You’re probably not going to read this. It’s long. It’s technical. People just don’t want to read long, technical material any more. There aren’t going to be any pretty pictures, and there will be a minimum of snark. What’s more, this is one of those posts that is going to upset a lot of people, both liberal and conservative alike. It’s also one of those that will likely cause the immediate reaction to be flat, bald-faced dismissal and angry rejection.
So why write it?
I write it for a couple of reasons. First, when it comes to rational debate on these subjects I see very few. If I want to throw my voice into the wind, I’m going to try to make sure it’s one of the reasonable, rational ones.
Second, I think that the bulk of people who wonder about controversial topics such as these actually do want to understand how to process facts and data. I think they don’t know how to evaluate evidence, and are stuck in a loop where the most intellectual arguments are “a whole bunch of smart people believe X” or, worse, “if you don’t believe X then you are too stupid to justify wasting oxygen.”
So, for this blog post, I’m going to explain why the approach to justifying Anthropogenic Global Warming (AGW) is exactly the same argumentative style as Intelligent Design (ID), and why they’re both wrong.
Insight into My Background (i.e., Disclosure Statement)
In case you’ve never read anything I’ve written – especially any of my academic works – I was trained as a social scientist. My research methodology and statistics background comes from several years of study under many of the people who – literally – wrote the books on the subject. I have background in both qualitative and quantitative research methodologies, and everything I write here derives from that work and experience.
I do not have a background in climatology. I make no claim to interpretation of data sets, nor would I be able to extrapolate the survey research in any meaningful or definitive way. Fortunately, it’s a damn good thing that I’m not trying to do that.
What I do know, and am trying to emphasize here, is the concept of method. The Scientific Method, as a matter of fact, which has rules that must be adhered to in order for something to be considered scientific.
What Makes Something Scientific?
Generally speaking, there are a few criteria for determining whether you’re taking the right approach. I’m not going to bore you with a thorough primer in Research Methods, but there are a couple of things here that are worth mentioning.
Obviously, any type of research examination has to be clear in scope, it has to be testable, and it has to be measurable. This doesn’t necessarily mean everything is turned into numbers, of course, but oftentimes it is. There is one additional criteria for ensuring that your approach is scientific. It may be counter-intuitive to the layperson, but is non-negotiable.
Any Hypothesis you can imagine about the way the world works has to be Falsifiable.
What does this mean? It means that, in essence, you start off with the assumption that you are wrong.
No, seriously. The upshot of this is that you begin with the assumption that no matter how perfect you think your idea is, no matter how wonderfully thought out, beautifully constructed, it can be proven false.
What happens if it isn’t? What happens if you test that Hypothesis over and over and over again, and no matter what you do you can’t prove it false?
Then your Hypothesis has graduated. Congratulations, your bouncing baby Hypothesis is now a Theory.
This is why, for example, we say that Evolution is a Theory. It was at one point in time a Hypothesis, but it has been tested for the past 150+ years – perhaps one of the most rigorously tested Hypotheses ever created, by the way – but because ongoing evidence continues to emerge that cannot falsify it (yet) it has been elevated to the status of Theory.
Being a “Theory,” far from the criticism of being a sin of conjecture (see what I did there? “Sin,” get it? Meh.), is actually a really big deal. Gravity is also a Theory, by the way, just to help put it into perspective.
The Null Hypothesis
Why did I spend that much time talking about Falsifiability? Because there has to be a way to make sure that we make our best ideas falsifiable. So, for this blog we have two hypotheses available for comparison, one for Intelligent Design (ID), and one for Global Warming (actually called Anthropogenic Global Warming, or AGW for short).
For ID, the Hypothesis is that The Universe came into being by an Intelligent Designer.
For AGW, the Hypothesis is that Global Warming is caused by Man.
These are ideas that someone came up with to describe the way the universe worked, or the way the world worked. (At this point we are trying to keep as much emotion out of this as possible. Each of these ideas is full of emotionally laden terms that need to be unpacked, but we’re not quite ready to do that yet.)
Now, these are nifty ideas for testing, and they should be tested. Remember, however, that in order for them to be considered scientifically valuable tests, they have to be falsifiable. That is, we have to assume that we’re wrong.
Enter the Null Hypothesis.
The Null Hypothesis (so-called because it’s our default hypothesis, often shortened to “H0”), is the opposite of whatever our idea is. This is important because if we are correct in our idea, if we can test that idea and show that it has merit, we can reject the Null Hypothesis.
This is very important!
Warning: This part gets confusing for a lot of people.
When you have an idea, even a very good one, you never, ever say that you have “proven” that you’re right. You don’t say that you proved your Hypothesis. You could have gotten lucky. You could have accidentally triggered something else at the same time and just thought you succeeded. You could have made a mistake in your calculations (this happens a lot!). Or, and this is actually something that happens most of the time, you found exactly what it was that you wanted to find, and bent over backwards to make sure that you got the results that you wanted.
Conversely, if you’re wrong, you don’t say that you proved the Null Hypothesis, either.
All you can say is that you either reject your hypothesis (e.g., you were wrong), or you failed to reject the Null Hypothesis, which means that you couldn’t show that the opposite of your idea was wrong.
An example may be useful here. Say you want to understand whether beating schoolchildren who get wrong answers on tests will help improve test scores (not your schoolchildren, obviously! Someone else’s schoolchildren). Your Hypothesis (called H1, in the nomenclature) is this:
H1: Beating children for getting wrong answers will improve subsequent test scores.
This means that our Null Hypothesis is this:
H0: Beating children for getting wrong answers will result in no change in test scores.
You do your study (I’ll leave that visual up to you, dear reader), and find out that test scores did, in fact, improve. Assuming the validity and reliability of your testing methods, your results, then, would state that you would reject H0 because the children were beaten and subsequent test scores did improve.
So, you accept your Hypothesis, right? No. We don’t know for sure that beating children was the sole reason for the improvement. There could have been some other factor (perhaps the material difficulty changed between tests, for example) that wasn’t part of the test that could have provided the same results.
Nevertheless, the schoolchildren were beaten, and test scores improved. Because there appears to be some connection, we cannot say that we are necessarily wrong in our Hypothesis (H1). In that case, we say that we fail to reject the Hypothesis (H1).
Why do we say that? Because we’re trying to falsify the idea. In the course of scientifically researching the subject, we want to reject it in order to be scientific. That is to say, there has to be some chance that our experiment will fail, otherwise we can’t say that we’re doing honest Science.
Let’s put this into simpler terms. If our experiment failed, we could reject our Hypothesis (H1). If our experiment did not appear to fail, we can’t say that we’ve “proven” our idea because of all the reasons already outlined. So, that means we have more testing to do. The more testing we do, the more the idea holds on, the more credibility it gains.
Let’s look at the experiment again. In order to find out if there is some actual difference between beatings versus non-beatings, you have to have a group of schoolchildren who are not beaten. This is called the control group.
What happens if the children who are not beaten also have their scores improve? What then? Well, we can’t reject that Hypothesis either! In other words, something happened that confirmed both Hypotheses, which means that there was a flaw in our assumptions, our methods, our measurement, our control, or a combination of all of these things (and more). So, you fail to reject your H1, and you fail to reject your H0. Back to the drawing board.
But remember, as soon as you do a test that rejects the hypothesis, it’s rejected. It’s done.
In many Research Methods textbooks a much more simplistic example is given. Think about a man put on trial for murder. Because the American legal system (ostensibly) works under the philosophy that it is better to let a guilty man go free than imprison an innocent one, the burden of proof is on the prosecution to show beyond a reasonable doubt that the man is guilty.
The temptation, however, is for many people to think that “not guilty” is equivalent to “innocent.” In their heads, they put together this dichotomy of hypotheses:
H1: The defendant is found guilty
H0: The defendant is found innocent
This is a false dichotomy. While the words are antonyms, the concepts are not binary. A man needs to be shown beyond a reasonable doubt that he is guilty. If the prosecution cannot do this, the man needs to be released.
This does not mean that he is innocent. It simply means that the prosecution could not accomplish via the evidence that H1 can be supported. Had the prosecution had better evidence, or made a more convincing argument, it is possible that the man could have been found guilty (assuming he actually did the crime).
Because we place people in jail because they are found guilty, not because they are “not found innocent,” the Hypotheses are better written like this:
H1. The defendant is found guilty
H0. The defendant is found not guilty
In other words – and this is very important for what I’m talking about here – the default assumption, H0, needs to be outright rejected in order for us to conclude that we can put the defendant in jail (or worse).
If we can show that there is reasonable doubt that H1 is untrue, or show that there is reasonable doubt that H0 is true, we must fail to reject the Null (Default) Hypothesis (H0), and the defendant must be released.
Examples for ID and AGW
Let’s return back to our ID and AGW examples and add in the Null Hypotheses:
ID-H1 The Universe came into being by an Intelligent Designer.
ID-H0 The Universe came into being by something other than an Intelligent Designer.
AGW-H1 Global Warming, if it exists, is caused by Man.
AGW-H0 Global Warming, if it exists, is caused by something other than Man.
(In both cases I’m drastically oversimplifying what a realistic scientific study would pose as Hypotheses to illustrate the point).
The key thing to remember is that when you are making a claim that A influences B, that is your Hypothesis (H1). the default hypothesis is that there is no influence.
The problem for many people comes in that when B happens, they also see A happening. What we don’t know, though, is 1) whether or not A causes B, B causes A, or neither (A and B may happen completely independent of one another). That’s why we write the default hypothesis the way that we do.
Remember, in both cases here the Null Hypothesis doesn’t have to be proved. We just have to get to a point where we can no longer fail to reject it. Just like our Defendant in Example 2 above, we have to get to a point beyond reasonable doubt that we can reject H0. The burden on the scientist is always to reject his own H1.
With AGW, the problem is that the Hypotheses are written like this:
AGW-H1: AGW causes the Earth’s temperature to increase
AGW-H2: AGW causes the Earth’s temperature to decrease
AGW-H0: There is no H0
If you look at what happens any time during the year that there is more-extreme-than-usual behavior, there seems to be a mad rush to accept either H1 or H2 (H0? We don’t need no stinkin’ H0!). Take a look at Slate’s take on the massive snowfall in up-state New York in late 2014, and you’ll see what I mean. Look at this anti-scientific stance from that article:
Global warming is probably juicing lake-effect snows, and we’ve had the data to prove it for quite some time.
You should see two major problems with this already. First, it’s an outright acceptance of H2, and second, the author – who is a meteorologist – uses the verboten term “prove”. You sir, fail at the scientific method.
Second, take a look at the bizarre circular argument: “(A)GW is probably juicing lake-effect snows,” which is a valid hypothesis, but then he goes on to say that “we’ve had the data to prove it.” Well, if we’ve had the data all this time, why is it only probably affecting the snowfall this time?
(Please note, it’s not just AGW-H1 enthusiasts who do this. There are plenty of H0 proponents who do this all the time and there are no shortage of examples. However, since the burden of rejection/acceptance is on H1, the litmus test is nowhere near as stringent).
For those who may be too young to remember, 1978 was known as a year where massive snowfalls hit the northeast. At the time, all the “scientific experts” agreed that it was due to Global Cooling, not Global Warming. In fact, a lot of the reporting going on right now is a repeat of the scare tactics back then, simply replacing the word “cooling” with “warming.”
The bottom line is that you cannot scientifically have a singular event causing diametrically opposite effects. The moment you do that, you have a tautological finding and thus impossible to be falsifiable. That’s when you fail at the Scientific Method.
The problem with both ID and AGW is, as exemplified above, that in many cases there is no H0 posited, let alone rejected. In both cases, the goal of the scientists is to justify their H1 (or H2!), not falsify it. This, scientifically speaking, is a problem.
In both cases, there is strong evidence for H0. In the case of ID, Quantum Physics, Evolution, and outright contradictory evidence to H1 would long ago have caused the abandonment of the Hypothesis. It would have, of course, if the scientific rigors of methodological criteria had been followed.
Unfortunately, the same can be true for AGW. Climate patterns have been tracked for a very short period of time with any kind of rigorousness – at least from the scale of Earth’s ~4.5 Billion year history. This means that much of the data must be extrapolated from best-case evidence, such as ice cores, tree rings, and other longitudinal data evidence left on Mother Earth for the past millions of millennia.
Projecting out to a future time, however, requires computer modeling – modeling that is not evidence, but rather a best guess of what the researcher thinks that the past history will lead the climate towards in the future.
In this case, too, there is additional evidence that leads credence to H0, including (but not limited to) volcanic eruptions (now there’s interesting new evidence that some of the behavior observed recently may be related to volcanoes), ocean tidal cycles, and solar activity. In addition, the evidence for H1 has been subjected to extremely high skepticism, as the computer models have been erroneously used as evidence. I don’t understand why people aren’t more embarrassed when they make claims like, “100% guarantee that the worst extreme weather, more hurricanes like Charlie, Ivan, Jeanne, and Katrina” never happened. Worse, known quantities of data have been omitted or outright falsified, and strong collusion has been forged between academic organizations, government bodies, and activist organizations.
If you do your own research you will find – as I did – that there are hundreds of opinion papers about each of these sub-topics of AGW. Each have evidence to show. Many devolve into ad hominem attacks (you can guess which ones were worse). The fact that there is still extreme controversy about each of these different elements, not to mention whether there is warming in the first place (i.e., there has been no evidence of actual warming in the past 18 years), shows that – from a scientific point of view – all of the dire models used to predict global temperatures have been wrong. Since those models derive from assumptions, the likelihood is that the assumptions were wrong.
Just like the Catholic Church did not want to lose the money it was making on Indulgences during Gallileo’s time, AGW is big money, big control, and big stakes.
In both cases, ID and AGW have failed to reject the Null Hypotheses. They may have also failed to reject H1, too, just like in our “schoolchildren” example above. But too many times researchers will examine only H1, and think that just because they can’t reject H1 (or worse, they “accept” it), there was no need to consider H0 at all or even test for it.
That’s bad science.
The Tinkerbell Arguments
You can see this by the demonization of those who are a stickler for the scientific method by those who have something to gain by H1 being “proven.”
Most people do not understand the scientific method and need to appeal to some measure of authority. In some cases it’s a straight-up appeal to some fictional consensus percentage:
“97% of all scientists believe in Global Warming.”
In fact, it’s not just made up, it’s deliberately misleading. The number comes from a survey of AGW articles that looked at climate abstracts, not scientists (many of whom write prolifically about their favorite topic – AGW – and so are double- and triple- or more-counted). Moreover, the “97%” was of a smaller subset (less than 1/3rd) of the total number of abstracts examined.
It is unclear whether or not those 97% of the 32.6% even had a H0.
As it turns out, the number is highly inflated. It appears that the researchers may have self-selected (as opposed to a random sample) their studies. There are far more credible scientists who dissent than you are led to believe. [Update 2016.12.14: here is a very good summary of where the “97%” myth originated.]
Even so, if Science were mandated by some percentage of people believing in something, there might be some point to the argument. However, simply believing something to be true does not make it true.
I call this the Tinkerbell argument for AGW. The ID crowd has something similar, though even less sophisticated:
“Intelligent Design, in some form, has been around for thousands of years – all those people can’t be wrong!”
“Look at X Scientist. He believed in ID, so if a smart person like that believes in ID it must be true.”
In both cases the arguments stray too far from the original Scientific purpose. Any truly intellectually honest scientific conversation would not have to resort to ad hominem attacks or appeals to some sort of religious scripture – whether it be The Bible or the UN’s IPCC Report on Climate Change.
Take a look at this excerpt from an article on the Creation Museum’s version of the “Scientific” Process:
The research methods (presented as science) behind the Creation Museum’s version of Ebenezer’s story, and every other story it tells, produce results that by definition cannot contradict the literal word of the Bible. Snelling described it to me as checking his discoveries against a “historical record,” based on the assumption that “God was there” when the dinosaurs roamed the Earth, and the the Bible is God’s literal account — transmitted through humans of “good character” — of what actually happened. As Creationist scientists like Snelling find more and more bits of evidence that “verify” what they already know to be true from the Bible, it reinforces the community’s own confidence in that theory. And, it seems, their work will always eventually verify what the Bible says. Although Snelling presents his work as science, he describes his methods as an inversion of how the scientific community works: scientists, he says, “use the present to inform our understanding of the past.” He, instead “uses the past to inform his understanding of the present.”
To wit, when I asked Snelling if he’s ever, in his entire career, encountered scientific evidence that contradicts the literal word of the Bible, Snelling said, “No.” He added: “but I’ve certainly at times had evidence, and I’m still working through evidence, that at first blush might seem problematical.”
Now, examine that paragraph within the perspective of AGW. If you have a belief in AGW that can cause both Global Warming and Global Cooling, with periods of extreme weather patterns and “normal” weather patterns, will you ever “encounter scientific evidence that contradicts the literal word of [AGW]?” No, of course not. You’ll “certainly at times have evidence, and you’ll still work through the evidence, that at first blush might seem problematical.”
To them, of course, this is a mere inconvenience, not a means to reject the Hypothesis.
Death Threats to Disbelievers
One of the most telling (and scary) moments in any debate is when the threat of violence becomes the main tool of persuasion.
It’s hard for me to say this, but in this case the religious fanatics ain’t got nuttin’ on the AGW folks. Those people are crazy.
Oh, and let’s not forget this little doozy:
Any rational scientific argument should never rely on the threat of force or physical violence. Either your idea has merit, or it doesn’t. Can you imagine a religious totalitarian state legislating that if you don’t believe in their branch of religion that you should be killed – maybe even by beheading? Think I’m joking? Think again.
Yes, just imagine if that were to come to pass somewhere in the world….
In any case, the reason why I say that AGW proponents and ID proponents use the same arguments can be exemplified by how they answer the same question:
What would it take for you to reject H1?
If you ask the question to Evolution, there are quite rational and reasonable answers that you will be provided. Biologist J.B.S. Haldane once famously answered the question as it pertained to evolution that “fossil rabbits in the Precambrian” would convince him to reject H1.
However, if you ask the proponents of ID, you will often get a very dogmatic answer: “Nothing!” The reason being, of course, that their basis is not scientific at all, because their source of evidence comes from the Bible and only the Bible. If the Bible is unassailable in their eyes, then it would be impossible for them to reject any logical fallacy that derives from that source.
Amazingly, AGW proponents take the exact same stance as ID proponents. In fact, they take H1 as H0 – accept their Hypotheses as the default – which is a colossal flaw in any scientific research.
I have just one question for those who would argue such tactics: If you are so confident in the integrity of your science, why do you feel the need to silence those who ask questions about it? Why do you not want scientists asking about H0?
Let us return to the scientific evidence, though. Both the ID crowd and the AGW proponents move far beyond the personal attacks to the point where we are removed from the realm of scientific method altogether.
Take one of the links I inserted above, where Reddit banned climate deniers. The author, Nathan Allan – a chemist – laments the fact that climate change ‘deniers’ (a pejorative term) don’t even deserve the moniker “skeptics,’ because they cannot form coherent or consistent arguments. Then, as evidence, he links to the same article about Climate abstracts and promotes the ‘97% of all Scientists’ number.
Pot, meet kettle.
Without irony or a sense of self-awareness, that same professor dismisses ‘deniers’ as rejecting H1 based upon political preference and personality.
Thing is, Nathan Allan is a false authority. That is, he is making the ‘fallacious argument from false authority’ and using himself as the authority. While he has a Ph.D (as do I) he does not have one in Climate Science (nor do I), and as a result he cannot therefore use his Ph.D as a foundation for his judgment on Climate Science (nor can I). The best he can do is comment as an ‘informed amateur’ (as can I).
Dr. Allan – as a chemist, not as a climatologist (and therefore cannot count himself among the ‘97%’) – evidently accepted H1, which undermines his credibility just as much as Ken Hamm, who accepted ID-H1, and recently debated Bill Nye on the merits of Intelligent Design.
Ah, Bill Nye. As much as I like the man and respect his work (and he, too, is a Swing Dancer, so there’s something else we have in common), he too is someone who has grotesquely accepted AGW-H1 even as he criticizes Ken Hamm and his flock for doing the same with ID.
The debate between Bill and Ken is notable because it is an allegory for not only the frustrations in dealing with those who don’t understand that they are supposed to work to falsify H1, but also how he himself fails to see that he, too, has fallen subject to the same methodological flaws with AGW.
Both Ken and Bill subscribe to the Appeal to Authority in order to ‘prove’ their points. Ken does so by repeatedly showing clips of other “smart scientists who believe in Intelligent Design” as well as quips about how the Bible has provided all the evidence he needs.
Bill is obviously frustrated by this in the debate, which makes it all the more poignant when he makes the exact same argument about AGW. Both Ken and Bill lament (and Dr. Allan, too) how “there has never been any evidence by credible people to show that [H1] shouldn’t be accepted.”
This is easy to do when you demean and belittle those who question your findings. Dr. Allan dismisses them as “non-scientist” rabble-rousers; Bill Nye pretty much does the same. Ken Hamm preaches to the choir about how only those who already have accepted H1 can come to truly understand H1.
Before you get after me about Bill Nye and being your childhood inspiration, you should probably be aware that he is one of the loudest voices for criminalizing those who fail to reject H0.
In other words, you need to Accept H1 before they will consider talking to you about the merits of H1. This, by the way, is why I believe 97% of those abstracts that hold an opinion on AGW, hold it already accepting H1 before they begin. You never have to reject or fail-to-reject H0 if you never have a H0 to begin with.
The “Go-To” Answer
Both ID and AGW have an expediency problem. That is, their preferred H1 is the immediate answer for everything and anything that happens in life. Any time a natural event happens, you know that they’ve already accepted H1 before ever looking at any evidence.
First, here’s the ID-H1 go-to answer (well, this goes beyond “ID” but you get the point):
But look at what we have for AGW, too:
Johns Hopkins research proves El Niño causes stunted growth (spoiler: no, it doesn’t)
You know what? I’m going to stop right here. Things just get more and more bizarre as time goes on, and the “complete” list just gets longer.
Why isn’t there anyone, and I mean anyone, who is pro-AGW come forward and explain how and why some of these pieces of conjecture have nothing to do with AGW? Why don’t they simply explain that “this is not how the mechanics of AGW work”?
Could it be that it’s because nobody actually knows the mechanics of AGW? Think about it for a second: every single model of AGW has failed to produce even one accurate claim over time. Worse, when those models are used not to explain the mechanics, but rather as evidence of AGW, the methodology is broken.
In other words, there is significant cause to fail-to-reject H0. Because of this, all of these claims about AGW “causing” specific, one-off events, is highly speculative.
Ultimately, the Scientific Method is used precisely to avoid these problems. Science should never be legislated, and it is not a popularity contest. If it was, we would never have emerged beyond Geocentric models of the Universe, Galileo would never have been arrested, nor would we have come to understand Evolution as well as we do. Neither of those concepts were the status quo when they were introduced.
Nor can we substitute “smart people” for scientific rigor. As we’ve seen, Bill Nye is a smart guy, but even he can succumb to the same methodological traps as his opponents. Sir Isaac Newton was an incredibly brilliant guy, but also believed that alchemy was going to allow him to transmute metals into stone. He also believed that if he could just figure out the dimensions of the Temple of Solomon, he’d be able to predict the end of the world.
Intelligence is not the sole determining factor of whether or not an idea is right or wrong. Intelligence is like a very, very powerful motor, but Method is like your GPS. Using Intelligence without proper Method will drive you to a wrong destination just as fast as a right one. In fact, in many cases it will drive you there faster.
Denier, Skeptic, or Scientist
Personally, I don’t see myself as a denier or a skeptic. I see myself as a scientist who tries to use the Scientific Method to come to the conclusion. In my own research I have come to see the flaws in the testing methods for AGW-H1, and have seen considerable evidence to not reject AGW-H0. Not yet, anyway.
Among the questions that I have that prevent me from rejecting H0:
Why are local climatological events characterized as AGW, when they fall squarely in the median of natural phenomena?
Why is that far too many computer models and prediction of climate outcomes go uncomfirmed? How is this not evidence for failing to reject H0? It’s intuitively obvious that some AGW proponents treat computer models that fit their viewpoint as if those models were observational facts.
How can a cohesive theory of AGW not be tautological? What would it look like?
Why do people continue to fabricate consensus numbers, when science is not predicated on “how many people believe” something? (By the way, that same number – 97% – is used to describe the number of biological scientists who are Atheists, so how should we interpret belief systems-as-evidence?)
What exactly is the danger of CO2? With the bizarre push to ban/regulate bovine flatulence and get rid of dogs, both of which have been around for thousands of years, haven’t we lost all sense of perspective about the gas?
Why, if AGW is ‘real,’ and the data is sound, do proponents feel a need to imprison, kill, persecute, prosecute, or otherwise silence those who question? After all, if they have good science on their side, why is force and violence necessary?
The danger is more than just leaving it to an academic exercise, however. We’ve seen what happens when emotions run away with us and we let them take over rational thought.
We’ve seen it with the DDT ban, which has resulted in millions of deaths of the poor in third world countries.
We’ve seen it in the catastrophic interference in environmental policies that have radically and irrevocably damaged the wildlife ecosystem. (About halfway down, do a search for “Yellowstone.”)
We’ve seen it in the waste of billions of dollars in political cronyism – and that’s just in the United States.
There is a lot of complaint about where the money comes from to sponsor the research – complaints which I think can be valid if the research methodology is shown to be unsound, biased, or deliberately flawed. True peer-reviewed research is supposed to be open and transparent about not only the methodologies but also the sponsorship.
All too often, however, we begin with the assumption that if research is sponsored, then the objectivity is automatically lost. Such knee-jerk reactionism is anti-scientific, and should be rejected on its face by anyone who rushes to that conclusion at the onset. This should be done by everyone. The fact that research is sponsored does not in and of itself reveal anything about the study. This is true for all research (because all research is sponsored at some level, in some capacity).
Good research identifies:
- Question to be addressed
- Operational Definitions (e.g., “We’re going to be using term X to mean this.”)
- Known Biases, and how the study attempts to mitigate them
This is why the “97%” number is so troublesome. Scientific methodology mandates that you never accept H1, but evidently 97% of those articles who identified a stance on AGW did so. That’s how we know!
What this means is that of all the abstracts studied, a third of them accepted a hypothesis, whether it be H0 or H1. It just so happens that 97% of those who did this bad thing were pro-AGW!
You should not be throwing around a number like that when it means that’s the percentage of scientists who didn’t do their job right.
Obviously I cannot accept H1 because I have failed to reject H0 – for both ID and AGW. More specifically, proponents of AGW have failed to convince me that they failed to reject H0.
If someone wants to haul my ass in front of the Hague, or that I should be killed because I stick to these scientific principles, then I think it says more about who is a religious zealot than who is a ‘denier.’