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Culture and the Evolutionary Process
How do biological, psychological, sociological, and cultural factors combine to change societies over the long run? Boyd and Richerson explore how genetic and cultural factors interact, under the influence of evolutionary forces, to produce the diversity we see in human cultures. Using methods developed by population biologists, they propose a theory of cultural evolution that is an original and fair-minded alternative to the sociobiology debate.
339 pages, Paperback
First published September 1, 1985
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About the author
Robert Boyd
8 books29 followersLibrarian note:
There is more than one author in the GoodReads database with this name
Robert Boyd is a professor of the School of Human Evolution and Social Change at Arizona State University.
There is more than one author in the GoodReads database with this name
Robert Boyd is a professor of the School of Human Evolution and Social Change at Arizona State University.
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Displaying 1 - 2 of 2 reviews
January 1, 2023
Great models. Rather dense, but the models are worth understanding. Try to get a later edition because the first one has some critical typos.
March 3, 2024
Authors are nearly blank slatists who quickly attribute parent child correlations to information despite extremely low shared environment variance estimates across studies. They also attribute all race differences to information.
More than this their fundamental conception of a meme is double thinky. To begin with, they profess that idea of the meme locus, with several competing variants at a locus. As an example they give ways to hold a ping pong paddle when playing. In doing this they conflate the actual behavior (way chosen) with the meme (ways known), saying that only one behavior can be chosen and so only one variant can win. This is double thinky because it doesn't help shake the feeling that culture people are always trying to equivocate culture as behavior with culture as information. This is why I won't use the C word in my work, I say memetics, because information is as different from behavior as genes. Imagine if sometimes genotype meant behavior and sometimes it meant DNA sequence. That's "culture."
In my model, upon exposure the player has every meme they have seen at once, each has an average effect on behavior, which will come out to some typical playing style in combination with genes, the play style being a combination of known styles and genetic fit. This is obviously a much better model than the Boyd Richerson model. The BR model takes 300 pages to develop and my model takes 4. The BR model takes 300 pages in large part because it's concerned with useless allele theory math; this is why the authors had to profess the idea of the memetic locus, which seems completely unrealistic. Locus theory is not useful when there is no locus to compete over. But as allele theorists (the better name "population geneticists", who study alleles and not populations -- quantitative geneticists study populations, and not alleles), the authors wanted to simply import locus theory, for something which is not a gene and should therefore not use locus theory.
All of this means their theory is not empirical. It is not empirical because it has no estimable parameters. Their definition of meme is not observable, because it is the same as behavior. This would lead a scientist to measure behavior, without measuring anything that estimates the memetic component of said behavior. Undoubtedly, most behaviors are highly heritable, including ping pong form. This makes it hard to imagine how one could test their postulate that must informatic transmission happens in early childhood from teachers and parents. Perhaps the unempiricism of their model is why they make the postulate, even though it seems like twin studies already debunked it. This unempiricism is perhaps one of the reasons why this model is the main cornerstone, 40 years on, of "cultural evolution", yet no parameters of importance have been estimated from it. HBD has h^2 and other parameters that are well-estimated, my models have h^2, m^2, dh/dp, dm/dp, r_g,m, paternal age effect, and more, all of these are estimable pretty easily, I have estimated some, solid estimates would build a real empirical body of new knowledge. They don't talk about estimable parameters where they should, for example, they should correlate parent child meme scores with genes controlled for (this could probably just be c from twin studies) to see how much parents actually bias child's information acquisition independent of the child's own genetic bias. They don't talk about this, they just post allele theory tables of theoretical probabilities instead. In general allele theory is a really big distractor in a lot of texts like this; Pearson had the right idea in this regard.
That said, unlike what I got from the Lumsden and Wilson model, I can see how some of this model could easily lead to some measurable correlations, with my updated definition of meme that hopefully allows memes to be measured. It was probably an upgrade to the previous models, sadly it seems the field has stopped here.
https://en.wikipedia.org/wiki/Dual_in...
Wikipedia lists this as the last of the 3 books (LW, Cavalli-Sforza, Boyd Richerson) and says "The book's conclusion also outlined areas for future research that are still relevant today." Then it quotes EO Wilson, saying "for some reason I haven't fully fathomed, this most promising frontier of scientific research has attracted very few people and very little effort".
Laland and Brown say: "In many ways the most complex and potentially rewarding of all approaches, [DIT], with its multiple processes and cerebral onslaught of sigmas and deltas, may appear too abstract to all but the most enthusiastic reader. Until such a time as the theoretical hieroglyphics can be translated into a respectable empirical science most observers will remain immune to its message."
So, in a way, this repeats my criticism. How could the field be different in Boyd and Richerson had clearly laid out some correlations to estimate, with procedures for estimating them? This is what I do in my model. Over 300 pages, and that never happens. Probably should have been 150 pages total with the last 20 pages devoted to that.
More than this their fundamental conception of a meme is double thinky. To begin with, they profess that idea of the meme locus, with several competing variants at a locus. As an example they give ways to hold a ping pong paddle when playing. In doing this they conflate the actual behavior (way chosen) with the meme (ways known), saying that only one behavior can be chosen and so only one variant can win. This is double thinky because it doesn't help shake the feeling that culture people are always trying to equivocate culture as behavior with culture as information. This is why I won't use the C word in my work, I say memetics, because information is as different from behavior as genes. Imagine if sometimes genotype meant behavior and sometimes it meant DNA sequence. That's "culture."
In my model, upon exposure the player has every meme they have seen at once, each has an average effect on behavior, which will come out to some typical playing style in combination with genes, the play style being a combination of known styles and genetic fit. This is obviously a much better model than the Boyd Richerson model. The BR model takes 300 pages to develop and my model takes 4. The BR model takes 300 pages in large part because it's concerned with useless allele theory math; this is why the authors had to profess the idea of the memetic locus, which seems completely unrealistic. Locus theory is not useful when there is no locus to compete over. But as allele theorists (the better name "population geneticists", who study alleles and not populations -- quantitative geneticists study populations, and not alleles), the authors wanted to simply import locus theory, for something which is not a gene and should therefore not use locus theory.
All of this means their theory is not empirical. It is not empirical because it has no estimable parameters. Their definition of meme is not observable, because it is the same as behavior. This would lead a scientist to measure behavior, without measuring anything that estimates the memetic component of said behavior. Undoubtedly, most behaviors are highly heritable, including ping pong form. This makes it hard to imagine how one could test their postulate that must informatic transmission happens in early childhood from teachers and parents. Perhaps the unempiricism of their model is why they make the postulate, even though it seems like twin studies already debunked it. This unempiricism is perhaps one of the reasons why this model is the main cornerstone, 40 years on, of "cultural evolution", yet no parameters of importance have been estimated from it. HBD has h^2 and other parameters that are well-estimated, my models have h^2, m^2, dh/dp, dm/dp, r_g,m, paternal age effect, and more, all of these are estimable pretty easily, I have estimated some, solid estimates would build a real empirical body of new knowledge. They don't talk about estimable parameters where they should, for example, they should correlate parent child meme scores with genes controlled for (this could probably just be c from twin studies) to see how much parents actually bias child's information acquisition independent of the child's own genetic bias. They don't talk about this, they just post allele theory tables of theoretical probabilities instead. In general allele theory is a really big distractor in a lot of texts like this; Pearson had the right idea in this regard.
That said, unlike what I got from the Lumsden and Wilson model, I can see how some of this model could easily lead to some measurable correlations, with my updated definition of meme that hopefully allows memes to be measured. It was probably an upgrade to the previous models, sadly it seems the field has stopped here.
https://en.wikipedia.org/wiki/Dual_in...
Wikipedia lists this as the last of the 3 books (LW, Cavalli-Sforza, Boyd Richerson) and says "The book's conclusion also outlined areas for future research that are still relevant today." Then it quotes EO Wilson, saying "for some reason I haven't fully fathomed, this most promising frontier of scientific research has attracted very few people and very little effort".
Laland and Brown say: "In many ways the most complex and potentially rewarding of all approaches, [DIT], with its multiple processes and cerebral onslaught of sigmas and deltas, may appear too abstract to all but the most enthusiastic reader. Until such a time as the theoretical hieroglyphics can be translated into a respectable empirical science most observers will remain immune to its message."
So, in a way, this repeats my criticism. How could the field be different in Boyd and Richerson had clearly laid out some correlations to estimate, with procedures for estimating them? This is what I do in my model. Over 300 pages, and that never happens. Probably should have been 150 pages total with the last 20 pages devoted to that.
Displaying 1 - 2 of 2 reviews