Monday, May 10, 2010

When Listening to Scientists, Be Sure to Check Their Shoes

During college, I worked on and off as an intern at IBM Boulder. I remember when I changed departments, to work on management software for the facilities group (whose job it was to keep track of the walls and such - seriously, not as simple as you'd think). One of the senior guys named Tom took me out for my inaugural trip to the coffee machine. Back then we didn't have nice coffee set-ups like many companies do now, just a machine that gave you little paper cup of battery acid for a quarter. As we approached, there were some people ahead of us a the machine, including one of the managers I had just met. "You're gonna owe me a coffee," said Tom.

"Uh, okay," I said, thinking it was some new guy tradition to buy coffee. "Why?"

"See that guy?" asked Tom, indicating the manager.

"Sure, " I replied.

"Check his shoes."

I dutifully looked at the shoes. Seeing nothing out of the ordinary, I asked "What about his shoes?"

"They're full of shit."

I bought the coffee.

When you're getting information from scientists or other "experts", there are some good signs that indicate when a shoe check might be needed (to see what they're full of). One of the best is when scientists argue for/against a particular hypothesis by lecturing about the scientific method, rather than actual evidence. Usually this is a bitch-fest about how opponents of their views are unscientific self-interested boobs, while casting themselves like Gandalf on the Bridge of Khazad-dûm (paraphrasing a bit):

You cannot pass! I am a servant of the Secret Fire, wielder of the Flame of Science. The dark fire will not avail you, Flame of Dumb-Dumb! Go back to the shadow. You shall not pass!


Riiiiiight.

(Of course, since I spend a good chunk of this blog lecturing about scientific method, maybe I should check my own shoes :-)

I recently came across a couple of excellent examples of exactly this phenomenon, and thought we'd all benefit (and maybe get a good laugh) from checking the shoes of those involved. The first is T. Colin Campbell's "review" of the latest Atkins diet book. I haven't read the book, and am no particular fan of Atkins over any other diet, beyond the fact that it applies well-understood metabolic principles to achieve predictable results. And I won't spend time dissecting Campbell's review. He doesn't say anything that amounts to much beyond the Gandalf quote above (I can't shake this mental image of Campbell on the bridge, wielding a carrot and handful of wheat against a cow with a platter of bacon on its back). Jimmy Moore already did a great job of chewing up Campbell's argument, so I'll direct you there and to the links within (definitely see also Chris Masterjohn's review of "The China Study", and Campbell's unintentionally humorous reply). I just find it funny that Campbell is lecturing anybody about the scientific method, when he seems to apply it selectively, if it all. For instance, see his discussion about his personal "scientific philosophy" and "holistic" approach in The Protein Debate. I think it's pretty clear that Campbell is a conditional fan of the "scientific method," as long as it leads you to conclusions that agree with his own.

BTW, if you haven't read The Protein Debate, you should. For a long time you had to pay for access, but now it seems to be available for free. Loren Cordain provides a review of a lot of interesting evidence ranging from archaeological to biological, along with tons of references. Cordain has his own axe to grind, of course, so don't be fooled into thinking he's giving the whole picture. But he certainly provides a lot more background (164 references) than Campbell (0 references). Funny that Campbell complained in his Amazon review that Atkins never published a peer-reviewed paper and lectured on the requirement of peer review in "real" science (shoe check), yet neglects to reference said when arguing his own position. Read Campbell's part in the debate for lots of "check his shoes" examples. Plus it's great fun to see Campbell get handed his own ass - on a platter, with a side of bacon.

The second example is a letter to Science Magazine, entitled "Climate Change and the Integrity of Science". According to the guardian.co.uk,

A group of 255 of the world's top scientists today wrote an open letter aimed at restoring public faith in the integrity of climate science.

In a strongly worded condemnation of the recent escalation of political assaults on climatologists, the letter, published in the US Journal Science and signed by 11 Nobel laureates, attacks critics driven by "special interests or dogma" and "McCarthy-like" threats against researchers. It also attempts to set the record straight on the process of rigorous scientific research.



Wow, 255 scientists including 11 Nobel laureates? That's a lot of shoes to check. And we'll have to check those of Nobel winners twice.

The letter actually gets off to a good start:

We are deeply disturbed by the recent escalation of political assaults on scientists in general and on climate scientists in particular. All citizens should understand some basic scientific facts. There is always some uncertainty associated with scientific conclusions; science never absolutely proves anything. When someone says that society should wait until scientists are absolutely certain before taking any action, it is the same as saying society should never take action. For a problem as potentially catastrophic as climate change, taking no action poses a dangerous risk for our planet.


Clearly you cannot wait until uncertainties are resolved before making choices about how to deal with the possible outcomes of those uncertainties. And in theory, science is all about performing inference in the face of uncertainty, understanding how incomplete information about the world informs beliefs about competing hypotheses. Alas, the letter ruins this excellent start by espousing the opposite course, demanding that we should agree with their "facts":

Scientific conclusions derive from an understanding of basic laws supported by laboratory experiments, observations of nature, and mathematical and computer modeling. Like all human beings, scientists make mistakes, but the scientific process is designed to find and correct them. This process is inherently adversarial—scientists build reputations and gain recognition not only for supporting conventional wisdom, but even more so for demonstrating that the scientific consensus is wrong and that there is a better explanation. That's what Galileo, Pasteur, Darwin, and Einstein did. But when some conclusions have been thoroughly and deeply tested, questioned, and examined, they gain the status of "well-established theories" and are often spoken of as "facts."

For instance, there is compelling scientific evidence that our planet is about 4.5 billion years old (the theory of the origin of Earth), that our universe was born from a single event about 14 billion years ago (the Big Bang theory), and that today's organisms evolved from ones living in the past (the theory of evolution). Even as these are overwhelmingly accepted by the scientific community, fame still awaits anyone who could show these theories to be wrong. Climate change now falls into this category: There is compelling, comprehensive, and consistent objective evidence that humans are changing the climate in ways that threaten our societies and the ecosystems on which we depend.


Oh brother, how much self-aggrandizing hyperbole can you pack into two paragraphs? Right off we get the lecture on the scientific method. The authors compare themselves to Galileo, Pasteur, Darwin, and Einstein (such name-dropping is another indication a shoe-check is required). The comparison with other "well-established" theories also needs some examination in comparison with the anthropogenic global warming (AGW) hypothesis:
  • The Big Bang (or whatever process created the Universe), formation of the Earth, and evolution have all occurred already. For that matter, so has significant climate change on Earth, without help from human beings. What we don't have is a way of testing specific predictions about the behavior of a very complex nonlinear system, namely that human behavior is the driving force behind the recently observed global temperature variations, and that changes in human behavior can alter the course of future climate change. Big difference.
  • The Big Bang, while "well-established" in the minds of physicists, is really only well-established in a semi-dogmatic sense. There are fairly major holes in the theory, in terms of predictive power. The current hypothesis required for getting from a Big Bang event to the Universe observed today ("inflation") has no evidential support - at all. It may be the best hypothesis we have at this point, but there's plenty of room for it to be supplanted by new information (and it wouldn't require much). The example is the most appropriate one for comparison to the AGW hypothesis, though for reasons opposite what the authors intended.
  • Estimates of the age of the Earth leverage some other very basic "facts", amongst them that statistical behaviors of radioactive elements are observed to be the same every time we look. The nucleus of an atom on the Earth largely can be treated as an isolated system: it doesn't have a whole lot of complex interactions with the environment, in particular there really aren't any nonlinear feedback loops or other dynamical behavior to consider when doing radioactive dating. Inference of the age of the Earth can then be performed with some accuracy, as the relevant "givens" and observations don't admit much uncertainty. By contrast, global climate has many MANY interacting variables, most of which we probably don't even know about yet, and considerable uncertainty underlying the ones we do know about. It is difficult to see how any specific prediction of the future dynamic behavior of global climate could be as accurate as that for the past behavior of radioactive elements that have been sitting around in a rock for billions of years.
  • Evolution is about as close to a "fact" as you're going to get. First of all, it effectively follows from a combination of the "laws" of thermodynamics (mainly the first and second) and the ability of a system (whether it is a molecule or a complex organism) to a) maintain a relative narrow set of states against environmental fluctuations, and b) reproduce itself at a rate greater than it's destruction. Evolution is just math, in the end. And of course, it is observed repeatedly in the laboratory and Nature. There may be many specific models that predict different evolutionary endpoints, or routes by which currently observed endpoints were achieved. But the fundamental phenomenon, that mutable self-reproducing systems will evolve, applies to all of these models, and all predictions are necessarily consistent with this "meta-behavior". By contrast, global climate is an instance of a specific system, which we model given what (very little) we know about the intertwined physical, chemical, and biological systems on the Earth, and continued warming is a specific prediction of that model. As climate is a system showing chaotic behavior across many timescales, it may be fundamentally unpredictable, for all practical purposes. So calling this prediction a "fact" is stretching thin even the approximate definition of "fact" made by the authors.
The letter goes on to state a variety of "facts" or "conclusions" which the authors imply are more or less incontrovertible, which would seem to contradict their initial points about uncertainty and the scientific method. I think the key problem here (and in most science) is the idea that there is any "conclusion" in science. The only real conclusion is the relative belief in one hypothesis over competing hypotheses, as opposed to a specific identification of "truth". But standard statistics is completely backwards on this point, instead testing if observed data are likely given that a hypothesis is true. It's not the likelihood of the hypothesis being tested, but that of the data. The truth of the hypothesis is assumed in this analysis. So when a scientist finds that their data is strongly consistent with the observations, they "conclude" the hypothesis is a "fact". But that ignores both any prior information (similar to "black box" diet studies which don't include knowledge of metabolism in assessing outcomes) as well as competing hypotheses. Your pet hypothesis might be consistent with the data at the 99% level, but if mine is 99.9% consistent, and further more consistent with other prior information, then it is more likely to be true. By not quantitatively assessing competing hypotheses, the authors of the letter are guilty of exactly the sort of "hiding heads in the sand" behavior of which they accuse their detractors:

We also call for an end to McCarthy-like threats of criminal prosecution against our colleagues based on innuendo and guilt by association, the harassment of scientists by politicians seeking distractions to avoid taking action, and the outright lies being spread about them. Society has two choices: We can ignore the science and hide our heads in the sand and hope we are lucky, or we can act in the public interest to reduce the threat of global climate change quickly and substantively. The good news is that smart and effective actions are possible. But delay must not be an option.


I think everybody involved here is "ignoring the science" in one way or another. Threats of criminal prosecution is the sort of idiot knee-jerk response made by politicians, who, incapable of thinking for themselves, blindly follow the "expert du jour". When it turns out the politician made stupid and shortsighted decisions based on "expert" advice, they want to turn on the expert rather than accepting responsibility for acting like an idiot. Physician, heal thyself!

But the authors of this letter are no better. AGW proponents seem to ignore the elephant in the living room: the climate is probably going to change at some point whether or not human activity has anything to do with it. If anything is going to doom humanity, it is our anthropocentric view, that we are the masters of the Earth, able to bend Nature to our will. History shows that environmental conditions are large unstable, requiring organisms to adapt or die. We clearly should not ignore the possibility of climate change and the effects it will have on human life. But should we focus our resources on trying to force Nature to behave as we wish (and probably failing over the long term)? Or is it better to learn from history, assume that change is coming, and figure out how we will adapt to Nature's whims? I'm guessing the personal goals of the "scientists" aligns strongly with one of these scenarios, not so much the other.

And that's the real issue with both examples: the gap between the personal goals of those providing information and the goals of the receivers of that information. I've discussed this before, more in the context of organizations like pharmaceutical companies. But scientists are just as self-interested as any other organism or organization. The personal goals of academic scientists are centered around career advancement and getting funding for research. For both, you need to make some scientific hypothesis and be "right" about it, not necessarily in the sense of having actual evidence quantitatively weighting the hypothesis, but in getting some large chunk of the scientific community to buy in. Achieving said buy-in is the core goal of academic scientists, and whether or not "consensus" is obtained through actual evidence isn't really relevant to the practitioners. They generally think that the consensus so obtained is itself evidence that they're right, but there's circular reasoning and confirmation bias written all over that. When you are evaluating the evidence put forth by a scientist, you not only must evaluate the quality of that evidence, but also the context in which it is presented, because the presenter undoubtedly (and probably unconsciously) re-weights things based on their own beliefs and goals. The scientist has a vested interest in being considered "right", which can be a lot different than actually being "right". The stronger those beliefs and goals relative to the actual evidence, the more likely you'll hear about "facts" and the "scientific method" as opposed to detailed evidence, both supportive and contradictory.

So when a scientist speaks, be sure to check the shoes.

23 comments:

Pål Jåbekk said...

Great to see you back in the blogosphere Dave, and a great post. Your writing about evolution made me think about how religion historically speaking has had a free card for criticism. Speaking out about religion has always been risky business. Now it seems much the same is happening with climate change. Being skeptical and speaking out about the human contribution to the current climate change can get you lynched just as much as accepting evolution could some years ago.

Dave said...

@Pal,

Thank you. The writing seems to come in bursts like this, not sure why.

Anything that people hold as absolute "truth" is going to cause the sort of phenomenon you describe. If it's a broadly held "truth", then being on the wrong side of it is a good way to get lynched, burned at the stake, denied research funding, etc. It's really the norm, and I think once people realize that, they will truly understand the need to think for themselves, and stop blindly following experts/priests/etc.

e4e said...

I love this part.

"The only real conclusion is the relative belief in one hypothesis over competing hypotheses, as opposed to a specific identification of "truth". But standard statistics is completely backwards on this point, instead testing if observed data are likely given that a hypothesis is true. It's not the likelihood of the hypothesis being tested, but that of the data. The truth of the hypothesis is assumed in this analysis."

That is a really cool way of thinking about it. Thanks.

Tony

LeonRover said...

For my money the equivalent of "checking the shoes" is the presence of the weasel word "might".

In my mental universe "might" ALWAYS includes OR "might not" by implication. Whatever view one is being asked to endorse, it is on the basis of a judgment or opinion provided by an expert.

For example, in an entirely different field, that of a murder trial in England of a mother for the deaths of her three children from SIDS, the expert paediatric witness Sir Roy Meadows was severely criticized.
http://www.guardian.co.uk/news/2005/jun/20/childprotection.

My other "bete noir" is the "precautionary principle", by which we must act, because the outcome might be as the proposers theory suggests.ineaking

Dave said...

@Tony,

Thanks.

@LeonRover,

Why is "might" a weasel word? And who decides that "experts" are indeed expert? Usually, it's other "experts", i.e. birds of a feather flocking together.

Not sure what you were getting at in the last paragraph, looks like it got garbled.

Walter said...

If I understand what Gary Taubes has said about science the presence of weasel words is a good thing - defining the limits and conditions under which something is true for instance.

LeonRover said...

Hello Dave

I use weasel to describe a word which describes a possible causation without also saying that it is speculative and there is a lot of investigation needed to produce a mechanism of explanation.

Might and may are thus weasel words for me.

Sorry about garbage in edits!

The "precautionary principle" when coupled with "might" grounded airline travel in Europe recently because non-zero levels of volcanic ash "might" damage jet engines.

Thank you for blog.

Dave said...

@LeonRover,

Yeah, I see what you're getting at. Your volcanic ash example shows the limitations of language. "Might" includes the entire range of possibilities between 0% and 100%, but says nothing about the degree. In the case of grounding the planes, grounding to "err on the side of caution" may or may not have been the right decision.

The thing that is annoying (but not very surprising) is that the mathematical tools exist to change a vague "might" into a number, and further quantify the values of choices given the available information. A decision with any degree of complexity (more than a couple of variables) is well beyond the capability of humans to mentally assess even as a good approximation.

I like to use computer chess as an example (all the better since there's no uncertainty in chess). The chess software on my laptop will defeat the top players in the world something like 4 out of 5 times. The computer is relentlessly rational - it always makes the "right" move (at least within the limits of the chess knowledge given to the software). A top grandmaster makes a suboptimal move about 10% of the time.

I doubt that the people making key decisions, like grounding airplanes, have anywhere near the mental analytic capabilities of a chess grandmaster. So they play CYA, and hide behind the word "might" without actually ever digging in to the details. For them, all "mights" are created equal, which leads to complete stupidity.

Dave said...

Take a look at this paper by Jeff Glassman, and compare to the Science letter by Gleick et al:

http://www.rocketscientistsjournal.com/2010/03/sgw.html

I contacted Dr. Gleick and invited him to respond to my criticisms here. I hope he takes me up on my invitation, and can point us to some evidence of quality similar to Glassman's. To be fair, Dr. Gleick did point out that a short letter to Science cannot possibly cover the complexities of climate science. But that's my complaint: if you can't add information to the discussion, then why are you bothering? And how can one possibly assess the "facts" cited there if no supporting evidence is given, or at least referenced?

Ms. X said...

Natural selection is not evolution. It is merely one suggested (and increasingly dismissed) causal mechanism. Problem is, without solid mechanism it is difficult (or should be) to say a theoretical process like evolution is anything like a fact.

Dave said...

@Ms. X

Please elaborate. Thanks.

Mike said...

Check your shoes too- It is the acceleration of climate change that is the issue= always was. The damage from oil exploration and the faith of the Gulf after BP lack of concern for safety regulations is Climate Change Accelerated. But nothing said will change your mind. Freedom has a darkside- dumbass bloggers for one.

Dave said...

@Mike,

Thank you for your comment. It serves as an excellent example of the level of rational discourse employed by supporters of anthropogenic global warming.

Chris Masterjohn said...

In the statistics texts that I've read, it is the null hypothesis that is assumed "given" for the statistical test, not the research hypothesis. So if you hypothesize that the mean of A is different than the mean of B, your statistical test would be the null hypothesis that there is no difference between A and B. You then ask the question, if the null hypothesis is true, what is the likelihood of obtaining the observed difference in the means of A and B? If the likelihood is more than the proposed level of significance, often 95%, then you fail to reject the null hypothesis and conclude there is no evidence for your research hypothesis. However, if the likelihood is less than 95%, then you reject the null hypothesis, and you consider this support for the tenability of your research hypothesis.

I have never read a standard statistics text that advocates testing the research hypothesis directly or advocates using the rejection of the null hypothesis as proof or definitive confirmation of the research hypothesis.

Chris

Dave said...

@Chris,

"I have never read a standard statistics text that advocates testing the research hypothesis directly or advocates using the rejection of the null hypothesis as proof or definitive confirmation of the research hypothesis."

Agreed. But as with much of standard statistics, scientists are rather poor at confining their conclusions to the limitations of the analysis, probably in no small part because standard statistics doesn't provide the framework for the sort of inferential reasoning you want to do in science.

Chris Masterjohn said...

Hi Dave,

Oh I definitely agree that scientists quite frequently do not confine their interpretations to the limitations of their analysis (or to their study design).

What type of statistical analysis is, in your view, required for scientific inference?

Chris

Dave said...

Hi Chris.

You know, I dislike the term "statistical analysis". It sounds picky, I know, but a "statistic" is really just a number derived from data. There's nothing wrong with statistics per se, they just are what they are, and I think it's important to distinguish between analyses that are data-centric vs. model-centric. Frankly, I think an awful lot of confusion in nutrition and health has its roots here.

Anyway, what we want to do is to quantitatively and transparently assess the plausibility of propositions based on information, e.g. "How much do I believe that saturated fat causes heart disease?" Part of this is obviously related to data, but the meat of the thing is really the model under test. In building models of the real world, we make choices about what include/exclude, postulate cause-effect relationships, etc. Ultimately we need to test the plausibility of this model, and want to update that plausibility as we gather new information.

For instance, I can always come up with a model that fits the data perfectly ("pixies did it"). You can't reject this simply through the likelihood of the null hypothesis, since I can basically make that as small as I like by invoking pixie magic. Other judgments come into play, and these are necessarily subjective (unless you have some data that indicates pixies don't exist). The key is to make this subjectivity transparent and quantifiable, to the greatest extent possible. The recent dust-up with T. Colin Campbell is a nice illustration of the problems that arise when this sort of subjective judgment is locked up in someone's brain, rather than being performed in a manner which is consistent, repeatable, and transparent.

Jaynes' "desiderata" would seem to outline the principles we desire:

1) If a conclusion can be reasoned out in more than one way, then every possible way must lead to the same result.

2) We always take into account all of the evidence relevant to a question. We do not arbitrarily ignore some of the information, basing our conclusions only on what remains. In other words, we must be completely non-ideological.

3) Equivalent states of knowledge are represented by equivalent plausibility assignments. That is, if in two problems our state of knowledge is the same (except perhaps for the labeling of the propositions), then we must assign the same plausibilities in both.

I've numbered these slightly differently than in Jaynes' book. We also want the framework to reflect "common sense", e.g. if the truth of A depends on the truth of B, and we find new information that makes B more plausible, then A should also be more plausible (and "not A" less plausible). Add to this the requirement that we quantify "plausibility" as a real number between 0 and 1, and you have the basis for Probability Theory. The rest of it is just math starting from these basic statements.

Chris Masterjohn said...

Hi Dave,

I definitely agree that fitting the data is insufficient in and of itself for a theory, and that all observations must be taken into account. This sounds like it will be a useful read.

Thanks!
Chris

Elenor said...

"I doubt that the people making key decisions, like grounding airplanes, have anywhere near the mental analytic capabilities of a chess grandmaster. So they play CYA, and hide behind the word "might" without actually ever digging in to the details. For them, all "mights" are created equal, which leads to complete stupidity."

I'm not sure the grounding was an example of CYA so much as an “OMG we never got around to calculating what level of volcanic (invisible) ash will damage planes to the extent of crashing them and killing lots of the public” -- who will raise bloody murder if such engine damage occurs again. (Stampeding the sheep, anyone?)

They did, in fact, DO the calculations AFTER grounding (almost) all of Europe, and determined a level of risk and 'reward' that would allow (some) flights in many circumstances, not in others. (And if Katla blows, it's probably all over for a year of air travel in Europe! But at least that's (probably) provably not anthropogenic!)

Margaretrc said...

I don't know if this comment thread is still open, but I'm going to try. Please help me understand your position on AGW. Are you skeptical that we humans have had anything to do with the current warming trend--that it is nothing more than a warming trend that is part of a natural process? Are you saying there is no point in trying to reverse our contribution--however small or big--to the greenhouse gases in the atmosphere? I am not looking to get into a debate here--I am keeping an open mind and I do trust not only your credentials, but your motives. I just want to learn. I did see an earlier post on sunspots (I think--it was late at night/early in the morning and my brain may have been a bit fuzzy)and Climate change and it certainly makes sense. My husband has pointed out something similar. Can you point me to some unbiased, reliable sources on this topic? We will be going on a "Global Warming" cruise to Alaska with the Skeptic Society in August and I do want to be "checking their shoes" so to speak. Despite their name, they don't seem to have a lot of skepticism re AGW--at least I haven't seen any. Likewise mainstream nutrition info., BTW, which is why I'm prepared to keep an open mind and will"check their shoes". Thanks, and I do enjoy your blog. Keep that information coming! Peggy

Dave said...

@Margaretrc

I think it's a reasonable hypothesis that human activity *might* be having a significant effect on global climate. But there's an awful lot of "know what we don't know" in there, particularly considering that the Earth's climate has been all over the place in the past. I expect if we were to rigorously compare different hypotheses, we would not find one to be heavily favored.

And comparing hypotheses as to the cause of climate change is somewhat academic. It does somewhat inform the hypothesis that humans might be able to effect a reversal, or at least slowing. But what we really need to do is make decisions on where to put resources. Do we continue on the current path and hope for the best? Do we put massive resources into trying to change the direction of climate change? Or do we make hedge our bets, and put some resources into getting ready in case the climate changes significantly regardless of anything people do? The bickering over whether or not "global warming" is anthropogenic or not misses the big picture on both sides.

The Rocket Scientist's Journal I linked earlier in the comments is a great place to start. If nothing else, it shows just how complicated climate is, and how little we really know about it.

Margaretrc said...

Thanks, Dave! You definitely are a Spark of Reason. I am working my way through the article you linked (that's actually what I was thinking of when I mentioned "an earlier post"!)and it is very informative. I am not a physicist--my strong suit is more chemistry, particularly as it relates to biological systems, so it is going to take me a while to get through it. But I will persist. And I'll keep checking back here.

Margaretrc said...

@Ms X, Okay, Biology IS my strong suit (as opposed to physics), so I'm going to jump in on this. First of all, one does not need to agree on a mechanism to accept evolution as a fact. Innumerable fossils show it happened in the past and we can observe it occurring constantly in the present, so we can, indeed, accept evolution as a fact as much as we can accept that the sun is the center of our solar system. Secondly,natural selection is by no means "merely one suggested (and increasingly dismissed) causal mechanism", as you say, except perhaps by creationists and others of their ilk. Scientists may tweak it, as they tend to tweak all theories (and natural selection is a theory, not an hypothesis)as new evidence rolls in, but the basic concept--as outlined by Darwin and further refined by many in the 150+ years since, continues to provide the most plausible mechanism and, as far as I know, no one has yet come up with one that explains the evidence better. Natural Selection is and will continue to be the (one) theory that scientists who work in the field accept as the most likely mechanism--unless and until someone uses it to make a prediction that turns out to be false, and that hasn't happened yet. Richard Dawkins'book, "The Greatest Show on Earth", is a terrific explanation of all the avenues of evidence for evolution and Natural Selection.