Uncommon Descent Serving The Intelligent Design Community

Does an Element of Subjective Judgment Exclude a Research Program from the Realm of “Science”?

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Congratulations to all of those Darwinists who seek to exclude ID from science whenever the CSI in a structure or DNA sequence is difficult to quantify exactly.  You’ve just excluded a highly influential form of evolutionary analysis (cladistics) from science as well.  The following lengthy quote is from Adrain, Jonathan M.; Edgecombe, Gregory D. & Lieberman, Bruce S., Fossils, Phylogeny, and Form: An Analytical Approach, New York: Kluwer Academic (2002), pp 56-57:

Phylogenetic inference is pivotal to an understanding of the systematics of any group.  Cladistics offers an objective framework for the analysis of data that inevitably incorporates elements of subjectivity (Hennig 1966, Swofford 1993).  A cladogram is a hypothesis of relationships derived from a set of putatively homologous morphological and/or molecular characters (Forey 1992), to which is added information on character polarity or the nature of an outgroup.  If homologous organs or characters are defined as those jointly inherited from a common ancestor (Simpson 1961, Hennig 1966), it becomes impossible to identify homologies without access to the true phylogeny (a problem of circularity:  Jardine and Sibson 1971).  Hence, criteria of compositional and structural similarity are used in practice.  Compositional similarity refers to resemblance in terms of biological or chemical constituents (the composition of the organs).  Structural correspondence refers to the spatial or temporal arrangement of parts, structure of biochemical pathways, or the sequential arrangement of organized structures (Sneath and Sokal 1973).  The number of potential characters is limited only by our ability to recognize putative homologies at increasingly fine scales.

Inevitably, even the most rigorous tests of homology can fail to identify character states that are similar because of convergence or ‘reversal’ (‘homoplasy’, rather than direct, common descent).  Most real data sets therefore contain character conflict (Strauch 1984, Deleporte 1993).  This is usually resolved using some optimality criterion (e.g., parsimony) to derive one or more cladistics hypotheses (which will reject some fraction of the supposed homologies).

Various types of data and analytical techniques are employed in cladistics, sometimes yielding widely differing results (Wiley 1981).  Nonetheless, there is consensus on the nature of the pattern being sought, and the objective reality of the process that produced it (cladogenesis).  There is only one true evolutionary tree, and the diversity of approaches therefore all have the same ultimate goal (Wilkinson 1992).  Inevitably, the process of selecting characters for analysis is subjective, and amounts to a radical form of character weighting (Meacham 1994, Wilkinson 1994a).  The sample is also likely to be biased towards more obvious features, and frequently towards those with some form of historical precedence (Pearson 1999).

The absence of complete objectivity at all stages in a cladistics analysis in no sense detracts from its value in producing hypotheses of relationships.  Other (non-cladistic) approaches in systematics also operate on finite data sets and incorporate similar assumptions.  Often, these do not produce hypotheses directly, but serve to describe aspects of the data, frequently offering additional insights into evolutionary processes (Foote 1996).  All results (phylogenetic and otherwise) should therefore be presented along with the original data and sufficient information to all the analysis to be repeated.

(emphasis mine)

Let’s count up the subjective judgments that go into constructing a cladogram.  I see at least the following (there are almost certainly more).

  1. Which characters am I going to select for analysis?
  2. Are these structures homologous?
  3. Is there “resemblance” of biological or chemical constituents?
  4. Are the spatial and temporal arrangement of parts similar?
  5. Are the character differences upstream or downstream?
  6. Homology or Homoplasy?
  7. Is there “structural correspondence”?

No wonder different scientists’ analyses yield “wildly differing results.”

Consider the following sentence extracted from the quotation above:

The absence of complete objectivity at all stages in a cladistics analysis in no sense detracts from its value in producing hypotheses of relationships.

Is the following a fair extrapolation of the authors’ logic:

The absence of complete objectivity at all stages in a ID analysis in no sense detracts from its value in producing hypotheses of design.

Comments
Joe @ 32 Please see KF's many posts .He has given a value of 4.32 bits to the aminoacid sites ,where as 4.32 is Fit/site Fit and bit are entirely different measures so how can you equate FSC to FSCI/O or CSIMe_Think
November 4, 2014
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Yes Rich, you are sorry. That still isn't a refutation of my claimsJoe
November 4, 2014
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Sorry Joe, I'm waiting to dance with Barry, get in line. You might want to learn Python in the meantime..Rich
November 4, 2014
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wd400:
If two groups of species share a trait that wasn’t present in their shared common ancestor it arose by convergent evolution.
"The Evolution Revolution" exposes that as pure wishful thinkingJoe
November 4, 2014
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Yes Rich and I challenge you to show how the two are not the same. Should be easy. However you won't even deal with my argument showing that they are the same thing.Joe
November 4, 2014
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In such a world is it possible that several different lines of fish evolved into amphibians? No. We know about convergent evolution because of phylogeny. If two groups of species share a trait that wasn't present in their shared common ancestor it arose by convergent evolution. In this case, amphibians are more closely related to each other than they are to fish, so we know they arose once.wd400
November 4, 2014
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Joe, do you know what equals '=' means? Joe: "If you knew anything you would know they are the same thing FSC = CSI = FSCO/I."Rich
November 4, 2014
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MT- CSI is complex Shannon information with functionality or meaning, and FSC is functional sequence complexity. And with respect to biology they both pertain to Crick's definition of biological information. Both differentiate between mere complexity and specified complexity.Joe
November 4, 2014
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Assume convergent evolution to be true, such that we have many examples of covergent evolution of genes, many examples of convergent evolution of protiens, many examples of convergent evolution of complex organs, many examples of convergent evolution of body plans. In such a world is it possible that several different lines of fish evolved into amphibians? How about amphibians to reptiles, how about reptiles to mammals. Is it possible that we have several separate fish->amphibian->mammal trees? Evolutionist arguments that this synario is highly improbable would seem like a stange argument. So doesn't convergent evolution make claudistics sheer fantasy? I don't know. EdEdward
November 4, 2014
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LoL! @ Rich- I was correct in that case. Nice own goal, Rich. Way to shoot yourself, againJoe
November 4, 2014
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Yes, Joe, I'm sure in your mind you're always right. https://uncommondescent.com/intelligent-design/no-bomb-after-10-years/#comment-521624 I'd like to dance with Barry. I've bought a new dress and everything!Rich
November 4, 2014
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So, you were wrong in 19 when you claimed Durston had fulfilled the criteria I listed? Durston has proved that protein sequences occupy specific regions of squence space, but not biologist would be suprised by this. So what's the big deal from that paper?wd400
November 4, 2014
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Joe @ 15 Have you gone through the python program code attached in the supplementary material ? Do you still disagree that FSC is different from CSI or other ID variants of it? In particular look at following code in conjunction with Equation 6 of the paper: #COMPUTE FUNCTIONAL ENTROPY PER ACTIVE SITE Density=TotalDistEnt/ActiveSites #COMPUTE STANDARD SHANNON UNCERTAINTY Shannon=float((ActiveSites*math.log10(20))/math.log10(2))Me_Think
November 4, 2014
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LoL! wd400, it is up to YOU to show that unguided processes can generate it. That is how science works.Joe
November 4, 2014
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Alright then Joe, where does Durston show evolutionary processes can't generate (enough of) the information measure he calculates?wd400
November 4, 2014
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Enkidu- If you want hilarious there isn't any need to look any further than your alleged ToEJoe
November 4, 2014
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Well Rich, I made my case. And I have always been correct when it comes to exchanges we have had. So you are lying about me, again. It's as if you are just pathological. The question is, will Rich ante up and address the case I made or will he be a cheerleader and try to dance with Barry?Joe
November 4, 2014
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Joe Function is an observation. CSI requires knowledge and understanding what we are observing. I've always found that to be hilarious about ID's position: "If you tell us beforehand that something is designed then we can tell you if it has CSI". :)Enkidu
November 4, 2014
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I'm staying right here Joe, hoping Barry shares his thoughts on if FSC=CSI. It's going to be fun. As you think it is and you're normally wrong, I wonder if he'll use that as a data point when making his decision?Rich
November 4, 2014
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No Rich, you are the FIASCO. You are just upset because your position has nothing. Your game has been exposed. Run back to your swamp and declare victory. It's all you have.Joe
November 4, 2014
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wd400:
Anyway, I don’t think the problem most people have with CSI is that is requires some sort of subjectivity.
Function is an observation. CSI requires knowledge and understanding what we are observing.
What a IDist would need to do is define CSI is a way that it can at least be estimated for a sequence, show that biology has it and then show that natural selection and other mechanisms can’t achieve it.
You guys are good at showing the limits of natural selection and other unguided mechanisms are impotent. And Durston did what you request. Perhaps it is time you guys stepped up and demonstrated that natural selection is up to the task. Lead by example, nothing is stopping you.Joe
November 4, 2014
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Sorry Joe, I asked Barry for his thoughts. We already know you're on the record as FSC=CSI=FIASCO.Rich
November 4, 2014
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MT:
FSC is change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)) and the unit of measure is ‘Fit’. It is not CSI or dFSCI
I disagree and have made my case.Joe
November 4, 2014
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Anyway, I don't think the problem most people have with CSI is that is requires some sort of subjectivity. What a IDist would need to do is define CSI is a way that it can at least be estimated for a sequence, show that biology has it and then show that natural selection and other mechanisms can't achieve it. I've not seen anyone get close to that.wd400
November 4, 2014
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In the paper "The origin of biological information and the higher taxonomic categories", Stephen C. Meyer wrote:
Dembski (2002) has used the term “complex specified information” (CSI) as a synonym for “specified complexity” to help distinguish functional biological information from mere Shannon information--that is, specified complexity from mere complexity. This review will use this term as well.
And a reminder of what Crick said:
Information means here the precise determination of sequence, either of bases in the nucleic acid or on amino acid residues in the protein.
ID's claims: ID is based on three premises and the inference that follows (DeWolf et al., "Darwinism, Design and Public Education", pg. 92): 1) High information content (or specified complexity) and irreducible complexity constitute strong indicators or hallmarks of (past) intelligent design. 2) Biological systems have a high information content (or specified complexity) and utilize subsystems that manifest irreducible complexity. 3) Naturalistic mechanisms or undirected causes do not suffice to explain the origin of information (specified complexity) or irreducible complexity. 4) Therefore, intelligent design constitutes the best explanations for the origin of information and irreducible complexity in biological systems.Joe
November 4, 2014
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Rich, FSC pertains to amino acid sequences that form a functioning protein. CSI wrt biology pertains to amino acid sequence specificity, which are amino acid sequences that form a functioning protein. Dembski goes over that in NFL:
Biological specification always refers to function. An organism is a functional system comprising many functional subsystems. In virtue of their function, these systems embody patterns that are objectively given and can be identified independently of the systems that embody them. Hence these systems are specified in the same sense required by the complexity-specification criterion (see sections 1.3 and 2.5). The specification of organisms can be crashed out in any number of ways. Arno Wouters cashes it out globally in terms of the viability of whole organisms. Michael Behe cashes it out in terms of minimal function of biochemical systems.- Wm. Dembski page 148 of NFL
Meyer's "Signature in the Cell" makes it clear that functional sequence complexity is the same thing as CSI- They both pertain to Crick's definition of biological information. That you guys can't even grasp that simple fact proves that you are on an agenda of obfuscation. You guys are sad, really sad. When all it would take to shut ID down is to ante up and support evolutionism/ unguided evolution/ blind watchmaker evolution/ the missing ToE, and instead you choose to attack us with your willful ignorance, it proves that you are cowards and that is the reason comments get closed.Joe
November 4, 2014
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Barry at 8, similarity and homology are different. Homology either is or isn't, so you can't have a percent homology (although many molecular biologists misuse the term in this way). In any case, it's quite possible to calculate the probability traits in different organisms are homologous, that's the basis of most multiple sequence alignment software, for instancewd400
November 4, 2014
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Joe @ 7 FSC is change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)) and the unit of measure is ‘Fit’. It is not CSI or dFSCIMe_Think
November 4, 2014
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Joe @ 7 FSC is change in change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)) and the unit of measure if 'Fit'. It is not CSI or dFSCIMe_Think
November 4, 2014
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Do you think that FSC = CSI Barry?Rich
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