Christians Shouldn’t Be Dismissive of Scientific Modeling
Image
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.)
Got curious about the alleged prediction from “the model” that 2.2 million would die of COVID-19 in the US.
What actually happened…
- scientists in UK used the UK’s Imperial Model
- They wrote a report full of numbers describing worst case scenarios in various regions
- The worst case scenario was that people would not change they’re behavior at all in response to the spread of the virus
- This hypothetical absolute status quo is silly, but it was clearly communicated in the report as the scenario being described
- One of the regions was US, and the absolute status quo outcome they estimated was 2.2 million deaths
This write up at Reason seems to be very well documented: https://www.google.com/amp/s/reason.com/2020/03/31/2-2-million-american…
From the report
In the (unlikely) absence of any control measures or spontaneous changes in individual behaviour, we would expect a peak in mortality (daily deaths) to occur after approximately 3 months (Figure 1A). In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic. Epidemic timings are approximate given the limitations of surveillance data in both countries: The epidemic is predicted to be broader in the US than in GB and to peak slightly later. This is due to the larger geographic scale of the US, resulting in more distinct localised epidemics across states (Figure 1B) than seen across GB. The higher peak in mortality in GB 16 March 2020 Imperial College COVID-19 Response Team is due to the smaller size of the country and its older population compared with the US. In total, in an unmitigated epidemic, we would predict approximately 510,000 deaths in GB and 2.2 million in the US, not accounting for the potential negative effects of health systems being overwhelmed on mortality.
The report even says this outcome was “unlikely.”
So… there never was any model that predicted 2.2 million in the US would die.
There was, in fact, a model that predicted that 2.2 million were “unlikely” to die.
As for the observation that this many might die if there was no response whatsoever… for all we know, that number might be correct.
The problem was, apparently, that the Imperial Model wasn’t designed to factor in how people and governments actually behave.
Maybe this was done in order to reduce the number of variables and increase the probability of a narrower range of projected deaths?
No idea.
The Reason piece goes on to point out
Unfortunately, the media generally failed to make clear that this was not a real-world projection, and were abetted in that malfeasance by the lead author of the study, Neil Ferguson. For example, Dr. Ferguson told the New York Times on March 16th that the potential health impacts were comparable to the devastating 1918 influenza outbreak. That outbreak killed approximately .6% of the U.S. population, which today would amount to around two million people, or very close to the fanciful 2.2 million projection. Nor does Ferguson seem to have made any effort to correct Kristof et al. when they wrongly claimed that 2.2 million was a realistic worst-case scenario.
And the media continues to misreport what the study said.
So, I don’t know what all this proves, but it doesn’t prove the models are bad. It seems pretty in line with what I wrote in my article: math is never wrong; people are.
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.
Earlier I cited an article that gave third party reporting to something Dr. Fauci may or may not have said.
The following quote attributes Dr. Fauci directly:
“Whenever the models come in, they give a worst-case scenario and a best-case scenario. Generally, the reality is somewhere in the middle. I’ve never seen a model of the diseases that I’ve dealt with where the worst case actually came out. They always overshoot,” Dr. Anthony Fauci, a key member of the White House’s coronavirus task force, told CNN’s Jake Tapper on “State of the Union.”
Source? CNN, March 30, 2020 - emphasis mine
So we should believe modeling exactly why?
Maranatha!
Don Johnson
Jer 33.3
[Don Johnson]Earlier I cited an article that gave third party reporting to something Dr. Fauci may or may not have said.
The following quote attributes Dr. Fauci directly:
“Whenever the models come in, they give a worst-case scenario and a best-case scenario. Generally, the reality is somewhere in the middle. I’ve never seen a model of the diseases that I’ve dealt with where the worst case actually came out. They always overshoot,” Dr. Anthony Fauci, a key member of the White House’s coronavirus task force, told CNN’s Jake Tapper on “State of the Union.”
Source? CNN, March 30, 2020 - emphasis mine
So we should believe modeling exactly why?
Perhaps….because Dr. Fauci does? Perhaps because he understands the role of variance and human action in where the models go, and he’s still staking his career and life (the man is 79, after all, prime COVID vulnerability age) on the response to this epidemic? Perhaps because he, and the agency he’s headed since 1984, has been calculating estimates of virulence and lethality accepted by medical experts around the world, and whose models have been used to address pandemics (ebola, H1N1, avian flu, etc..) around the world?
Honestly, Don, I don’t think you’d take it well if you were treated with the contempt you’re pouring out on many of the top epidemiologists of the world. Maybe extend some of the same courtesy you’d expect, and maybe even consider learning about WHY Dr. Fauci isn’t particularly bothered that early estimates are higher than the actual result?
(hint; it has something to do with statistical confidence ranges and the fact that people sometimes respond to perceived threats.. )
Aspiring to be a stick in the mud.
Have you been alive the last 3.5 years when the media uses things like this to manipulate news stories to make Trump look like the worst president ever? Or have you been stuck under a rock?
[Mark_Smith]Have you been alive the last 3.5 years when the media uses things like this to manipulate news stories to make Trump look like the worst president ever? Or have you been stuck under a rock?
Mark, if this is a conspiracy where huge numbers of doctors are faking death certificates to make it look like someone with no symptoms of COVID died of it, don’t you think that someone would be raising H*** about the matter? Sixty thousand corpses/funerals and hundreds of thousands of hospitalizations are pretty darned hard to fake, don’t you think?
It’s possible to maintain a conspiracy when you’ve got only a few dozen people holding all the cards (e.g. the Mueller investigation), and the relevant data are largely hidden from the public—and keep in mind there that as the data are coming out, all H*** is breaking loose. It’s also halfway possible to maintain a false narrative when one side of the argument is funding all the research—e.g. global warming. In this case, however, you’ve got millions of witnesses to how their loved ones died after showing the symptoms of COVID.
No doubt that the media have the long knives out for Trump, but the data I’m working on are pretty darned hard to fake.
Aspiring to be a stick in the mud.
You still don’t get it. Have 58000+ people died of COVID in the US. Yes! Personally, I would consider 70K deaths by August to be a tremendous success in pandemic terms. Was the US unprepared for this? Absolutely. ANY PRESIDENT would have been unprepared because people do not like spending money preparing for things… they want low taxes, not stockpiles of PPE and ventilators. They want cheap stuff, not PPE made in Michigan. So have it made in China… no problem right? Every president and every Congress has known this was going to eventually happen and NO ONE did anything about it. Not just Trump.
You act like I’m some conspiracy nut. Far from it.
What I am talking about is how every news outlet uses the models to say we need “better leadership.” Let’s write 5 articles today on how Trump didn’t prepare well enough for this virus. Things like that. The sole reason they use models is to attack Republicans. That is what I despise. That is what makes the models pointless.
Of course models “predict the worse case and the best case.” That is not the point.
The point is how models are being used to weaken (or perhaps destroy) a presidency and a nation just for the political, social, and cultural benefit of one side who controls the main stream media.
And finally Bert, please stop acting like you are modeling this epidemic. Its creepy. (“but the data I’m working on are pretty darned hard to fake.”)
Mark, I’m going to have to suggest that it’s you who doesn’t get it. No, the reason journalists use models is not solely to attack the President, but because they happen to be news. Moreover, the solution to the problem of journalists misunderstanding models is emphatically not for us to attack the models. The proper response is to explain them in their proper context.
And yes, I do happen to be doing a simple model to try and clarify what’s going on. This is something that anyone who remembers high school health class and 1st semester calculus ought to be able to do, and I make no apologies for it. It is the kind of thing that we all ought to be doing to start shedding light on the subject instead of merely heat and anger. Give it a try.
Aspiring to be a stick in the mud.
is the journalists are biased political operatives. Its not “lack of understanding” about the context of the model.
[Bert Perry]And yes, I do happen to be doing a simple model to try and clarify what’s going on. This is something that anyone who remembers high school health class and 1st semester calculus ought to be able to do, and I make no apologies for it. It is the kind of thing that we all ought to be doing to start shedding light on the subject instead of merely heat and anger. Give it a try.
Bert, if you want to do that, go ahead. But stop pretending you are a public health modeler. You aren’t.
“Whenever the models come in, they give a worst-case scenario and a best-case scenario. Generally, the reality is somewhere in the middle. I’ve never seen a model of the diseases that I’ve dealt with where the worst case actually came out. They always overshoot,” Dr. Anthony Fauci, a key member of the White House’s coronavirus task force, told CNN’s Jake Tapper on “State of the Union.”
This is consistent with what I’ve been saying and said in the article. I explain there both why models work this way and why they’re still useful.
It’s really not hard to understand that a range of possible outcomes with a range of probability is more useful than no information at all. … I have to think that folks not getting this are just not trying very hard.
Nothing I can do about that.
@Mark: “The media” do not control the models. They don’t develop them, they don’t collect the data for them, they don’t fund them, they sometimes try to interpret them—but usually leave even that to others… then interpret the interpretation.
So, the “debate” kind of goes like this:
- Aaron: various facts and reasoning from them (analysis, and opinion downstream of that)
- Response: hey, look over there at that awful stuff!!!!
Well, that’s one way to interact with information. It’s not a truth-loving way, though. And as Christians we’re called to love truth and grow in truth-loving habits. Every single one of us.
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]“Whenever the models come in, they give a worst-case scenario and a best-case scenario. Generally, the reality is somewhere in the middle. I’ve never seen a model of the diseases that I’ve dealt with where the worst case actually came out. They always overshoot,” Dr. Anthony Fauci, a key member of the White House’s coronavirus task force, told CNN’s Jake Tapper on “State of the Union.”
This is consistent with what I’ve been saying and said in the article. I explain there both why models work this way and why they’re still useful.
Aaron, your explanation fails. Models that always overshoot are worse than useless. People in authority make decisions based on the worst case scenario, and in this case they are bankrupting the country, causing unnecessary harm. If the models were more accurate, more reasonable decisions could be made.
Maranatha!
Don Johnson
Jer 33.3
Stop. Take a breath. Consider the breadth of the reporting on COVID-19. Now, be honest. Is most of it in the national media (NYT, LA Times, CNN, MSNBC, CBS, NBC, etc. ) telling a totally impartial view of data and modeling. Or, is it being used to drive an agenda that somehow the federal government under Donald Trump is not doing enough. Even when something is positive, do they show it that way? For example, we are testing 250,000+ people a day for COVID-19. That is a tremendous success. Listen to Dr. Birx talk about that. This is hardcore testing looking for nucleic acids of the COVID-19 virus. Only HIV and HPV testing does that. Most rapid flu tests use antibodies. COVID has resisted a fast antibody test up until recently, and even then it is iffy. Did the government drop the ball on testing early on? Yes. that is undeniable. But they have ramped it up to a level no one on the Earth has ever done before. How does the media report that? They talk about percentages of population being tested to hide any success…
So, modeling is one thing. It is obvious to any honest observer that the modeling is being used by the media to drive their narrative. Is that the model’s fault? No. It is the media’s fault.
Now, Don talks about a different problem. I think along with others that some models are deliberately high to try to drive an outcome with the model. That is separate from media bias.
Stop. Take a breath. Consider the breadth of the reporting on COVID-19. Now, be honest. Is most of it in the national media (NYT, LA Times, CNN, MSNBC, CBS, NBC, etc. ) telling a totally impartial view of data and modeling. Or, is it being used to drive an agenda that somehow the federal government under Donald Trump is not doing enough. Even when something is positive, do they show it that way?
Never stopped breathing. :-D
Mark, these are two different topics:
- the problem of what people (including the media) do with the information models produce
- the question of whether the models themselves are helpful and whether those who develop and use models are trying to accomplish some political goal
I’m not interested in #1 at all. My article isn’t about that, and I’m not at all interested in that because it’s a given. We all know that the majority of the largest and loudest news outlets frequently show a lot of leftward bias (not always, though!). Been there, done that (for me this happened in the 1980s!). Don’t care.
Nothing said about topic 1 has any bearing on topic 2… which is my concern here and is a far more important question.
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]Nothing said about topic 1 has any bearing on topic 2… which is my concern here and is a far more important question.
I think most of us here understand the importance of doing modeling apart from how they are used politically. The bigger question to me though, is this: why keep using (and praising) models that are known to be inaccurate? When Dr. Fauci says the worst case scenarios have NEVER come to pass, that means two things. 1. Given that the worst case will be used politically, it’s irresponsible to keep using models with a false “worst case,” and 2, more importantly, knowing that the worst case never comes to pass, the model needs serious adjustment. I completely understand that the most likely scenario is down the middle, but if one of the best or worse cases is never reached, then the model MUST be wrong (or at best incomplete), because if it were accurate, then occasionally either the best or worst case would come to pass, even if not statistically often.
Dave Barnhart
Just this morning I am going through my news feed on my phone, which, try as I might, is still biased towards leftest news… (thanks Apple). I see this “news story” which contains this paragraph:
“A new model prepared by epidemiologists and computer scientists at Harvard and the Massachusetts Institute of Technology in partnership with the Daily Beast provides an estimate of what that might look like in Georgia, where fitness centers, tattoo and massage parlors, bowling alleys and hair salons were allowed to reopen last Friday and restaurants and other businesses began operating on Monday. As of the end of last week, at least 871 people statewide had lost their lives to COVID-19. According to the model, Georgia would have logged a total of between 1,004 and 2,922 coronavirus fatalities by June 15 if it had maintained its pre-Friday lockdown policy. But that range shoots up to 1,604 to 4,236 deaths if approved businesses return to just 50 percent of their pre-pandemic activity (or “contact”) levels — and 4,279 to 9,748 deaths at 100 percent of pre-shutdown activity.”
This is what I mean by bias in models is inherent. Daily Beast asked MIT and Harvard to make a model to look at Georgia. Why Georgia you might ask, and not Massachusetts, or Illinois, or Colorado? Because the aim is to make Republicans look bad and to make Trump look bad and incompetent. They also want Georgia to pay for not electing Stacey Abrams their governor, and to make sure they do it right the next time. So modeling is about 10% math/statistics, and 90% desired result.
The only time this is not true is in modeling for business operation and such things. Say I own a production plant and I want to model profit and cost with how my plant works. I believe that model… it has no bias other than profit.
You get into the public policy realm, and someone is trying to influence something. That includes climate change modeling.
Aaron, you said that most of these models were produced before COVID so they weren’t biased. OK… but I think there is a bias in them to overinflate so politicians could not ignore them. That is why they told Trump 2.2 million, or whatever. To make it so horrible he had to act…
The bigger question to me though, is this: why keep using (and praising) models that are known to be inaccurate? When Dr. Fauci says the worst case scenarios have NEVER come to pass, that means two things. 1. Given that the worst case will be used politically, it’s irresponsible to keep using models with a false “worst case,” and 2, more importantly, knowing that the worst case never comes to pass, the model needs serious adjustment. I completely understand that the most likely scenario is down the middle, but if one of the best or worse cases is never reached, then the model MUST be wrong (or at best incomplete), because if it were accurate, then occasionally either the best or worst case would come to pass, even if not statistically often.
I’m sorry but I can’t make sense of this. Can you clarify what you mean?
These models do not claim that their best or worse cases are particularly likely to ever happen. If the model claimed to say x will sometimes happen and it never does, it would be faulty, but they don’t attempt to do that.
Aaron, you said that most of these models were produced before COVID so they weren’t biased. OK… but I think there is a bias in them to overinflate so politicians could not ignore them. That is why they told Trump 2.2 million, or whatever. To make it so horrible he had to act…
Not quite what I said. Models are just math. They can’t be biased. Humans can be biased. It’s possible (though not easy!) to build a bias into a model, but there is no rational reason for a team of scientists who’s only purpose is to make projections as accurately as they possibly can to intentionally make them inaccurate. That doesn’t pass the reality test.
A dose of reality here: IHME and a bunch of other organizations are competing globally with one another to be the go-to tool for actionable infectious disease/hospital capacity projections. So when a deadly new virus hits the entire world, they’re going to intentionally get it wrong in order to defeat the American president?
I’m continually amazed that anyone finds that to be remotely plausible.
Do people do biased things with all forms of information (including projections from models)? Of course. Not in dispute.
Some of the models are going to turn out to have had some bad calculations or bad assumptions and/or bad data. They’re not all making the same assumptions so they can’t all be right.
IHME already knows it has a lot of questionable data… but it works with the best data it can get.
The COVID Tracking Project has given up on certain kinds of data for the time being…
States are currently reporting two fundamentally unlike statistics: current hospital/ICU admissions and cumulative hospitalizations/ICU admissions. Across the country, this reporting is also sparse. In short: it is impossible to assemble anything resembling the real statistics for hospitalizations, ICU admissions, or ventilator usage across the United States. As a result, we will no longer provide national-level summary hospitalizations, ICU admissions, or ventilator usage statistics on our site.
Because this data is so spotty, IHME and others have to try to estimate likely hospital needs vs likely hospital capacity from death rates and other data. It’s one reason that projected ranges are often large.
I’ve never claimed these models were producing really great predictions… only that they’re the best predictions we have and that leaders of cities, counties, states, and nations have to do their best to plan for what might happen.
The other thing I’ve claimed is that there is no reason to believe these folks are any less honest than any other professional off the street. Are there some idiots and liars? Well, human nature being what it is, of course. But we have no more reason to believe the COVID-modelers are deceitful than we have to belive that, for example, the economics modelers are deceitful.
Why all the hostility toward IHME and others and not toward economic forecasters (who are famously wrong so much of the time)? It doesn’t make any sense.
I’ve got nothing against economic forecasters. They do their best and their predictions often turn out to be wrong. Why should I think medical professionals trying to save lives would try less hard to get their projections right? But are they going to be wrong sometimes? Of course!
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 - are the modelers deceitful, or politically motivated? I don’t think so, but I can’t know for sure.
However, their projections seemed to be wildly overstated from the beginning and the progress of the situation seems to confirm that. IHME seems closer now, with more data in, but time will tell. However, the initial models were so outrageous that the whole world stampeded into “we’ve got to do something” even though that meant economic suicide. When we come out of this, things are going to be really bad. I don’t think we need a model to be able to predict that. Our great grandchildren will be paying off the debt from these two months, if the world lasts that long.
Maranatha!
Don Johnson
Jer 33.3
Here’s an article I think offers a balanced view. My own view is pretty close to this.
Maranatha!
Don Johnson
Jer 33.3
[Don Johnson]Here’s an article I think offers a balanced view. My own view is pretty close to this.
I don’t think I disagree with anything there. I would recommend this one also: https://www.nationalreview.com/2020/04/as-new-data-improve-our-understa…
(If it doesn’t let you in, clear all your national review cookies and it probably will… or try a browser you don’t usually use)
I think it’s very likely that eventually, when we’ve got a whole lot more info and the benefit of hindsight, we’re going to see lots of mistakes were made. What I hate to see people do, though, is make the leap to the conclusion that leaders here and now should have made different decisions with the information they have now… or had in Feb or March. In some cases that might be true, but none of these decision-makers get to travel to the future then come back and make decisions now based on what they discovered.
This is true of Trump as well. Though I think he was slower to get serious than he should have been, and just about anyone at that level who is in the habit of being attentive to facts would have been quicker, he wasn’t late by a whole lot, given the ambiguities of the situation at the time. I’m not going to go into how he’s handled the situation since mid-March (you have the public Trump, and then the “what’s actually getting done” Trump; the former is obvious; the latter is hard to determine from the outside because most of the info comes through highly politicized filters.)
What should be clear to everyone by now is that there never was a single “the model” decision makers were relying on; the models they did use and continue to use are efforts to do the best we can with not very good data; the problem of all the politically-driven doing the things they usually do (on both the right and the left) is a real problem, but a separate one; the 2.2 million number came from the UK’s Imperial Model, and the model’s projections were very sloppily communicated to both the President and the media; providentially that number was big enough to wake the President up, even though he almost certainly didn’t understand it what it meant; and that the federal government has a very different role in all of this than the states and smaller jurisdictions do; also that the economy was self-closing well before all the gov’s got into action with their orders.
It’s likely that if all the restrictions were lifted at this moment, the vast majority of people would continue to socially distance, mostly stay home, voluntarily not work if they’re allowed to and aren’t out of money yet, etc. There is no “on switch” for the economy… short of a miracle cure popping up… because economies are ultimately driven by human minds in addition to human might. And the minds are not there yet, for the most part.
However, their projections seemed to be wildly overstated from the beginning and the progress of the situation seems to confirm that. IHME seems closer now, with more data in, but time will tell. However, the initial models were so outrageous
No, they really weren’t. See my post several comments up about where the 2.2 million came from. It was dumb to invent a fictional worst case scenario, but the Imperial Model report never said the worst case was likely. They specifically said it was not.
The more famous models’ early projections turned out to be quite different from reality, but this should be expected. The data is very even even now; it was far worse then. It’s like being a meteorologist who is trying to predict weather but the radar is broken and the barometers are all contradicting eachother, and observers on the ground are turning in different kinds of data under the same labels.
Of course that’s going not going to produce really good outcomes… still the best predictions anybody had at the time.
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,
Respectfully, I think you’re missing an important part of the big picture.
How much of the professional scientific community believes “the world is going to end” due to climate change? How many of their predictions over the last thirty to fifty years have come to pass – or even close?
The scientific community may be “professionals” – they are professionals who are as leftist/liberal/anti-God as possible who push any contrarians out of the peer review community. Surely you know this. Their careers and reputations depend on them catering to anti-God positions, and this frequently leads them to conclusions that cater to their anti-God, academia colleagues and associated think-tank and political friends. They may very well be among the friendliest, most intelligent people we know and interact with, but their thinking and positions are completely skewed by deep humanism.
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)
[JNoël]Aaron,
Respectfully, I think you’re missing an important part of the big picture.
How much of the professional scientific community believes “the world is going to end” due to climate change? How many of their predictions over the last thirty to fifty years have come to pass – or even close?
The scientific community may be “professionals” – they are professionals who are as leftist/liberal/anti-God as possible who push any contrarians out of the peer review community. Surely you know this. Their careers and reputations depend on them catering to anti-God positions, and this frequently leads them to conclusions that cater to their anti-God, academia colleagues and associated think-tank and political friends. They may very well be among the friendliest, most intelligent people we know and interact with, but their thinking and positions are completely skewed by deep humanism.
Two things here: you’re confusing what scientists do with how their results are reported and popularized. The vast majority of climate predictions anyone has heard about are the ones politicians, advocacy groups, and highly politicized media outlets have made famous. Most of what scientists predict, they predict with all sorts of “if…” qualifications and caveats and probability scales. The world ending anytime soon is not a claim coming from very many scientists.
And they’re mostly interested in success in their fields, not political aims. Does bias creep in? Absolutely, but no more than it does for grocers, barbers, economists, truck drivers, farmers, pastors, school teachers (well, probably far less than most of them, given how political eduction has become), plumbers, you name it.
Two, it isn’t clear at all what sort of political bias would make sense when it comes to modeling the spread of disease. How would your bias even influence you? As I’ve already pointed out, these modelers have every reason to want to get it right regardless of their politics. Unless you’re willing to fall on your sword to try to—in some very complicated and unlikely way—influence an election, your success in your profession depends on doing what you do better than others do it.
So my question to those who think the modelers have acted with a political agenda is this: how would that work? Did all these independent and global organizations get on the phone in a big secret meeting and decide “Let’s all tell essentially the same story, even though we’re using different models. Because here’s our chance to smash the US economy and get Trump out of office! … sure, we’ll smash the economies in all the other countries of the world also, and we’ll make ourselves look like idiots because our projections look wildly innacurate, but hey, it’ll be worth it!!” … and then every single one of them agreed to this plot… along with a vow of secrecy?
No, occam’s razor, folks. Just people doing their best and sometimes failing.
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.
Although not directly related to modeling, this piece expresses quite well what is happening now at the juncture I list in the subject field. You’ll note it was written by Matt Taibbi, a contributing editor to Rolling Stone, and hardly a friend of either conservatives or Christians. However, I think he gets what many of us are thinking as we consider what is happening with the coronavirus “crisis,” and why many tend not to trust models that are supposedly completely scientific and ostensibly not political. (Or at least, we don’t tend to trust their presentation, since they are often misused.) The Atlantic piece he references about why internet speech should resemble China’s censorship model more than the “free speech” model is particularly chilling.
https://taibbi.substack.com/p/temporary-coronavirus-censorship
Note: I don’t agree 100% with everything he says in this piece, but if you’re like me, it will make you think.
Dave Barnhart
I’m trying to stay on topic, but your post reveals significant flaws in your logic.
Academia, especially the scientific community, is, by a huge majority, anti-God, and, therefore, anti-American conservatism: because much (most?) of that is people who are pro-God and in complete disagreement with much of what the anti-God scientific community promotes. This means the scientific academia is immediately predisposed to hate Trump and the Republican party and do everything they can to promote liberalism/leftism and those Democrats who are anti-God. Why do they even bother modeling global warming/climate change? Why do their models always support the global warming/climate change alarmist positions? Because those are the positions that are as far from God and showing any support of a Creator as possible, and they are positions that support the liberal, leftist, anti-God agenda. The scientists themselves do not need to claim the world is coming to an end – they only need to model it in such a way that it generates the desired responses. You cannot tell me the scientific community that builds these models is not predisposed to only support and promote thinking that is anti-God. This is why the peer review process virtually eliminates any professional / expert thinking that would support or even come close to hinting at the possibility of the Divine, and why there really is, on a global scale, a sense of “let’s all tell essentially the same [wrong/anti-God] story. Ultimately, it is being driven by the enemy of God, and it is wonderfully easy for him to coordinate these attacks against God because of sinful humanity.
The political bias that would make the most sense would be that which would hurt American conservatism and help American liberalism. Again, this is easy to see when you recognize that most of scientific academia is ultra anti-God and pro-humanism.
And let’s not forget about the WHO, which is composed of “experts” all around the world and which failed to properly report SARS-CoV-2 because of political bias – toward China. China still claims to only have had 83,958 confirmed cases and 4,637 COVID-19 fatalities (laughably false statistics indeed), and yet the WHO still panders to China, despite the obvious lies they continue to propagate. Why haven’t the WHO “experts” done their jobs? Because they, too, have political motivations.
Scientists around the world are biased for political purposes. This really shouldn’t even be a topic of conversation, but you seem to think scientists pretty much don’t care about politics and only care about science. Yet they consistently ignore Truth and even fight, war against it. Anyone can use any data he wants to paint any picture he wants, and when the majority of a community hates God, the picture they are going to paint will logically follow suit. The majority of the scientific community abhors Donald Trump (and conservatives, in general) because he represents, to them, a potential loss of decades of advances in liberal/leftist/anti-God thinking.
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)
@Dave: I’ll check it out. There’s no question that getting the specialists (experts), politicians, and the masses all effectively balancing one another is a difficult thing. I’m personally convinced that we’re way out of balance in the populist direction, but I’m also not a technocrat, so there need to be disciplined and rational (not mob driven or mood driven) ways to keep experts accountable and connected to reality.
I don’t know if the article talks about this, but there’s always the problem of groupthink as well among tight communities of specialists.
This goes both ways though: specialists get too insular and lose touch with realities outside their fields; “the masses” get reflexively hostile toward experts because they don’t know enough of them as human beings.
It’s so easy to blame the big, vague “Them” for things if you don’t know any of “Them.”
Old fashioned xenophobia.
I think I want to write an article on how my thinking about science has changed over the last couple of years… and the growing impression that conservative Christians/fundamentalists have largely become anti-science. Which is unfortunate, if not tragic. But I was doing some growing in this area in 2019, and events of 2020 have accelerated it. It grieves me to see so many people I know (most in real life, not here at SI) latch on to whatever the conspiracy theory du jour is.
So we have a deep failure on “the right” (theologically and in political philosophy… which is really also part theology) to teach critical thinking and science. Political polarization + COVID has really exposed a lot of alarming deficiencies in the conservative Christian worldview. (Here I mean the version of the worldview people actually hold to, not the essence of what it is. I don’t think the worldview itself is flawed.)
In addition to what I’ve read over the last year from Christian authors, projects at work have had me digging into and summarizing lots of research in the social sciences. The first-hand interaction with their work has changed how I look at “scientists,” — even social scientists, who are famously on the soft and messy end of the science spectrum. If there’s a place where bias has lots of opportunity to shape outcomes, it’s in the social sciences, but even there, I have seen much less of it than one would expect, based on so much of the anti-science rhetoric I’ve grown up hearing in our circles.
In short, I think part of the clash on this topic is due to deeper differences in how we view science in general.
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.
[JNoël]Aaron,
Respectfully, I think you’re missing an important part of the big picture.
How much of the professional scientific community believes “the world is going to end” due to climate change? How many of their predictions over the last thirty to fifty years have come to pass – or even close?
The scientific community may be “professionals” – they are professionals who are as leftist/liberal/anti-God as possible who push any contrarians out of the peer review community. Surely you know this. Their careers and reputations depend on them catering to anti-God positions, and this frequently leads them to conclusions that cater to their anti-God, academia colleagues and associated think-tank and political friends. They may very well be among the friendliest, most intelligent people we know and interact with, but their thinking and positions are completely skewed by deep humanism.
That would be a basic genetic fallacy, and of that you ought to repent, Mr. Noel. Moreover, as someone who’s got two degrees in engineering, and who’s worked (in school and professionally) with engineers and scientists for over three decades, you happen to be wrong, too. There are people of all political stripes, and while you’ll get more liberals in government employment, there are people who will speak up when they believe the science is being misrepresented. You will find people as well from all kinds of religious perspectives; for example, about half the current group I work in is evangelical Christian homeschooling dads, and the guys down in the lab show their “liberalism” with a sign “make devices great again.” You sometimes get a near consensus when one entity (or a group of associated entities) funds most of the research, as in climatology, but even there, people not receiving funding have been instrumental in pointing out the weaknesses with the data and evidence.
I should also note, since apparently the detractors of the official models want to use divergence of model from reality as a reason to not only reject the model and its creators, that many of them were avidly pointing out a few weeks back that since COVID-19 deaths had not yet reached the level of typical flu seasons, that the models were to be rejected. Note; since that is not operative, are those who made that argument going to apply the same logic to their own comments?
Aspiring to be a stick in the mud.
Furthermore, most of the scientific/academia community (I’ll refer to to them as “their/them”) hates God, and their science forces them to promote anti-God positions. This logically leads them to political ends, because any politics that supports God or even the possibility of a Creator undermines their anti-God world view and will destroy their so-called science, ending their careers. This all makes sense when viewed from a spiritual standpoint, but it is apparent that the more exposure even a Christian has to the their worldly philosophy the easier it is to being to agree with their positions and ignore the reality of the spiritual war being waged by them, those friendly, really smart people, against God.
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)
[Bert Perry]That would be a basic genetic fallacy, and of that you ought to repent, Mr. Noel.
What you think is an attack, I think of as a rebuke.
Take it whichever way you want.
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)
[Aaron Blumer][…] my thinking about science has changed over the last couple of years… and the growing impression that conservative Christians/fundamentalists have largely become anti-science. Which is unfortunate, if not tragic. But I was doing some growing in this area in 2019, and events of 2020 have accelerated it. It grieves me to see so many people I know (most in real life, not here at SI) latch on to whatever the conspiracy theory du jour is.
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.
I won’t claim any specialized knowledge into the epidemiological models being used for coronavirus, or even mathematical modeling in general. However, I do have degrees in math/statistics and computer science, and while I won’t pit my “expertise” against those here who have math/medical PhD’s, or even engineers who use models more than I do, I also think I understand modeling reasonably well, at least better than the average U.S. citizen. A model that “predicts” possible casualties > 10-20x the actual number is likely either poorly constructed, using bad assumptions, or using bad data, or maybe a combination of those factors. OR, it could just be that the model is fine but is being misused by those reporting on it. Either way, I’m not likely to trust it when seeing those large discrepancies unless I can read everything (including the model, assumptions, and data) for myself, especially when those reporting on it have demonstrated their willingness to obscure the truth in favor of their agenda.
This is why, unfortunately, it’s difficult (if not impossible) for the average person to completely distinguish the science from the politics, even when we wish to do so.
Dave Barnhart
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? Maybe that’s a dangerous reality, but there is no one to blame but the experts themselves. They need to step up their game in how and what they communicate.
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)
scientists were “priests of fact” as Aaron suggests, but that is not the reality.
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?
Tyler is a pastor in Olympia, WA and works in State government.
[TylerR]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?
So let’s say that they are what you say they are. In most cases, I don’t have reason to doubt it. That doesn’t mean I accept the lecturing on the “meaning” of their words and findings from those who designate themselves the official interpreters of the facts, rather than just passing on the facts.
And more importantly, they’re just one set of experts. They can tell me about how the course of Covid is going to go, how many likely dead, etc. What they can’t tell me is how many are going to die because they can’t have “non-essential” elective surgeries, or how many businesses are going to close, and the eventual cost to our society of that step, or how many will commit suicide, or how many will starve, etc. In other words, this isn’t just an easy “people are going to DIE from Covid so STAY HOME!” decision.
Dave Barnhart
[TylerR]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?
It’s not that I disagree with you, and we should assume the best in others. But what if most of those professionals believe the universe is billions of years old and that humans evolved from primordial goo? And what if many of those professionals are hostile in their thinking toward anyone who claims the earth is young and that it was created by God in six days?
Just sayin.’
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)
You wrote:
But what if most of those professionals believe the universe is billions of years old and that humans evolved from primordial goo? And what if many of those professionals are hostile in their thinking toward anyone who claims the earth is young and that it was created by God in six days?
Yes, but what are you going to do about it? Dismiss it all because you don’t like their worldviews? You don’t do that with laws. I don’t do that when I’m forced to consider whether an insurance company “discriminates” against a transgender individual because it has a blanket prohibition against breast augmentation for male-to-female surgeries. I’m obligated to consider that our state statute defines “sexual orientation” to include a subjective feeling of “gender identity,” and that its illegal to “discriminate” on that basis. This is a real case!
Do you rebel against all authorities that don’t share a Christian worldview? I don’t understand what you want to do.
Tyler is a pastor in Olympia, WA and works in State government.
was that models are scientific analyses of the situation. Ok. Say I take that as valid. So what?
What do you do with that model? That is the question.
If you are honest and unbiased, and you predict say 200,000 deaths, you call the leaders to act. So they do.
If it was all so antiseptic, that would be great. But it isn’t.
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. The media then reports “great depression hits America.” Why? To weaken Trump. Not to be honest.
Its all designed to weaken a man they want gone.
That is the problem. This isn’t about science, or data, or medicine. Its about politics and culture war.
[JNoël]It’s not that I disagree with you, and we should assume the best in others. But what if most of those professionals believe the universe is billions of years old and that humans evolved from primordial goo? And what if many of those professionals are hostile in their thinking toward anyone who claims the earth is young and that it was created by God in six days?
Just sayin.’
Well, either the assumptions they make, the data they present, and the correlations they derive work, or they do not. It has nothing to do with their philosophical and religious presuppositions. Your claim is a genetic fallacy that proves nothing except that you are unable or unwilling to make a real argument.
It’s also false. Sorry, I’ve spent a lot of years in and around secular universities (Michigan State and Colorado, my daughters are at Winona State), and in the sciences and engineering, most professors, whatever their personal views, really want to simply do the best job they can in teaching and research. Science tends to have right answers that push out ideologues from the start, and going further, students quickly figure out who has an agenda—and avoid those professors. That avoidance is career death to a professor in the sciences because you need students to teach, and grad students to publish. Professors who are avoided by students don’t get tenure, plain and simple.
I realize that the stereotype you’re using is popular in some sectors of fundamentalism, but it’s time to let it go. Deal with the evidence, not the personal views of those presenting it.
Aspiring to be a stick in the mud.
[TylerR]Yes, but what are you going to do about it?
Do you rebel against all authorities that don’t share a Christian worldview? I don’t understand what you want to do.
Really, my only point in this conversation is that we should not simply accept everything the anti-God worldview scientists are telling us, and to recognize that their lack of the Spirit will often lead them to conclusions that feed their flesh more than a Christian walking in the Spirit. It can look different for different scientists - some for money, some for political gain, some for notoriety among their peers, and, of course, some really are just looking for truth and are trying to do the right thing.
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)
[Bert Perry]Well, either the assumptions they make, the data they present, and the correlations they derive work, or they do not. It has nothing to do with their philosophical and religious presuppositions. Your claim is a genetic fallacy that proves nothing except that you are unable or unwilling to make a real argument.
Seriously? I don’t know who you spent time with, but this is not at all what I have seen and experienced. The philosophical and religious presuppositions absolutely drive their decision-making. Ultimately, philosophical and religious presuppositions drive every human’s decision-making, whether we want to believe it or not. Secular science is anti-God and is unwilling to acknowledge any study that would take them down the road of needing to acknowledge the possibility of a God.
[Bert Perry]It’s also false. Sorry, I’ve spent a lot of years in and around secular universities (Michigan State and Colorado, my daughters are at Winona State), and in the sciences and engineering, most professors, whatever their personal views, really want to simply do the best job they can in teaching and research. Science tends to have right answers that push out ideologues from the start, and going further, students quickly figure out who has an agenda—and avoid those professors. That avoidance is career death to a professor in the sciences because you need students to teach, and grad students to publish. Professors who are avoided by students don’t get tenure, plain and simple.
Yes, they do - scientists regularly push out religious ideologues. How many of the professors you spent a lot of years in and around did you try to get to recognize the truth of creation and how foolish and unscientific their belief in science is?
If you were a scientist, striving to excel in the field, they would mark you as an ideologue and marginalize your beliefs, finishing any aspirations you would have in advancing within their community. If you did share and argued your rightly held belief in Creation with them and they took no action against you, then they did not see you as a threat and simply didn’t bother with pushing back (“You believe in creation? How quaint. Now let’s get back to the real work.”).
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)
We’re pretty far afield at this point I think.
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?
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.
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.
I just watched this entire interview with Anne Schuchat, Principal Deputy Director of the CDC.
It’s well worth the time to watch (1.25 x or faster helps), especially those who are inclined to take a dim view of the science. Just watch it and then tell me where the bias is, where the unprofessionalism is, where the politics is.
Anne is not a scientist, per se, but is clearly neck deep in all the medical science going on and the science that is driving what CDC is trying to do…. So tell me where the bad science is.
I’m sure some won’t find it persuasive, but it’s a good example of why I see these people as professionals who are working hard to help people… Not to achieve political goals.
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.
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.
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