12 Misunderstandings Of Kin Selection Pdf Kiera

1. 12 Misunderstandings Of Kin Selection Pdf Kiera Cass

Posted March 24, 2011 at 12:46 pm It’s not really boggling at all.How can it matter how excruciatingly clear he was if the critic never read the book in the first place?Though it’s interesting that I don’t find absolutely ridiculous the notion that a gene can be actually selfish, if you follow the meaning of the term down to the bottom. When a person is selfish, it all boils down to molecules in action, so why can’t a shorter chain of interactions also hold the label? I don’t think it’s a particularly useful argument, but if a person insists on not understanding what a metaphor is, why not have some fun forcing them to attack the strawman properly? Posted March 25, 2011 at 1:08 am Oh, and on this specifically: “I’m certainly not an expert at this stuff, but I took it as obvious that r applies only to the variable portion of the genome.”It varies depending on how r is calculated.

The simplistic “r of parents to offspring is 0.5” sorts of statements involve the assumption that the parents are dissimilar at all loci involved. There are various complications to account for this. Empirical measures run roughly along the lines of looking at whether two individuals are more similar to each other than they would be if chosen at random from the population., but can extend to explicit analyses of paternity & so forth.This can have interesting results. If there is very little variation in the combination of markers & population investigated, inferred relatedness among individuals is uniformly low. If similarity in the reference population as a whole is near one, no pair of individuals can deviate from it to any substantial degree.

There are a couple of fun papers on Solenopsis (fire ants) that show this result. There’s damned little genetic variation in introduced populations. Consequently, measures of relatedness drop down near zero and researchers wonder why Hamilton’s rule isn’t holding. Posted May 28, 2012 at 11:39 am Perhaps Nowak’s greatest flaw in the original paper is his rather arrogant assumption that mathematical models alone must dictate what is to be accepted as true, and that verbal models or deduction from evidence has no place whatsoever in Biology.

Worse than this, his own model stacks up a preconstructed sequential mathematical structure to get the end effect that he is aiming at. And even worse than both of these, he completely neglects testing if Inclusive Fitness would improve upon the results of his own model. What Nowak is doing in essence is mathematical curve fitting to his own preconceived ideas. Posted March 24, 2011 at 6:44 pm I was listening recently to a discussion between Richard Dawkins and Lawrence Krauss in which they argued about who was the greatest scientist, Einstein or Darwin. Dawkins thought that natural selection was a simple concept and that therefor Darwin didn’t need to be very clever to come with it and that Einstein was therefor the more brilliant scientist.This argument reinforces for me what I thought at the time, which is that although the concept is very simple, it is clearly not one the human brain is capable of dealing with easily, and that therefor it was probably far more difficult to think of than it seems now that we are familiar with it.

Like maths which is so simple that computers can be progammed to do it very easily, but which the human brain is not really designed for so we aren’t very good at it, natural selection is clearly more difficult than it seems (to Richard Dawkins at least;-)). It certainly must be at the head of the queue for ‘most misunderstood scientific theory’.

If I had a dollar for every time I’ve read errors about evolution in books and articles written by people who should have known better, I could take myself out for a very nice dinner! Posted March 25, 2011 at 3:34 am Your implication is somewhat ingenuous.

Wiles could not have proved the theorem without a massive amount of automated computation.The disputes over the huge involvement in artificial electronic mathematics involved in his proof resonate to this day.Computers have become very good at mathematics, and an algorithm partly developed by the PhD student at Cornell: Michael Schmidt (along with Hod Lipson) is able to derive fundamental equations from raw data.(Science 2009, Vol 324, p81)A version is available on-line. Posted March 25, 2011 at 6:42 am To say an algorithmic machine is better at mathematics than a human is, to my mind at least, like saying an abacus is better at arithmetic than a human. An abacus needs direct human involvement, a computer, one can wind up and let go.Computers are much quicker at performing logical algorithms than humans, as long as the humans create the algorithms. I don’t consider this thought or mathematics. There are computational proofs, of course, but again these rely on the sheer capacity of computers to crunch numbers.Asserting that these logic machines are good at mathematics is like saying a Porsche is good at sprinting.

Posted March 25, 2011 at 5:41 pm 1) I did answer it, but necessarilly briefly.To summarise the scores of academic papers adequately for one at your level would take longer than the number of compiled pages alone. You request the impossible.2) You continually forward your personal incredulity on a complex subject as a reason for disbelief.This is a clear logical fallacy.3) It is not my job to be your unpaid tutor.

It is up to you to resolve your ignorance on automated math algorithms for yourself. That is if you actually care about what is true.4) I did not ‘ignore’ your post. I went out of my way to check the author’s names and the date of the paper for your edifictation.I hope that I did not waste my time. Posted March 25, 2011 at 11:40 am Sean, computers are capable of abstract mathematical reasoning and have in fact discovered novel theorems previously unknown to mathematics. These are genuine mathematical discoveries in the sense that the software was not pre-programmed to arrive at those specific theorems but was exploring proof space by following interesting lines of reasoning (for some quantitative definition of “interesting”).If that doesn’t meet your definition of what it means to do mathematics, perhaps you’d care to spell out a definition that excludes the products of artificial reasoning systems but includes the products of naturally evolved reasoning systems.

Posted March 25, 2011 at 4:28 am I usually grind my teeth with these “who was a better scientist” question (unless of course a kook or a mediocre scientist is being compared with one of the very obviously more brilliant people in history). Einstein and Darwin worked on very different problems. Darwin gathered a lot of information on animals and worked out a very convincing argument that all animals are related and that Natural Selection plays a part in the evolution of species. Einstein looked at reported measurements of physical quantities (positions of planets and stars, etc) and worked on reconciling differences between observation and the existing ideas about how things worked (Newtonian mechanics, light propagation, etc).

12 Misunderstandings Of Kin Selection Pdf Kiera Cass

They were people working on different topics; we can hardly compare them. Posted March 25, 2011 at 7:02 am Dear mr. Dawkins, I’m sorry but I absolutely don’t share your interpretation of Darwin’s statements about the evolution of the sterile caste in eusocial insects. The form of natural selection Darwin invoked, is not kin selection, but kin group selection.

He doesn’t say that the fertile and the sterile share the ‘genetic’ base of the characters that are typical of the sterile, but he says that the fertile with sterile ‘siblings’ share with their own parents the tendency to produce a heterogeneous offspring (both fertile and sterile). This sharing makes the colonies with sterile castes to produce similar colonies, which allows natural selection (in the guise of kin group selection) to reward the colonies with sterile castes in the competition against the colonies without sterile castes. In Darwin’s opinion, therefore, the sterile caste doesn’t evolve thanks to a (genetic) benefit to its own members, but thanks to a benefit to the entire colony (and despite a cost to the members of the sterile caste). If Darwin had read Hamilton’s papers, he would have been surprised to know that the inclusive fitness of a sterile is positive and comparable to the one of a fertile!

Darwin was not a precursor of inclusive fitness theory: he almost always made use of individual selection, but he sometimes made use of group selection (not only in relation to eusocial insects, and not only in the guise of kin group selection). This was also Hamilton’s opinion (Innate Social Aptitudes of Man, 1975).

Sorry for my ugly English (I’m an Italian boy). Posted April 4, 2011 at 4:15 am Hamilton seems to have regarded:– inclusive fitness and kin selection as two different concepts/theories/– inclusive fitness as the general theory and kin selection, group selection etc.

As special cases.This, I gather from the following quote of Hamilton (1975: “Innate social aptitudes of man”, quoted from ‘Narrow roads of gene land’, vol 1, p. 336):“The usefulness of the ‘inclusive fitness’ approach to social behaviour (i.e. An approach using criteria like (b K-k) 0) is more general than the ‘group selection’, ‘kin selection’, or ‘reciprocal altruism’ approaches.”Hence, there are still different traditions/usages that can be confusing, despite the 12 misunderstandings sorted out.1. In the above cited clarification of 12 misunderstandings, Dawkins seems to take ‘kin selection’ as synonymous with ‘inclusive fitness’ (unless I missed something). Anyway, I’m sure this usage is widespread, though clearly not Hamilton’s. I’d count it as the 13th misunderstanding for which Dawkins left space in his clarification paper.2.

Others call the general theory ‘multilevel selection theroy’ and take ‘inclusive fitness’, ‘kin selection’, ‘reciprocity’ etc. As special cases.2.1 As a sub-issue of point 2, some include the term ‘group selection’ into multilevel selection theory as the special case where ‘between-group’ selection prevails over ‘within-group’ selection;2.2 while others avoid the term ‘group selection’ alltogether, because it has been too dirreputed in the late 1960s.3.

Still others seem to speak of ‘group selection’, no matter whether between-group selection or within-group selection prevails. That is, they seem to call the general theory ‘group selection’ rather than ‘multilevel selection’ theory.So, there are at least three different terms competing for the label of the genaral theory: inclusive fitness (sensu Hamliton), multilevel selection theory, and group selection.Did I get everything wrong?