Formal Falsify and Replace Analysis of Darwinian Theories

[mabus]

Forest;

Darwin himself was an IDer

My understanding of Darwins theological beliefs is that he was himself an avowed Atheist.

LifeEngingeer;

This theory can be expressed using the mathematical equation F(G,JAx)=ECJAxt. In this equation, G is the goal of survival, JAx is the allele or potential allele Ax of gene J, ECJAxt is the force of error correct operating on JAxt at time t and the function F is ‘select or apply the force of error correction most compatible with the goal of survival’.

Would you please provide an example of this equation being applied in practice to produce a specific and testable prediction which could be falsified? That is after all the benchmark of prediction theories.

I have a hard time figuring out how your equation could possibly produce any reliable predictions as they are subjective and impresive. G for example which represents the goal of survival, how do you quantify that. What number do you give it?

[LifeEngineer]

Quote: Would you please provide an example of this equation being applied in practice to produce a specific and testable prediction which could be falsified? That is after all the benchmark of prediction theories. I have a hard time figuring out how your equation could possibly produce any reliable predictions as they are subjective and impresive. G for example which represents the goal of survival, how do you quantify that. What number do you give it?

A couple of good questions. Before answering the questions, there are three points that should be noted. First, with respect to the test being discussed, the immediate question is whether the theory fits or explains the data in the test being discussed. Second, the accuracy of predictions is evaluated not in absolute terms but relative to the accuracy of competing predictive theories. Third, theory formulation is a process of successive approximation. The ‘theory’ presented here is a rough initial form that can undoubtedly be refined to produce better prediction.

It is, at least in theory, quite easy to quantify the relevant values for the goal of survival. If JAd is the most common allele for gene J then survival value of JAx is calculated in terms of the difference in probability of survival between individuals with the JAd allele and the probability of survival with the JAx allele. In practice lots of technical problems in carrying out such a calculation but the concept is straight forward.

I can think of three types of falsifiable tests for the theory being proposed. The first is relatively simple, the other two are, I believe technically fairly complex. First, the theory asserts that error correction processes are mechanisms to increase the likelihood of survival. Mathematical modeling can be used to show that the probability of a complex species surviving without error correction mechanisms would be extremely low.

Second, we know that the force of error correction varies from gene to gene. Since the theory asserts that error correction is beneficial, it would predict that error correction would be stronger (there are fewer instances of mutations not being eliminated by error correction) where the current allele was essential or where mutations are likely to lead to a significantly lower probability of survival.

Third, the theory would predict that if the survival value of an existing dominant allele is significantly reduced (there is a need for an adaptive change) then the force or efficiency of the error correction mechanism should be reduced.

[mabus]

LifeEngineer;

I must disagree with your introductory statement, that theories should be graded on a curve. Either a theory is correct, or it is not. If i create a theory that explains how unicorns bounce the sun across the horizon every morning and into the night to explain the cycle between day and night, it may very well be a better theory than what the other guy has. But it's still not the truth. If we have ten predictive theories, and ALL ten of them FAIL to predict natural events, then they ALL FAIL. We don't pluck out the one that fails the least and call it science. Either a theory accurately predicts natural phenomenon or it does not.

As to your predictions. You had three of them and i will discuss each of them in the order they were presdented.

Your first prediction claimed that a statstical model could be created to predict the PROBABILITIES of error correction. This is NOT a scientific prediction, but rather a simple statistical model.

The second prediction is better, and i agree we should expect that allelles with errors, which are vital to the survival of the organism would probaby show a marked increase in error correction rates through simple darwinian evolution. We see this in all aspects of nature really, where all organisms throw resources and energy into aspects of life that increase the chances the organism will survive and live long enough to breed and spread it's genes further. This is of course basic darwinian evolution at work.

Your third prediction, leaves a lot to be desired. It's basically the same exact prediction as the 2nd one, but stated differently.

In the second prediction you say vital errors are corrected at a higher rate, and in the third prediction you say minor errors are corrected at a lower rate. They are both the exact same prediction.

What we're left with is one valid prediction, which says that evolution will do exactly what we already know it does, exactly for the reasons darwin said it did them some 200 years back. I don't see anything groundbreaking here.

That said, i could be mistaken and please feel free to correct me if i misunderstood. But i was under the impression that you were going to present an ALTERNATIVE theory of evolution which could reliably predict events, something you argued forcibly that darwinian evolution could not do. I distinctly recall you saying bluntly that other theories existed which COULD do this. Am i missing something here?

[Forest_Dump]

Mabus:

"My understanding of Darwins theological beliefs is that he was himself an avowed Atheist."

Check out the last page of The Origins of the Species.

[cheaky monkey]

dawrins original theory was not perfict anyways. It had to be modified later, to the modern synthesis, for it to be perfict (in the sence that it explains all evolutionary questions).

Forest dump: are you refering to

' there is grandeur in this view of life, with its serveral powers, having been originally breathed by the creator into a few forms or into one.....'

sentance?:s sorry i got a smaller version of the book, its the only reference to a creator i could find without reading to much.

Darwin began a strong christian, trained to be a theologan (or something similar), but he gave that up... and eventually, according to some peoples views on him, pretty much gave up the idea of a god. (or a christian's idea of a god, a creator and so forth)

he may have said thoes things because he was fearfull of what the public would say about his book, and the place of god in it?

[Forest_Dump]

Darwin did indeed more or less finish his formal education in a seminary. He did also believe, at least for a while, that evolution was evidence of God's handiwork. It has been more redently that these teleological (i.e. goal or progress oriented) aspects of evolutionary theory were removed because no explanatory place could be found for them. IDers ever since have been trying to put these back for their own ideological and political purposes.

[cheaky monkey]

Thats interesting forest_dump, I always thought he never finished his education there. :S

I wish darwin was more known for his studies on orchids and other cool plants :(.

[mabus]

Forest, indeed you are correct he does reference a creator in the final page of origin of species. I was mistaken in calling him an atheist, where i should have instead said Agnostic. My apologies for any confusion.

[LifeEngineer]

Quote: It has been more redently that these teleological (i.e. goal or progress oriented) aspects of evolutionary theory were removed because no explanatory place could be found for them.

An interesting if not entirely accurate description of the teleological debate in science. Scientists and philosophers have long agreed that the religious/magical form of teleological causation is not appropriate for formal hard science. As far as I am aware, the rejection of magical teleology has never been seriously debated.

A portion of the scientific community has generalized the rejection of magical teleology into a suggestion that it would be preferable to reject all teleological causation. Only in a handful of fields like evolutionary biology has the preference for non-teleological theories been accepted as a dogmatic standard. In many fields, including essentially all applied science fields, teleological theories are the dominant form of predictive theory actually used.

Unfortunately, when large portions of evolutionary biology rejected teleological theories they also ended up rejecting hard science predictive theories. They instead ended up accepting descriptive theories whose validity is determined by subjective political opinions rather than by formal hard science testing.

As I have pointed out previously, it is interesting that even in evolutionary biology, teleological theories, such as those involved in the WHO flu study, are once again beginning to be used.

[LifeEngineer]

Mabus,
As has been discussed a number of times, analysis performed using hard science falsify and replace standards produces significantly different conclusions than analysis performed using subjective peer review standards. You will generate conclusions based on your review methodologies which are different than the conclusions that would be generated by the hard science standards I advocate.

You asked if the theory I am proposing could be falsified and I listed three examples where the theory could potentially be falsified. For at least two of those formal tests, I don’t think the results are currently known. Suggestions for tests that might falsify a proposed theory are not the same as suggestions for measuring the accuracy of the predictions generated by the theory.

The theory proposed here predicts ‘the force of error correction at a point in time’. The value of the force of error correction can and does vary from 0 to 100%. If we take as the null hypothesis the theory that error correction forces are randomly assigned or randomly assigned by some probability distribution, then the proposed theory is likely to produce far more accurate predictions for the millions of error correction forces operating in a typical genome.

[mabus]

Ok then, let me try this from another angle. How is your theory any different from darwins?

[LifeEngineer]

Different from what predictive Darwinian theory?

The proposed theory is predictive and teleological and it addresses genetic change processes.

[Forest_Dump]

As to Darwin, he did indeed withdraw before finishing. As to his atheism, at the time of writing The Origins of the Species he was clearly an IDer. However, he may well have become an atheist later in life.

As to ID:

"A portion of the scientific community has generalized the rejection of magical teleology into a suggestion that it would be preferable to reject all teleological causation. Only in a handful of fields like evolutionary biology has the preference for non-teleological theories been accepted as a dogmatic standard. In many fields, including essentially all applied science fields, teleological theories are the dominant form of predictive theory actually used."

An interesting if not entirely accurate description. The notion of a "designer" implies something with a capacity of creating a design and enacting it (thus I find "intelligent" to be redundant). I would not describe it as dogmatic, however, because should something with this capacity be discovered, ID could indeed be back in play. In fact, of all the proposals I have heard and read about, SETI seems most likely to have success there. Ideas like seances, the earth or galaxy as an organism, etc., would all fall far behind (and, of course, I suspect few would call these scientific by most definitions).

As to teleology in applied sciences, I can see the possibility here. In fact, the 'desgner' is invariably a human enacting designs of their own creation. This may be seen in tinkering with various mechanisms or experiments of even in cooking data to produce the results they want. I can't really think of many other examples. However, many do employ analogies of natural phenomena to assist their modeling - firemen, for example, often refer to fire as a living breathing organism that may be out to get them. This, of course, does work as a training or cautionary devise but is not the same as genuinely proposing that fire is a sentient organism.

[LifeEngineer]

Forest,
I thought at first that your insistence on equating teleology with ID and designers was just a questionable debating strategy. But I wonder if it is not just a matter of non-designer or scientific teleology not being taught and discussed in some parts of academia. Are you familiar with or even aware of non-designer teleology?

[Forest_Dump]

Never heard of it. Any references I can check at my local (sorry read university) library?

[LifeEngineer]

Well if google is any indication, you are right. I could probably claim to have invented the concepts of scientific teleology and teleological determinism, but then someone would find 40 year old texts that discussed it. Is it possible that in todays information intense culture 40 year old ideas are getting lost?

[galatomic]

I've never heard it refferred to as "non-designer" teleology but I can think of several philosophers who might have been close.

Michael Polanyi in "Personal Knowledge" comes closet to laying out a scientific "teleological" approach.

Kant believes there must be vital elements required to understand life but he deems it beyond science to discover.

Schopenhauer's idea about will 's primary role in all nature.

Whitehead laid out the mathematics for an extensive cosmology composed of "actual entities" who create the world for "teleologically defined" satisfactions that "lure" them to prefer and work for certain outcomes over others.

Galatomic asserted that advanced micro galactic civilizations use their technology to achieve beneficial chemical outcomes not predicted by the chemical determinism of their environment.

Then there are many forms of pan-psychism that might qualify

galatomic

[Forest_Dump]

LE

A few suggestions:

1) I never trust inter-net sources that much. The medium is too new - not everything is on the net, particularly things like 40 year old text books (BTW, I collect these. I am interested in how changes in theoretical orientation and new discoveries change what is often considered to be either the "state of the art" or the "orthodoxy" through time). Lets just say, if an idea was in taxt book 40 years ago and is not now, the question becomes "why"? Ideas are not usually lost but they are commonly discarded for any number of reasons. The inter-net is very problematic in this way. There is little control over what goes on the inter-net and things can come off, be edited or revised at the speed of light.

2) Don't trust memory. I have some pride in mine and I test it quite a bit through playing chess. And that is why I know not to put too much trust in it. Not long ago, someone posted a link to atheist arguments (specifically a satire on ID debates but oriented around the idea of the moon being made of cheese). Among the articles was one from a journal of cognitive sciences. In it, the authors talked about the relationship between memories and history. In short, there was no strong correlation between memories of an event and the reality of it. Cases have been documented of people having very strong memories of things that simply never happened. Something like this happened to me recently. I was reading a paper trying to get some technical details on a research problem I am currently working on. Something stuck in my mind as I was reading but only bubbled up a page or so later. A brilliant idea I could use with a cross reference. I flipped back, found the reference and checked it out - but nothing of relevance. I went back to that section of the paper I was reading and read through it several times - nothing. I had misread it entirely and transposed the contexts. The idea is still good (I subsequently applied it) but I guess it is mine since it is not really implied in the references I checked (and I have already agreed to present a paper on it in the New Year but I will certain mention how the idea originated). Sometimes good things come from bad practises (in this case sloppy reading) but that is rare. Still I remember vividly how the idea came to me including the "shape" of the paragraph on the page - it is just that when you look at the actual words in that paragraph, they don't match with the content of the memory.

3) One main point here is that there are many sides to scholarship. Coming up with ideas is a small part of it. Just as important is how ideas are presented (i.e. the style of writing). Technicians may come up with useful or new ideas but not know how to express them in a way that others can understand. On the other hand, poets, music writers, etc. may be very adept at presenting ideas in a beautiful manner. But that does not mean the ideas themselves are any good. I know many songs that are great but when you read the actual lyrics, they are vapid or turgid. People who can blend the two are rare. Finally, the third important attribute of scholarship is indeed in the technical details. Ideas presented without proper citation are at best sloppy craftmanship. At worst, it is plagarism, aka academic theft. I often write papers as a fast rough draft to get the ideas down sans citations. This can work. But then you have the hard part of going back and backing up your ideas through checking sources, etc. Although I have hundreds of pages of notes on things I have read (part of not trusting my memory), this part always has me surrounded by stacks of books and papers as I double check my notes and chase down ideas not captured there. And although I tend to have long lists of citations (occasionally longer than the paper itself), I often only use a small fraction of the sources I checked. But these are the technical details that most often sink potentially good papers. However, no matter how hard you work at this, in the end nobody I have ever run across does a good job of self-editing.

Learning from reviewers and critics is a skill too rarely taught particularly when it is indeed possible the reviewers and critics may not be good. And the ones you learn the least from are those that agree with you. Ignore them for the most part and focus on those who disagree. These are the ones more likely to point out where the flaws and weaknesses are. At the risk of simplistic dicotomies, there are two kinds of reviewers. First are those that do challange your premises and data. Always take those to be the most important. In science, a central theme is the question of bias and how to deal with it. Look for your own first and most ruthlessly. The second is people who are indeed blinded by their own biases (and it is not tough to spot these either). If you have not found a way to penetrate someone else's biases, then you have not presented your ideas well enough to make them think. Of course, there will always be some who will never accept new ideas. There is little you can do here except move on. Getting bogged down in a stagnant debate is pointless and damaging. This is because it wastes time, drives them into an emotional entrenchment and does the same to you - in fact often driving you (and I mean me) into stubbornly rejecting the idea that maybe they are in fact correct. And ultimately that is the biggest danger - that these pointless debates end up reinforcing our own biases instead of leading us to tear them down.

As to your own specific ideas, the best thing I can recommend is look at your ideas about what science is (and you seem to refer back to things you learned 40 years ago) and find out what has changed since. 40 years is a long time in the history of science and much has been learned since. Some of this has actually changed the way we think about science. Science is no more defined by the use of mathematical models than it is by the use of white lab coats or slide rulers. Blind adherence to methodology has its place but also its limits. In fact, even anarchic methods and just bad scholarship has its place (and limits). For this, check out Feyerabend's book "Against Method". If you can find both the value and dangers of that work (pay particular attention to the discussion of Galeleo), then you will closer to today.

[LifeEngineer]

Forest,
I certainly agree with much of what you say. There are certainly some interesting biases in the information available on the Internet that seriously limit its value in scientific analysis.

Like you, I am interested in studying both how information changes overtime and in how it is communicated.

In the business world, there are very efficient methods of communicating relevant current knowledge in almost any field of expertise. Even when you worked in very small companies, it was practical to get the updates on the most recent development in your field by talking to professional acquaintances or by talking to professional consultants. When I was actively involved, I could call a friend and/or a consultant and in 15 minutes get a quite reliable update on the key points of any evolving issue. I always recognized that I was not and could not be an expert on every topic, but I always had almost immediate access to the pro’s and con’s of any developing topic.

I get the impression that such networks are not nearly as efficient in academic areas. Lots of people seem to have ready access to the ‘party line’ on a subject, but few people seem to have access to detailed technical knowledge. The falsification argument presented here is based on fairly basic population mathematics, yet none of the people arguing about the conclusions appear to have access to technical knowledge regarding the math involved.

One of the subjects I have specifically studied is what might be labeled ‘cumulative deterioration of knowledge’. Under certain types of conditions, the bias of a group of experts can result in a gradual and cumulative deterioration in knowledge. The ‘Emperor New Clothes” fairytale provides a surprisingly accurate description of this not uncommon phenomena. The evidence, I believe, that strongly suggests that many existing fields of ‘science’ are experiencing this cumulative deterioration of knowledge.

Formal falsify and replace testing is the ‘scientific method’ of determining whether or not cumulative deterioration of knowledge is occurring or has occurring in a field. It is interesting/surprising how many scientists today seem to reject as inappropriate any effort to apply formal hypothesis testing.

I will post this before I address the specific issue of scientific or non-designer teleology.

[LifeEngineer]

Forest,
I don’t think the issue is my memory of what certain textbooks and teachers had to say about scientific teleology 40 years ago. The issue or problem is that my current understanding of scientific teleology is a synthesis of different ideas taken from philosophy of science courses and literature, from abstract mathematics and mathematical modeling courses, from experimental psychology courses, and bits of knowledge acquired over the years. Most of the basic concepts associated with scientific teleology had been defined, but I am pretty sure I never saw a single source that brought all the ideas together into a consolidated statement of position. If all the ideas had been in one place, it would have taken me almost 40 years to figure out how to formulate testable predictive teleological theories.

It would probably be interesting to have a technical discussion of the relative merits of ‘mechanistic predictive theories’ versus ‘teleological predictive theories’. Do we have any philosophy of science experts how understand the fine points of the mathematical modeling of scientific causation?

[MoonChild]

Back to your statement of the predictive model, my main concern with it is that you are trying to predict an overall outcome (organism survival) with a function of the change in (or correction of a change in) a SINGLE ALLELE. Unfortunately except in extreme cases (which generally result in fetal death), it's impossible to create a situation in which you know with any certainty that only one allele in a live birth has change from WHAT IT WOULD HAVE BEEN (now, this IS a testable, albeit expensive, assertion- by doing a COMPLETE genome map of both parents and the offspring). You can in that case at least quantify how many changes actually occurred. But there are still two immediate problems that come to mind:

1. How do you identify where error correction has occurred if it was successful, compared to no error requiring correction?

2. How do you successfully argue that a chosen allele change was the cause of the organism survival or demise?

Thoughts?

[MoonChild]

Excuse me , I meant to say "identified" allele change, not "chosen" in point #2 above...

[Rettaw]

No worries :)

[MoonChild]

Sorry, this bulletin board has a different format than the one I'm used to, I couldn't find the button! I've got it now though :) My fault, I was in a hurry...

[LifeEngineer]

Moonchild,
Good questions.
Quote: 1. How do you identify where error correction has occurred if it was successful, compared to no error requiring correction?

This is largely a matter of definition. You might argue that point mutations can only occur at a relatively few sites, and you can argue that for about 50% of all genes that no point mutations are possible. However, if you assume that only a very small number of point mutations are possible, then you would have a very difficult time explaining how mutations are random if they can only occur in a very select pre-determined set of locations. The analysis here uses the assumption that point mutations can occur at essentially any location on a gene. You can perform this analysis using the limited mutation assumption, in which case, you would probably be able to show that known genetic changes could not be explained by the defined random mutation assumption.

It is useful to remember that you either need to use the same random mutation assumption to explain equilibrium and rapid change or your predictive theory needs to incorporate a dynamic mutation rate assumption.

Quote: 2. How do you successfully argue that a chosen allele change was the cause of the organism survival or demise?

If you assume that ‘random mutations’ are being generated at a predictable rate by random mutation, and if based on observation you know those mutations are not appearing in the population, then you know from basic mathematical concepts that the mutations are being removed by some type of decrement process. If you assume, as a literal interpretation of Darwin would suggest, that the dominant form of selection is natural selection, then there should be natural selection forces- death or infertility- operating to remove the alleles being introduced by random mutation. Since you know or can calculate the number or frequency of mutations that are occurring, you can calculate the expected rates of natural selection required to remove the expected mutations. Since this very high ‘expected rate of death or infertility from mutant alleles’ is not observed to occur, you can conclude there is a dominant form of selection other than natural selection operating.

[Forest_Dump]

There may be some problems here. I seem to remember someone talking about albinism among birds and noting that as a rule albinos are fine in terms of reproductive fitness but often are social outcasts and cannot get a mate. This can change, however, in cases of low population densities (such as colonial or fringe populations) where they may become "acceptable". In cases like this, "founder effect" may play an exagerated role in the flourishing of new variants. This is more along the lines of Darwin's finches. Variants that might have been maladaptive in one local may flourish upon arriving at a new econiche. Not sure how that can be predicted but we certainly have seen lots of examples were it wasn't (Australia and their wild history with introduced species certainly comes to mind here).

[MoonChild]

Moonchild,
Good questions.
Quote: 1. How do you identify where error correction has occurred if it was successful, compared to no error requiring correction?

This is largely a matter of definition. You might argue

I strongly disagree. it's a matter of determining how something might be measured, not arguing over definitions and carefully defining your assumptions to make your model "work". The reality is that you can make any assumption you want but until you specify how to measure the event, the assumption cannot be tested. Assumptions are important - you can't invoke them like 'God' as some non-testable airy-fairy "thing out there" - it's got to be based on previous evidence and testable. In essence, for every assumption you invoke, you've got an underlying hypothesis that has to be tested in order to rigorously defend your analysis.

That's why statisticians bothered generating models which are free of assumptions of any particular distribution (such as normal), instead of doing it the easy way.

The analysis here uses the assumption that point mutations can occur at essentially any location on a gene.

Again, where is the technology to test what is actually happening? Error correction is really, really ephemeral. If you don't see the "expected" number of mutations (based on a complete genomic analysis??? this is getting expensive fast!), then your options are:

1. your expectation (ie assumptions) were wrong
2. error correction has occurred
3. some other mechanism is in play
4. some combination of the above
5. something you haven't thought of yet.

And there is NO WAY to shed light on which it is, until you find a way to MEASURE THE PHENOMENON.

Your response to my #2 above also invokes more assumptions than I'm at all comfortable with. Again, assumptions have to be based on prior evidence of SOME sort. Remember, an assumption is a hypothesis.

One of the major problems with your model as explained so far is that you dump a huge number of assumptions into a black box and don't appear have a mechanism to determine whether your observed outcomes are due to actually rejecting your hypothesis, to one (or many) of those assumptions being incorrect, or to your model not manipulating the data in a meaningful way.

As Forest pointed out, 'fitness' is heavily reliant on the immediate environment over time for an individual. One of the problems as I see it is a confusion over 'logical depth' - you are trying to look at a gross outcome (survival or reproduction - which one is not even clear) in order to test mechanisms which are occurring at a much, much smaller scale. This is akin to trying to examine the atomic structure of bricks by visiting a construction site.

[MoonChild]

by the way, I still don't understand exactly what you mean when you invoke "Darwinism". Are you implying that one can only use the 'rules' as set forth in his book from 150 years ago? Or do you mean by 'darwinism' the body of knowledge about genetics that we have built up during the past 150 years (largely in the last 20 years!) about the mechanisms of DNA, mutation, recombination, etc., but which posits that all that we see has occurred through natural processes as opposed to divine intervention of some sort?

I have zero interest in discussing "just how right Darwin was". He got us all started down the right path (and he wasn't even the first to think of it, just the one who wrote the popular book), that's good enough for me. I'm only interested in the body of knowledge that scientific inquiry has built - error mechanisms are cool, I want to know all about them - but don't give a rat's ass is it "proves" or "disproves" Darwin :roll: . It's just another piece of a fascinating puzzle.

[LifeEngineer]

Moonchild,
You are welcome to introduce any alternative definitions of variables and any alternative definitions of predictive theory you wish provided your definitions are compatible with the available data and evidence. The basic equations we are working with hear has the form

BI+fRM-fNS-fEC-fX1-…..=EI
We have non-controversial methods of measuring beginning and ending frequency (BI and EI) for individual alleles. I elected to define the force of random mutation in terms of known forces of point mutation. I used a standard method of measuring the force of natural selection. I elected to define the force of error correction as the balance item in the above equation and to lump all the miscellaneous forces into the fEC category. This is a standard and perfectly legitimate technique.

These definitions provide sufficiently precise measurements to evaluate the relative merits of two competing predictive theories.

You are welcome to present an alternative predictive theory and you are welcome to present for discussion alternative definitions of the variables or forces involved in producing the observed changes in the frequency of alleles.

Quote: And there is NO WAY to shed light on which it is, until you find a way to MEASURE THE PHENOMENON.

The purpose of the analysis here is to compare competing predictive theories. The fact that our current knowledge is incomplete, does not prevent us from testing and rejection theories that do not fit the data and accepting, at least temporarily theories the do fit the data.

We come again and again to the differences in approach between ‘hard science’ and ‘peer review science’. Peer review science says we can use two different subjective standards for evaluating ‘scientific theories’. In peer review science we can reject unwanted theories because they don’t represent perfect knowledge and we can continue to support favored theories by arguing there is no acceptable alternative theory.

Hard science standards, by contrast, require that all theories must be expressed in a testable predictive format and any theory that passes testing is accepted, for the time being, over any predictive theory that fails to pass testing. At least based on this initial test, a genetic change model or theory that includes a ‘intelligent goal directed error correction process’ provides a better fit to observed data than a theory that recognizes only random mutations and natural selection.

It would not be terribly difficult to produce alternative predictive theories that would pass the test presented. No one, however, has yet produced such an alternative predictive theory.

[Forest_Dump]

LE

I have to admit - you constantly amaze me. I am still astounded at how you have invented this dicotomy between what you call "hard science" and what you now call "peer-review science". Add to that your data cooking which includes such logic as: "I elected to define the force of random mutation in terms of known forces of point mutation. I used a standard method of measuring the force of natural selection. I elected to define the force of error correction as the balance item in the above equation and to lump all the miscellaneous forces into the fEC category. This is a standard and perfectly legitimate technique." (Standard and perfectly legitimate where? In the insurance industry? Not surprised really. This is the industry in Canada that, because insurance is deemed mandatory, justified a rate increase a couple of years ago on the basis that they had lost a lot of money in the stock market. Well, who didn't? Too bad they didn't put their actuarial scientists to work predicting that.)

And finally, you cap it off with: "At least based on this initial test, a genetic change model or theory that includes a ‘intelligent goal directed error correction process’ provides a better fit to observed data than a theory that recognizes only random mutations and natural selection." Yumpin' yiminy. Well, this is a classic example of implied science to be sure but beyond that, I don't see it.