Interesting regularities in human behaviour: older authors write happier books

[Second post of the series “Things that I probably will not develop in a proper paper, but I find interesting enough to write here”. The first is on the XX century decrease of turnover rate in popular culture]

In the last couple of years, part of my research has been dedicated to explore the emotional content of published books, using the  material present in the Google Books Ngram Corpus. Our analysis produced some interesting results. While analysis like ours need to be carefully weighted and possibly re-produced with various samples (but this should happen always…), I think that tools like the Google Books Corpus represent an extraordinary opportunity, as my goal is to study human culture in a scientific/quantitative framework.

Keeping this in mind, there are few reasons to be cautious (see for example here), mainly due to the fact that we do not know which books are inside the Google Books Corpus.  It is well known, for example, that the share of scientific and technical literature greatly increases in the XX century sample, generating potential distortions (on the other side: the share of scientific and technical literature increased in reality in the XX century). In one of my first posts, I analysed how different normalisations seem to create different biases in the trends, with the frequencies of the same set of random words (which are supposed to be stable through time) decreasing when normalised with the total count of words in the sample (as Google does in the Ngram Viewer) and increasing when normalised with the count of “the” in the sample (assuming the word “the” would be a good representative of “real” writing and “real” sentences).

As a consequence, I am lately trying to back up and extend results from Google Ngram with a less-distant reading analysis, that is, to repeat the same automatic analysis, but in specific books of which we know authors, time of publication, etc. An interesting side-result of the analysis I am working on, that keeps to appear practically everywhere, is that books tend to become more “positive” with authors’ age. I calculated a ratio of the amount of words associated to negative and positive emotions (using LIWC), so that higher values represent preponderance of negative emotions versus positive ones and viceversa. The “King of Horror” Stephen King (see the plot below), for example, seems in fact to get milder with time (the “outlier” in the bottom-right of the plot is “The Colorado Kid”, considered indeed “a true diversion from King’s normal horror fare“).

King

Analysing a quasi-random sample of contemporary best-seller authors (which includes 354 books, with authors like Terry Pratchet, Dean Koontz, Michael Crichton, etc.), there is the same strongly significative correlation between authors’ age and ratio negative/positive emotions (see the plot below, p<.001). The same analysis in another sample of 200 books from the Gutenberg project (mainly XIX Century best-sellers, including the like of Charles Dickens or Robert Louis Stevenson) shows an analogous (significative, but weaker, with Spearman’s rho=-.17 and p<.05) trend.

ratioCont

This result is quite well known. James Pennebaker (the developer of LIWC) reported a similar study, where the same effect was found using written or spoken text samples from more than 3000 subjects participating in various disclosure studies (i.e. “the common feature of all studies was that the investigators were studying individuals who were disclosing emotional events or experiences in their lives”). In the same paper, Pennebaker and colleagues analysed also a sample from 10 published authors, somehow similar to my Gutenberg sample, but they did not find significative trends.

While quite incomplete (I would need a bigger sample; compare different ways to extract the emotional content; what happens in other languages? etc.), the results are quite interesting to me. First, they tell us that we get happier (or, well, that we use a more positive language…) with age, which is against the stereotype of grumpy grandpas and screaming-with-pasta-rolling-pin-in-the-hand grandmas (this is the Italian version, which is, in any case, better than the lonely/sad “seniors” of contemporary mainstream western culture). Incidentally they resonate with the hugely publicised finding that well-being would follow a U-shape trend through life, with the lowest point in the 40s, and an increase after that (I can not really say much about this. Just as a balance, here a partly skeptical view).

Second, the majority of anthropologists tend to think that general regularities in human behaviour (i) do not exist (as local “cultures” will mainly act towards differentiation) or (ii) when they do, they are very abstract and hence not informative (say, all humans need to eat). If we can predict that, with age, the balance between negative and positive emotion words changes, and that it changes in a specific direction, this seems quite specific and informative to me.

Decrease in popular culture turnover rate

[This post is the first in a series I’d call “Things that I probably will not develop in a proper paper, but I find interesting enough to write here”]

One way to quantify change in cultural dynamics is to measure the turnover rate of a particular domain. The turnover (z) is the number of new items that enter, after a certain amount of time t, in an ordered list of size N. What does this mean? A straightforward example of turnover is the new entries in a Top-list Chart. This week, for example, 4 new singles entered in the BBC UK Top-40 Single Chart (see here – of course the actual number of new entries will change from week to week).  So, for the week starting 8 March 2015, z=4 (the number of new items that enter…), t=1 week (…after a certain amount of time…), N=40 (…in an ordered list of size N). Notice that, with this information, one can calculate the turnover for all N from 1 to 40 (for example, this week, the 4 new entries are at the 1st, 7th, 13th, and 18th place, so, for, say N=10, z would be equal to 2).

These top lists are today ubiquitous, so that is relatively easy to calculate turnover for many cultural domains (here,  for example, the bestseller hardcover fiction books from the New York Times. While there is not an explicit way to filter the new entries, one can easily check from the number of “weeks on list” information the books that are in the list for the first time, and then get z). In fact, with slightly more effort, one can calculate the turnover of plenty of cultural domains, provided that is possible to extract the frequencies of traits through time.

Last year, together with Alex Bentley, I published a paper where we showed that the turnover profile (i.e. how z varies for different N) of a cultural domain is informative about the selective forces acting on that cultural domain (I talk about it in this post). The turnover profile  is an aggregate measure that considers an average of the turnover rate through time. So, for example, the turnover profile of the BBC UK Top-40 Singles for 2014 would be, for each N (from 1 to 40), how many new singles, on average, each week of 2014, entered in the correspondent top-N.

Another way to look at the same information is to consider the time dimension of the turnover rate, without aggregating.  One could check, for example, if, during 2014, there were “turbulent” periods for the UK Top-40, with many new entries, and “stable” periods with few changes. Different cultural domains (say books versus songs) could be characterised by different regimes. Finally, long-term turnover rates can suggest some more general changes in popular cultural dynamics.

On the last point, I calculated the turnover rate through time for two datasets. The first one (see figure below), is the Billboard Top-100 weekly Singles chart from 1946 to 2007 (data from Alex Bentley). Our N is now equal to 100, and the y-axis gives information on through time. The weekly turnover is averaged for each year.

billboard

The second one is the Top-10 yearly fiction books in United States from 1900 to 2000 (data from various sources, from a project of John M. Unsworth). In this case I plotted the authors turnover, averaged for each decade. For example, for the 1940 decade, z=7 means that each year, on average, 7 new authors entered in the top-10 in respect to the previous year.

unsworth

A striking feature of the two series is the decrease, starting around the 60s, of the turnover rate. This means that, in the last part of the century, the same best-selling authors and musicians tended to be more successful, comparatively, than what was happening in the first period of the data, where change in the top-N was faster. For example, in the 90s, the three most successful authors (Danielle Steel, Stephen King, and John Grisham) occupied 39 of the 100 possible positions in the top-10!

If this decrease is common in other popular cultural domains (which I suspect, but I do not know), it is interesting to wonder what kind of mechanisms could have produced it. One of my favourite hypotheses is that is exactly the fact that public top-lists started to be widespread (it is not unreasonable to think that today the phenomenon is even more prominent, almost farcical, with online diffusion of top-n of virtually everything). Below, as an example, a plot from the Google Books Ngram that shows that references to the same term “Top 10″ were basically absent in popular culture (to be precise: in the English language books present in the Google sample) until the 60s. Untitled

Top lists provide a way to know what others, unrelated, individuals prefer and to avoid to choose by yourself.  Why go to the bookstore and choose by myself a book, that could turn out to be bad, when I can just check the “what’s hot” section, and rely on the judgement of (millions of) other people? Of course, one could consider both the decrease of turnover and the increase of top lists popularity as the effect of some other more general mechanism (call it “consumerism”, “globalisation”, or whatever) but this does not change the fact that top lists are perfect artefacts to support a conformist bias (in cultural evolutionary terms: a disproportionate preference for common traits).

Another hypothesis is that Danielle Steel books are actually better (i.e. more effective spreaders) than Mary Johnston books (the author of To Have and To Hold, the American bestseller of 1900, according to my data). While this may sound a little crazy, one can imagine that, as the number of books and the number of readers increased, probably exponentially, during the century, higher competition generated better and better (in the sense above) books, so that it is now more difficult to write something more effective than what is already in the top list, in respect to what was happening at the beginning of the century. I was reminded of this idea when some friends recently described to me how their daughter was caught in an “epidemic” of Harry Potter in a primary school class in Edinburgh, where in around a month all pupils (the majority of whom did not know about it before) read the first book of the series. This does not mean that we reached the highest peak of literature, or of “effectiveness”, with J. K. Rowling or Danielle Steel, but that, perhaps, to go back to an higher turnover, new authors would need to explore the “design space” of narrative in other directions.

Is culture a “scientific idea ready for retirement”?

[cross-posted, with minor changes, at the International Cognition and Culture Institute’s blog]

The website edge.org asks every year to a remarkable amount – 175 this time, if I read correctly –  of important exponents of the “Third Culture” a general question on science and/or society. The 2014 question was: “What scientific idea is ready for retirement?

I did not read (yet) all the answers, but I was surprised to see that two of them, from Pascal Boyer and John Tooby, were one and the same: culture. One could take the answers as a provocation of two evolutionary psychology-minded scholars against mainstream cultural anthropology (which I’d subscribe to) and just skip to the others.  However, knowing the work of the two, and, especially, because when people ask me what my research is about I tend to answer “human culture” or “cultural evolution”, I think I have to take this challenge quite seriously.

On one level, I agree completely with the answer: “culture” can not be considered as an unproblematic explanation of phenomena. I was recently reflecting on the fact that, while I consider myself an atheist, I find often unpleasant hearing – and especially pronouncing – profanities. Rationally I know that they are simply a series of sounds, but still I can not avoid to be annoyed.  The imaginary naive anthropologist would say: of course, it is your culture! (I am Italian, and I received a then standard catholic education). But this is exactly what we want to explain: why this specific “cultural stuff” (being bothered by profanities) and not others (say going to church or pray) is still present?

I think that everybody that read this blog would agree that it is not useful to use culture as an explanation: we can not explain X (my problematic relationship with profanities, the readiness to perceive interpersonal threats in the south of USA, etc.) with “culture”.  As Boyer writes in his answer, “that such processes could lead to roughly stable representations across large numbers of people is a wonderful, anti-entropic process that cries out for explanation”. However I feel like this is a starting point. would be interested in X as a “cultural stuff”, and then try to explain it. Boyer and Tooby do not seem to agree: “culture”, in their view, is not only mistakenly used as an explanation, but it is not a scientific concept at all. Tooby writes:

Attempting to construct a science built around culture (or learning) as a unitary concept is as misguided as attempting to develop a robust science of white things (egg shells, clouds, O-type stars, Pat Boone, human scleras, bones, first generation MacBooks, dandelion sap, lilies…)

This is a quite serious accusation. Try to build a unitary explanatory framework for egg shells and first generation MacBooks (who is Pat Boone?) seems indeed a desperate endeavour. Are we in such a situation? An accepted working definition of culture, for people interested in a naturalistic explanation of it, is usually something like “socially transmitted information”. I know this will not satisfy everybody but, for the sake of discussion, let’s assume that one can mostly agree with it (I do).

Now, if we use this working definition to decide what belong to culture, we need to acknowledge that the set has somehow fuzzy boundaries. “Social” transmission  does not isolate precisely some information/behaviours versus others: one of the clearest and most important message of recent cognitive anthropology is that socially transmitted information is in general not simply copied from one head to another, but it is reconstructed using previous individual knowledge. Or, even if we want to give more importance to the “copying” aspect, some information will be more likely to spread because of certain common features of human mind. The same Pascal Boyer has convincingly argued, for example, that minimally counter-intuitive agents, i.e. agents that mainly conform to our intuitive, universal, expectations of how an agent should behave and appear, but have a few violations, are more memorable than completely intuitive ones as well as completely counter-intuitive ones. Superman can fly and has problems with kryptonite, but his behaviour is understandable (he feels lonely, he has a strong sense of justice, etc.).  Shall we consider Superman (or religion, which, according to Boyer is successful – partly – for the same reason) less “cultural” than other domains where individual predispositions are less important? This is clearly not very satisfying.

Also “classic” cultural evolution research has emphasised the importance of social and individual learning being intertwined. There is also a name for this: Roger’s paradox. The anthropologist Alan Rogers (here the original paper) showed, with a simple model, a counter-intuitive result:  in a changing environment, in a population in which individuals are individual learners or social learners, the fitness of the latter, at equilibrium, is equal to the fitness of the former, so that there would not be selection for social learning. In short, this is due to the fact that social learners are “information scroungers” that spare the cost of individual learning but can not track the changes in the environment. While the fitness of individual learners is constant (the benefit of preforming the correct behaviour minus the cost of tune to the environment), the fitness of social learners depends on the composition of the population: the more social learners, the less reliable information, the less the fitness. At equilibrium, Rogers shows, the composition of the population is such that the fitness of social and individual learners is the same. As social learning is everywhere, this has been called a paradox. The “solutions” of Roger’s paradox (see, for example, here and here) all basically involve the possibility that individuals are both social and individual learners.

It seems, then, that it is quite difficult to use “social” transmission to isolate what culture is, as individual learning, as well as universal features of human psychology, are likely to play a role in all instances of social transmission. One could answer: yes, of course we know this is important, culture is “socially transmitted information (in which individual learning, etc. have an important part)”. However, the problem with this definition is that, like in the white-things-science of John Tooby, everything goes. Indeed the diffusion of first generation MacBooks is a good topic for cultural evolution studies, as well, I suppose, the diffusion of possible uses for egg shells (I checked Pat Boone in wikipedia: definitely a topic for us).

Is the situation for “culture” as a scientific concept that bad? I think it is quite interesting to take seriously this criticism and to ponder on the possible problems of the “socially transmitted information” definition. However I am not so pessimist. In a next post (as this became way too long) I will propose a couple of alternatives. One is to drop the “socially transmitted” part (as I suppose anthropologists like Dan Sperber would suggest), and one – which I prefer – involves the idea that studying “culture” does not imply defining a specific domain, but defining how “cultural stuff” are studied, what kind of questions are asked, what kind of properties we are interested in.  Other scientific disciplines, say physics or chemistry, not only studies all white things, but all things, of all colours, and I do not think this would be an argument to retire them.

Of course all this is quite speculative so any comment is more than welcome. And, by the way, a great 2015 to everybody!

Dog movie stars and dog breed popularity

A new research I co-authored with Stefano Ghirlanda and Hal Herzog has just been published in PLOS ONE (the paper is open access and can be found here). In this paper we continue our analysis of dog breeds popularity as a particularly interesting (and data-rich) cultural domain. We had already shown that the choice of which puppy one buys seems largely driven by fashion, i.e. social influence, more than by functional considerations (see my post from last year). Now we looked explicitly at one source of social influence, i.e. movies featuring dogs.

We found that indeed there is a strong effect of movies on the popularity of dog breeds. While this is not probably a shocking result, it is quite interesting to have precise quantitative data. We used the AKC database, totalling over 65 million dog registrations from 1926 to 2005, and analysed a total of 87 movies featuring dogs. The impact of movies has been large. We found, for example, that movies have an influence that can last up to 10 years from the initial release. The 10 movies with the strongest 10-years effect are associated with 800,000 more registrations in the AKC then what would have been expected from pre-release trends. A striking example is the 1959 Disney movie The Shaggy Dog. The registrations of Old English Sheepdogs were stable on around 100 dogs per year in the ten years preceding the release of the movie. In 1969 only, ten years after, 4,226 Old English Sheepdogs were registered.

We also found that the more a movie was successful (we estimated the number of viewers from the opening weekend earnings) the more impacted on the popularity of the breeds of the dog featured. Another interesting finding is that the influence of movies has decreased during the century. Earlier movies are in general associated with larger trend changes than later movies. This suggests that movies – perhaps because of an increased competition with other media, such as television, and, more recently, the internet – have gradually lost their influence on pop-culture.

Stefano made a nice figure showing some of the trends (click on it to see a larger version). Both the figure (here) and the data (here) are publicly available on figshare.com

DogMovieStars

Together with our previous results, which showed that behavioural characteristics, longevity, or health were not correlated with breeds popularity, this new analysis provide a quite clear picture: we do not choose, on average, dogs because they are more healthy or, for example, trainable, but because we see them in the neighbours garden, or in the last blockbuster. Why this is not bad per se (copying what others do is a quite effective strategy in many situations) is definitely bad for dogs. The only feature that we found to positively correlate with popularity is indeed the presence of genetic diseases. Of course this does not mean that dog owners actively look for breeds with genetic diseases, but, as a minimum, that they do not keep this in consideration when choosing a puppy and, more worryingly, that the huge differences in popularity and the rapid increases of some breeds provoke over-breeding which results, in turn, in an increase of genetic disorders. My take-home message here is: don’t follow fashions when choosing a puppy!

Now a couple of more cultural-evolution related questions. First: how important is how the dog is presented in a movie for the effect on the popularity of the breed? We excluded few movies in which the dog was clearly a negative character (Cujo, for example) but we did not analyse in detail this issue. My feeling is that is not so important. While our data end in 2005, the AKC provides the rankings for more recent years. Hal noted the steady increase of French bulldogs (they were at the 54th position in 2003, and at the 11th last year). It happens that in a famous scene of the hugely popular movie The Hangover, Mike Tyson holds in his arm a French bulldog (see the video below from around 1:30). Since the movie is from 2009 (and we do not have the data…) is not clear whether the movie had an influence on the increase on popularity or if it is the other way around (i.e. the authors capitalised on the growing popularity of the breed and used it for the movie), but the dog is not more than a prop in the scene in question. The idea is that the mere presence of a dog in a popular movie makes it accessible and that, as features of different breeds are, in a sense, neutral (see below), a simple advantage in accessibility generates a cascade of effects (e.g. people will talk about that breed more than about other breeds) that may greatly influence popularity.

(the case of French bulldogs is also relevant for the previous point, as French bulldogs carry – in Hal’s words – a huge load of genetic disorders)

Second: does this result suggest that we are copy-machines, easily influenceable by evil Hollywood’s producers? I do not think so. As I mentioned above I consider the choice of a breed as being, by and large, neutral. This does not mean that all breeds are equal (of course they are not). However, given the choice of owning a dog (this, I think, is a non-neutral choice. Would be interesting to see whether movies influences the total number of dogs in time), the features of different breeds can be reasonably adapted to one’s own habits (or the other way around) so that the choice has, in the majority of cases, not enormous effects on the owners. Many people that are buying French bulldogs now would have probably bought poodles fifty years ago. Something similar happens, for example, for baby names (of course they are different; yes, some of them may have an effect on your life [but see here], but, in the majority of cases, being called Alberto or Stefano does not make much difference). For this kind of cultural traits I would indeed expect social influence and media having a strong effect on popularity, but less for traits that implies more important outcomes. We are not blind copy-machines, but selective copy-machines.

Ghirlanda S, Acerbi A, Herzog H (2014) Dog Movie Stars and Dog Breed Popularity: A Case study on Media Influence on Choice. PLoS ONE 9(9): e106565

What is – and what is not – cultural attraction

A couple of weeks ago, I wrote a post commenting on a recent paper relevant for cultural evolution (Claidière et al. 2014 “How Darwinian is cultural evolution?”). The post prompted a lively and interesting discussion in the comments (thanks to everybody!), focusing on the concept of “cultural attraction”, as presented in that paper and in previous works of Dan Sperber (see e.g. the chapter 5 in “Explaining Culture”).

I thought it could have been useful to summarise here the main points of the discussion, to not let them “buried” in the comments. A few cautionary notes before starting: first, if I misinterpret something I’ll be happy to correct it; second, I need to assume that readers know what I am writing about, this is better intended as a quasi-internal minute.

It seems to me that in the comments we clarified trough successive steps what attraction is not, getting closer (at least for who needed it) to a better understanding of what it is, so I will proceed here in the same fashion.

First, cultural attraction is not restricted to cognitive factors. While the work in the cultural epidemiology tradition has emphasised the importance of cognitive factors in cultural dynamics (in a more than well justified opposition to the “traditional” socio-cultural anthropology of few decades ago), cognitive factors are only one of the possible factors of attraction.

Second, cultural attraction is not to be equated with Boyd and Richerson’s content-based biases. As for the first point, probably nobody involved in the discussion was convinced of that, but this identification happens in the literature so it may be not useless to point it out here. As before, content biases may be factors of attraction in particular cases, but nothing more than that.

Also, cultural attraction is not to be equated with Boyd and Richerson’s guided-variation. Again, the work in the cultural epidemiology tradition has emphasised the importance of constructive processes in cultural propagation, but the claim is that cultural attraction is a more general framework that covers both constructive processes and selection (various Boyd and Richerson’s biases) as a special case.

Finally, cultural attraction is not cultural evolution. Mechanisms such as drift (and possibly others) are in fact mechanisms of cultural evolution, but would not fall under the umbrella of cultural attraction, so that the two cannot be considered equivalent.

This work-in-progress schema may be of some help: cultural attraction does not overlap with cultural evolution, as random (?) forces as drift, and possibly others (question mark on the left) are not considered. On the other side, forces as selection, guided-vairation, migration, etc. can be subsumed under cultural attraction.

attraction

I think Dan and Thom made a great job in explaining how exactly attraction should be related to concepts that are already present in cultural evolution and, also, there may indeed be a point in having a general concept (attraction) that “goes together with a unitary way of modelling things”.

Let me finish with three thoughts that may (or not) stimulate further discussion:

1) I think it would be helpful to re-state an explicit definition of attraction. In the paper is written:

the constructive processes we discussed above may tend to transform different inputs in similar ways (rather than randomly), and in doing so cause the outputs to tendentially converge upon particular types, called attractors. This tendency is called cultural attraction.

But this would be again the “narrow” version of attraction (the same happens in the Summary “[…] The process by which they do this is called cultural attraction”), so I assume a more general definition, like this one (also from the paper):

the possibility that every item of every type at t may have some causal effect on the frequency of items of every type at t+1

Or something else?

2) Generality is surely good, but, to use again the biological case as comparison (and keeping in mind the Godfrey-Smith schema): since biologists can usually assume hi-fidelity transmission, they are in the advantage position of being less general. Thus the need for generality in cultural evolution is not good per se, but it is linked to the particular importance of non-preservative processes, which is, again, an empirical question.

3) Finally, a practical question: what should we do with the sophisticated formal models already developed for, say, selection-based processes? Would they need to be rewritten in the more general attraction terms (as the example you give in the paper), or one could – when a cultural domain is considered enough preservative, say first names – keep on using the existent models?

If we’re all cultural darwinians what’s the fuss about?

An important paper from Nicolas Claidière et al., “How Darwinian is cultural evolution?” appeared recently in Philosophical Transactions of Royal Society B. 

Claidière and coauthors adopt a useful schema from the philosopher Peter Godfrey-Smith to distinguish “how darwinian” an explanatory framework can be considered. At the more general level, an explanation can be considered “populational” if considers “a system (such as culture) as a population of relatively autonomous items of different types with the frequencies of types changing over time” (Claidière et al. 2014). A second step is needed to qualify the explanation as “evolutionary”, that is, the frequencies of those types at time are a function of their frequencies at time t-1. All cultural evolution explanatory frameworks are both populational and evolutionary (I do not consider here vast amounts of socio-cultural anthropology).

Things get more interesting at the next two levels, i.e. the “selectional” and the “replicative”. The former implies that the above types should exhibit variation, heritability, and fitness differences, while the latter adds a further constraint, that is that they should also replicate themselves. While only strict memeticists claim that cultural evolution is darwinian in all four senses, Claidière et al. argue that the correct explanatory framework for cultural evolution is not even the selectional one.

The dispute is about the fidelity of cultural transmission. For memeticists, the problem does not exist, as fidelity is sufficient to consider cultural transmission as a proper process of replication (as it is considered in biological evolution). For “standard” cultural evolutionists, rates of mutations of cultural items are higher than in genetic transmission, but it is still useful to consider in general the cultural success of an item as a result of selection among competing variants. According to Claidière et al. however this is, in the majority of cases, incorrect, as cultural traits do not propagate trough a process of copying (with more or less fidelity) but they are reconstructed each time. For example, I am trying here to report with high fidelity the cultural trait “How Darwinian is cultural evolution?”, but I am certainly modifying it, making it shorter in respect to the original version, focusing on parts that am particularly interested, misinterpreting and misunderstanding (my fault) what authors wanted really to transmit. Even worst, what you, reader, will recall of this post, will be even different (if anything). All this, for a transmission chain of two or three passages.

Claidière et al. reformulate and extend a concept that the anthropologist Dan Sperber proposes from a long time: cultural evolution forces are better thought in terms of attraction then in terms of selection. The various forces that transform cultural items during the reconstructive processes are not random, but they tend to act in a consistent, even when weak, direction, making cultural outputs converge toward particular “attractors”. Sperber and colleagues generally focuses on cognitive forces. For example, some features of a story are easier to remember than others, and they will serve as attractors when the story is re-constructed. Eric Havelock (about which I read in Rubin, 1995) suggests that this is indeed a function of heroes and gods in epics and ballads that were orally transmitted. Heroes and gods are “bags of attractors” (that’s neither Havelock nor Rubin expression), as they have fixed and concrete features that are easy to image and to remember, which help narrators both to describe abstract concepts and to organise the narration in familiar sequences (Levi-Strauss often cited aphorism on animals “good to think with” should go in a similar direction).

While I am generally sympathetic with this proposal (as well as a Dan Sperber’s fan), I think there are few points worth to discuss. The first concerns the notion of “attraction”, and the fact that is often understood in different ways (and the effort of Claidière et al. to present a clear definition is certainly welcome), being sometimes equated to Boyd and Richerson’s content bias (by me, for example). The second, more interesting, concerns the issue of reconstruction versus replication preservation. The question whether cultural propagation is better described as one or the other is an empirical one, and the answer varies for different cultural domains. Claidière et al. agree with that, but claims that “a large number” of cultural propagations are results of reconstructive processes. Perhaps. Without entering in technical details on how exactly copying fidelity should be considered (which are anyway useful), there should be a continuum between ideally pure individual innovation and virtually error-free copying (this continuum being wider than in the biological case), and, depending on the domain we consider, we may want to “move” in the Godfrey-Smith’s schema.  I’ll try to write more on that soon.

[Much more interesting stuff below in the comments. Thanks in particular to two of the authors of the paper discussed, Thom Scott-Phillips and Dan Sperber, and to Alex Mesoudi and Tim Tyler. Also, the discussion continues here.]

“Journal of Cultural Evolution”: some material to discuss

In preparation of the meeting of next week (13:00, Wednesday 9 April at EHBEA in Bristol, see my previous post and the conference program), I post here some material we plan to discuss.

On the operative side there is one important news: we had a meeting with Peter Turchin (see his excellent Social Evolution Forum) who proposed the possibility to join forces. Peter is the editor in chief of “Cliodynamics: The Journal of Theoretical and Mathematical History“. In short, this option would involve broadening the scope of the existent journal (now mainly focused on historical, long-term, processes) to include other dimensions of cultural evolutionary studies, and changing the title – and renewing the editorial board – so to reflect the new scope. Notice this option will depend both on what we will discuss on the meeting and on the decision of the current editorial board of  Cliodynamics.

The journal currently publishes peer-reviewed articles in electronic-only form, and it is based on the eScolarship platform from the University of California.  Access is completely free (as it happens, in general, in Open Access journals), and no fees are required to publish (as it does not happen, in general, in Open Access journals). This model can be sustained by a mix of voluntary work and external fundings: if I understood correctly, a person supported by a grant is currently working part-time on it, and this grant will last for the next three years (so that, in principle, we would not necessary need, at least for the first period, other fundings).

An appealing aspect is that the journal has been submitted almost three years ago to Thomson Reuters’ review, so that, if the process will go smooth, it will be soon indexed in the Web of Science, which means, notably, that it will have an Impact Factor. (However, it is very important to understand exactly the effect of a potential change of name, scope, etc. on this process).

If one considers this publishing model appropriate, there are several advantages in pursuing this option, including importantly that the “platform” (by which I mean organisational as well as technical aspects) is already in place, and it could be used for a relatively prompt launch (“prompt” being intended with reference to the publishing time system).

For the sake of debate, one might legitimately prefer a more traditional publishing model, so to be sure to have on the side an experienced publisher and to concentrate on the more “scientific” aspects of the endeavour. Also, I understand a certain psychological attraction of having a “shiny” new start of the enterprise. Finally – but this may be my idiosyncrasy – why all the not-from-a-big-publisher academic journals that I know seem to look aesthetically unpleasant? Does it need to be like that?

See you in Bristol to discuss about it  – and, again, comments below are encouraged!

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