible to get him out of office (including a completely throwaway impeachment, which was very close to political suicide for the left) since he won the election. Scientists do not visibly evidence the same degree of hatred, but the overarching political leaning of scientific academia is undeniably leftist. The scientific community cannot be characterized as wholly anti-Trump like the political left, but the community is most certainly overwhelmingly liberal.
Second, and more importantly, the bias that comes into the mind of humanists - God-haters, in general. The professional scientific community is anti-[one, true] God. A majority of that community supports abortion – you should need no further evidence than that regarding their opinion of the value of human life. I don’t believe they purposefully skewed results of studies to “prefer” more death, as you argue (another straw-man?), but it is very easy to allow non-scientific thinking to produce data that will favor one’s own world view. They do it all the time with climate studies and pro-evolution/anti-young-earth-creation research, why not do it now?
I’m guessing by now most of you have heard about the CDC’s latest numbers on provisional death counts. The truth about how mild COVID-19 is becomes increasingly evident, and it further amplifies the reality that the models were terribly overinflated. Why would scientists do this? There can only be two reasons: they are incompetent, or they are biased. Everyone including myself wants to believe the former is not true, which leaves the latter. Meanwhile, domestic violence numbers continue to increase, and unemployment numbers are expected to now be the highest they have been since 1939. Incompetent or biased modeling is to blame. I think bias is more likely.
Ashamed of Jesus! of that Friend On whom for heaven my hopes depend! It must not be! be this my shame, That I no more revere His name. -Joseph Grigg (1720-1768)
And as Christians we’re called to love truth and grow in truth-loving habits.
Can’t we agree on this while acknowledging that the models were inaccurate, wildly inaccurate in many cases? Models are math, but as we all learned at the very beginning of math and are reminded every day we help our children with math homework/schoolwork, formulas and models only give good information when you put good data into them. I always ask my kids, “Does that answer make sense?” When the answer is, “No,” it’s back to the drawing board.
I think we can agree that we should not be dismissive of scientific modeling. We should be rather skeptical about bad scientific modeling. I find it hard to understand why we should still be defending that or criticizing those who are pointing out that the models are bad.
Whatever the models said at the beginning, as we progressed, they no longer made sense. Doesn’t loving the truth mean we should acknowledge that the models were not truthful and were not even close (even if they were well-intended)? Saying “That’s just how models work” is inaccurate and insufficient. Models are supposed to give reasonable depictions of things. In other words they were false. We don’t even have to attribute some ill intent or motive to the modelers (though it would seem wrong not even to consider this). We can just say they were wrong.
And much of the news about it has been false. It shouldn’t be controversial to point that out, should it?
[Larry]And as Christians we’re called to love truth and grow in truth-loving habits.
Can’t we agree on this while acknowledging that the models were inaccurate, wildly inaccurate in many cases? Models are math, but as we all learned at the very beginning of math and are reminded every day we help our children with math homework/schoolwork, formulas and models only give good information when you put good data into them. I always ask my kids, “Does that answer make sense?” When the answer is, “No,” it’s back to the drawing board.
I think we can agree that we should not be dismissive of scientific modeling. We should be rather skeptical about bad scientific modeling. I find it hard to understand why we should still be defending that or criticizing those who are pointing out that the models are bad.
Whatever the models said at the beginning, as we progressed, they no longer made sense. Doesn’t loving the truth mean we should acknowledge that the models were not truthful and were not even close (even if they were well-intended)? Saying “That’s just how models work” is inaccurate and insufficient. Models are supposed to give reasonable depictions of things. In other words they were false. We don’t even have to attribute some ill intent or motive to the modelers (though it would seem wrong not even to consider this). We can just say they were wrong.
And much of the news about it has been false. It shouldn’t be controversial to point that out, should it?
But the point here is whether or not the modelers should be trusted or dismissed. Their data was so wrong on this one that they were either incompetent or biased. It isn’t that we hate the modelers, it’s the question of how can we trust them when the data was this wrong.
Ashamed of Jesus! of that Friend On whom for heaven my hopes depend! It must not be! be this my shame, That I no more revere His name. -Joseph Grigg (1720-1768)
I watched a sermon from a well-known Reformed pastor yesterday who called for civil disobedience. He said the entire thing is a deliberate power grab by Democratic Governors, and that they didn’t care about churches. He spent a good deal of his sermon providing examples from Scripture about how God blessed civil disobedience. The sermon had 10,000 views on Facebook when I saw it.
Having worked in government my whole life, I found his comments stupid and simplistic. People in government are not out to destroy churches. We’re not important enough. We flatter ourselves on that one. I do wonder, however, if I’m discounting the demonic aspect working behind the scenes in these government decisions.
Regardless, there is a lot if unhappiness and skepticism out there about COVID-19. A lot.
Tyler is a pastor in Olympia, WA and works in State government.
First, the bias that scientists have against the Trump administration. Liberal politicians everywhere hate Trump with …
I note that there is no evidence backing this. It’s just asserted. But that’s a distraction, really. The question I posed earlier remains. How would this bias work among scientists doing this kind of work? Are they really going to botch what their bread and butter depends on to defeat an American president when a large number of them aren’t even Americans? It’s not rational to think everything that happens is somehow about Trump. This is not about Trump. Quite a bit of what happens is not.
Second, and more importantly, the bias that comes into the mind of humanists - God-haters, in general. The professional scientific community is anti-[one, true] God.
This is the sort of attitude that has resulted in vast numbers of Christians never even considering a career in science. It’s unfortunate. But again, it’s not relevant. How would this bias change what scientists do in the kinds of projects we’re talking about here? Is there any reason think an atheist scientist wants to cripple global economies, kill lots of people, or make his own models look wildly bad in order to defeat an American president? People in medical science are in it because they want to improve public health and help people. I’m sure there a few exceptions but that really doesn’t defeat my point. There is no scenario where it makes sense for these professionals to intentionally misrepresent this disease. There is no scenario where these workers’ religious or political bias would make them, as a whole, want to act contrary to the purposes they’ve dedicated their lives to up to this point.
The truth about how mild COVID-19 is becomes increasingly evident, and it further amplifies the reality that the models were terribly overinflated. Why would scientists do this?
This is not even close to an accurate representation of the latest information. You’re basically arguing here that the models prove that the models are wrong. In any case, I’ve explained repeatedly and at length how models work. This is a dead horse.
Can’t we agree on this while acknowledging that the models were inaccurate, wildly inaccurate in many cases? Models are math, but as we all learned at the very beginning of math and are reminded every day we help our children with math homework/schoolwork, formulas and models only give good information when you put good data into them.
These sentences don’t go together. If a model is fed poor data and the projections don’t turn to “come true,” there is no defect in the model. This is a data problem.
Please learn about how models work.
In any case, as I’ve already explained, predictive models project a range of possibilities with varying levels of probability. They don’t say “this will happen” or “this will not happen.” There are always lots of “ifs” and “probablys” and “possiblys.”
If a model’s predictions to do not change significantly as assumptions are replaced with facts and data improves, that would be evidence of a defective model. For this kind of data—an unfolding pandemic that we knew zero about at the beginning—predictions staying the same = bad model. I don’t know how to make it any simpler.
Models are supposed to give reasonable depictions of things. In other words they were false. We don’t even have to attribute some ill intent or motive to the modelers (though it would seem wrong not even to consider this). We can just say they were wrong.
This is not correct and I’ve already explained why and how. Feel free to reread. I don’t have anything new to say about that.
And much of the news about it has been false.
This is correct. What it means is that news media have not paid close enough attention to the right aspects of models, namely, how they work, what they actually claim, and how they’re supposed to be used.
The reason this has progressed to the point where you think this is that Christians (and the public in general) get their “knowledge” of science from the presentation in the press, rather than from actual books or scientific journals. And since the press (and unfortunately, some scientists) have demonstrated their willingness to abuse science to achieve whatever ends (political, social, etc) they have in mind, and use it as a club to beat those not “in the know” into submission, people start to distrust not only the messenger, but the actual science behind the messenger. That’s sad, but not particularly unexpected.
This is true and underscores what I’ve been saying. Science is not the problem. Scientists aren’t even the problem.
Can we all agree on one thing - that the next time the world is called to look to the experts, everyone will be even more skeptical than they are this time?
I’m not sure it’s going to turn out that way. The groups looking at everything about COVID-19 through a political lens are a minority (though a very loud one) and as I survey what’s being written and said on these topics, the anti-science/anti-models attitudes drop off sharply as soon as one moves even a couple of steps away from the views of the most passionate political zealots.
But if it does turn out that way, it’ll be another educational failure. To me, the main problems we’re seeing with this are (a) poorly educated/lazy/politically-driven media (on both left and right) and (b) a general public that isn’t good at critical thinking when it comes to analyzing claims from those they see as their own (“Us”) vs. those they see as not their own (“Them”).
All the us’s and them’s are humans with the full range of normal human motivations. There isn’t a large class of “Them” that have bizarre motives for what they do.
scientists were “priests of fact” as Aaron suggests, but that is not the reality.
Never said anything close to that. Pretty sure you know that, too, Mark. Trying to force reality into a binary that’s either “scientists are all wrong” or “the sciences are priests of fact” can only result in confusion.
What if … epidemiologists in civil service, and in research facilities, are dedicated professionals trying to do their best amidst a lot of uninformed criticism and scrutiny from people who no idea what they’re talking about?
Yep.
In other words, this isn’t just an easy “people are going to DIE from Covid so STAY HOME!” decision.
Nobody is saying it is… well the Public Service Announcements do, I suppose, but in a 15 or 30 second ad, you have to be really focused on the central message. I’ve been preaching (sometimes literally) since well before the COVID outbreak: go to good sources, folks.
I want to plug this video again: https://youtu.be/TflnboU2y10
I would encourage everybody to subscribe to the JAMA Network and view/listen to a few of these videos. It’s a pretty potent reality check as far as what these people are really interested in, what drives them.
There is a drum playing marching music in the background. That drumbeat is a call to defeat Trump. To deride everything he does. To call him callous for “not believing the models” and acting on them.
Trump shuts down the economy to save lives.
More all-about-Trumpism.
This is a global phenomenon. Nations all over the world have taken economy-crippling steps to fight this disease. The probability that this is all about Trump is not significantly higher than zero.
What would bias Trump to prefer that people die rather than that they live?
Obviously nothing. Doesn’t defeat my point.
Having worked in government my whole life, I found his comments stupid and simplistic. People in government are not out to destroy churches. We’re not important enough. We flatter ourselves on that one. I do wonder, however, if I’m discounting the demonic aspect working behind the scenes in these government decisions.
Or you could just have leaders making the best decisions they can with the information they have. They’ve all got a mix of motives, of course. Elected officials never stop being political. It’s impossible, and as much as it frustrates at times, this is part of the genius of our system. None of these leaders has absolute power because they all have to please large constituencies in order to remain in power. Majorities will have to still be happy enough with them to vote for them again. They’re all keenly aware of that.
So the result is that you have lots of inefficiency. This is the price we pay to avoid real tyranny, or pretty quickly end it when actions cross that line.
But Tyler’s observation raises another important point: I’m persuaded that too many on the conservative end of things don’t know enough real humans who work in government and in science, and this where these sinister-motive narratives find such fertile ground.
My work over the last five years has put me in contact with lots of real humans that have profoundly different views from me on things. Without exception, when I’ve gotten to know them, their humanity has been the mostly keenly-felt reality. The extreme, “Us” vs. “Them” grid collapses very quickly when you have attentive conversations with people that turn out to be, by virtue of shared humanity, more like you than not.
But that experience does require being interested and listening.
Views expressed are always my own and not my employer's, my church's, my family's, my neighbors', or my pets'. The house plants have authorized me to speak for them, however, and they always agree with me.
[Aaron Blumer](First, the bias that scientists have against the Trump administration. Liberal politicians everywhere hate Trump with …)
I note that there is no evidence backing this. It’s just asserted. But that’s a distraction, really. The question I posed earlier remains. How would this bias work among scientists doing this kind of work? Are they really going to botch what their bread and butter depends on to defeat an American president when a large number of them aren’t even Americans? It’s not rational to think everything that happens is somehow about Trump. This is not about Trump. Quite a bit of what happens is not.
What? Seriously? There is no evidence backing that liberal politicians everywhere hate Trump with … ? I think you may be as foolish as Trump, if you really believe that.
You don’t have to work that hard as a scientist to sway politicians into taking actions that the general public will never care enough to try to condemn them such that they would lose their bread and butter.
Or maybe, just maybe, there will be a public outcry enough to actually call into question the models and someone with enough money brings a lawsuit. Who knows. Stranger things have happened. If the next year plus brings about economic and social disaster as a result of the actions governments have taken to prevent the end of the world pandemic, we may see some interesting things about how science and modeling impacted the decision making process.
[Aaron Blumer](The truth about how mild COVID-19 is becomes increasingly evident, and it further amplifies the reality that the models were terribly overinflated.)
Why would scientists do this?
This is not even close to an accurate representation of the latest information. You’re basically arguing here that the models prove that the models are wrong. In any case, I’ve explained repeatedly and at length how models work. This is a dead horse.
I should have better placed the CDC link in my response. I am not arguing about a model proving a model wrong. The CDC data, not a model, but actual data, increasingly shows the inaccuracy of the models. SARS-CoV-2 is increasingly revealing the foolishness of mankind - and I don’t mean only scientists. Maybe that’s how God wants it anyway.
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I feel as though you have come to a point in your responses where you feel as though you must present anything you possibly can to keep yourself from giving up any ground so as to not lose credibility. Several of us have presented reasonable, logical arguments, and yet you continue to defend scientists who clearly not only missed the mark, but who so grossly missed it that the only explanations are either incompetence or bias. I choose the latter to be the more likely. It seems you believe that their models, in this case, have shown them to be incompetent (in this case). Either way, it should cause everyone, not only Christians, to stop trusting science so much.
I’m going to sign out on this one. Enough has been said on both sides, at this point. It has moved beyond reasoned discourse to noise.
Ashamed of Jesus! of that Friend On whom for heaven my hopes depend! It must not be! be this my shame, That I no more revere His name. -Joseph Grigg (1720-1768)
They want us to stay in our homes, so they can lay chem-trails overhead and control our minds from the fallout.
Tyler is a pastor in Olympia, WA and works in State government.
Somehow Weird Al’s song “Foil” comes to mind at this point. But a bit more seriously, if our response to the “official” models is not a critique of the methodology and models going in, but is rather simply a personal attack or other genetic fallacy, we deserve all the mockery the world is going to dish out at us.
Does the media have it out for Trump? Sure. Do certain of the civil servants as well? You bet. However, that alone does not mean that their work is flawed. You’ve got to proceed from the evidence, not the personalities.
And that evidence starts from the reality that every significant epidemic starts with a huge pot of significant unknowns and a reality that makes modeling difficult; you start with a small # if infections/hospitalizations/deaths, and you’re hoping to predict an exponentially larger number of the same at a point in the future, and that while peoples’ behavior is changing.
Um, yes, you’re going to have some pretty wide confidence ranges (I’ve seen the same for end of life Arrhenius/Weibull predictions, and that will not necessarily have anything to do with any bias on the part of those doing them. It’s just the nature of the beast.
And as we determine whether this is something that might just play out, or whether we need to get significant herd immunity to stop it, you know what? We need these models going forward. Maybe we ought to be a little bit more educated, and a touch nicer, about the matter.
Aspiring to be a stick in the mud.
like chem-trails or tin foil hats or illuminati and lizard men.
I am shocked you would compare reasonable objections to how models are being used to that.
I was referring to people who believe all Democrats, particularly Democratic Governors, are each engaged in a united effort to destroy this country so they can impose socialist control. Conspiracy theories and general irresponsibility appear to be endemic on the right, particular the Religious Right. I’m not sure why.
As someone who has worked in government my entire life, I can safely say this - government cannot pull off a massive conspiracy! Yet, the simplistic statements (“they’re trying to take control,” etc.) we see everywhere by irresponsible fools on the Right make it clear that some of these people are simply not rational human beings. Their followers who parrot their lines and share their YouTube videos are being irresponsible.
“Don’t let a good crisis go to waste,” indeed! Many people in the Religious Right Industrial Complex are taking that to heart, and are whipping up gullible people (including too many Christians) into a frenzy of foolishness.
The pastor I mentioned, above, who called for civil disobedience was Jeff Durbin. His sermon has now been watched over 30,000 times on Facebook.
Tyler is a pastor in Olympia, WA and works in State government.
I was referring to people who believe all Democrats, particularly Democratic Governors, are each engaged in a united effort to destroy this country so they can impose socialist control.
Do you believe that people can be so desperate for power that will engage in certain behaviors to increase the chances of gaining that power?
[Larry]I was referring to people who believe all Democrats, particularly Democratic Governors, are each engaged in a united effort to destroy this country so they can impose socialist control.
Do you believe that people can be so desperate for power that will engage in certain behaviors to increase the chances of gaining that power?
Certainly they could be. The trick here is that there’s a perfectly innocuous explanation about why the early estimates were high, and for that matter why other estimates seem off as well. This is not a banker’s calculation where you expect everything to match precisely, all the way down to the second decimal place (and hold additional data for accurate rounding later). It’s an extrapolation on a pattern with exponential growth and shifting assumptions that’s going to create wide error margins.
And if someone were attempting such a conspiracy, there are way too many people involved with easy access to the Internet and the press to keep it silent. Per Mark’s comment, yes, it is nearly as ridiculous as talk of black helicopters and aluminium foil hats.
Aspiring to be a stick in the mud.
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