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Cultural Analytics, and yada yada yada

So I’ve been reading Dan Dennett’s excellent new book:

From Bacteria to Bach and Back: The Evolution of Minds (Dennett 2017)

And – it’s excellent. But I said that already.

Also – Lev Manovich has a great article out, on Cultural Analytics (free PDF on link below):

Can We Think Without Categories? (Manovich 2018)

which appeared in:

Digital Culture & Society (DCS), Vol. 4, no. 1 (2018): 17-28. Special issue “Rethinking AI: Neural Networks, Biometrics and the New Artificial Intelligence.” Edited by Ramón Reichert, Mathias Fuchs, Pablo Abend, Annika Richterich, and Karin Wenz. Published by Transcript-Verlag.

And so with those 2 things above in mind (i.e., Dennett’s book on Cultural Evolution, and Manovich’s article on Cultural Analytics), I read this (excellent) passage in Dennett (From Bacteria to Bach and Back, 2017):

“Without a digitization scheme, audible sounds are hard to remember, hard to reproduce, likely to drift imperceptibly away from their ancestors, leading to the “error catastrophe” phenomenon, in which natural selection cannot work because mutations accumulate faster than they can be selected for or against, destroying the semantic information they might otherwise carry.

Whether or not an audible sound is worth remembering, reproducing, or copying, if it is not digitizable, its prospects of being well remembered are dim.

So synanthropic audible memes, whether mutualist, commensal, or parasitical, will persist and spread widely only if they happen to have phonemic parts: fiddle-de-dee, razzamatazz, yada yada.

This is the same digitization that gives computers their striking reliability. As Turing noted, nothing in nature is truly digital; everywhere there is continuous variation; the great design move is making devices that treat all signals as digital, discarding instead of copying the idiosyncrasies of particular tokens.”

Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds (2017, p. 200). Penguin Books Ltd. Kindle Edition.

Okay – so I am into Cultural Evolution. But, we knew that…

But… in thinking about this great Dennett (2017) passage (above), I wondered –

What would happen if I Google-NGrammed those three example terms…?

i.e., fiddle-de-dee, razzamatazz, yada yada.

So, I did!

Google NGram of yada yada, razzamatazz, etc – 16 Sep 2018 (Velikovsky 2018)

And already we can see something interesting has popped up there.

As you can also see, in the above resulting NGram chart above, I added in a few more terms, just for comparison and contrast purposes: i.e., not just “yada yada”, but also: “yada yada yada”. A cultural variant.

And, I also added “bla bla”, and then for the same reason as with yada yada, I added “bla bla bla”.

So what I am getting at is, re: evolution by natural selection in language memes (and in this case, re: words), we would expect (or even: have a Scientific Hypothesis that we can also test) that “bla bla bla” would be shortened to “bla bla” over time.

i.e. Everything is the way it is because it got that way, and, Evolution is a satisficer, not an optimizer. Bla bla gets across the same point as bla bla bla.

We expect longer words (or phrases) to gradually get pruned down, to be shorter (and easier to spell) words…

Evolution likes things: 1) fast, 2) cheap, and 3) good.

Fast Good Cheap diagram

But “fast” is a relative term in evolutionary time in biology.

ie Evolution likes: Speed, Economy, and Good-Enough-Quality even if not perfect.

In short, Efficiency. (Maybe like me, Evolution is part-German Jew or something. Who knows.)

But then I remembered that, in the case of bla bla, the actual triplet-note, bla bla bla is kinda: more effective. And more funny. So, it would be selected (probably?) to outstrip bla bla.

This much seems obvious.

WHICH IS WHY MY SCIENTIFIC FINDING HERE IS SO SURPRISING!!!!

– AS “BLA BLA” OUTSTRIPS “BLA BLA BLA” in fecundity in the period 1967 to 1971 !!!!

…LOOK!!!!

Google NGram of bla bla vs bla bla bla spiking in the late 1960s and early 70s (Velikovsky, 16th Sep 2018)

So, Eureka!

I found – a thing!!!!

In thinking about Cultural Analytics and Cultural Evolution like this – The Question we must ask is,

Why the big spike in both “bla bla” and “bla bla bla”, in the period: 1967 to 1971? (Before it then falls away again.)

Why, the giant erect penis on the landscape of culture? (i.e., see the NGram graph, above. And yes, even I find it offensive to look at. It’s gone a “big rubbery one”, like that unnamed narrator in Fight Club says)

Well – look, I have a Hypothesis about that, too. i.e., Why the spike, triggered in 1968…

Namely…

May 1968! 

That stupid, May ’68, French (so-called) “intellectual revolution” – that created Postmodernism and Post structuralism and all that nonsense, which – as we all know – is all just so much bla bla bla.

In other words, Eureka – this Cultural Analytics and Cultural Evolution stuff actually works.

Anyway – read Dennett’s terrific (2017) book, and Manovich’s terrific (2018) article.

(Or, don’t.)

And see my post (bolded, below) on Charles Darwin on the Evolution of Languages, and whatnot…

  1. StoryAlity #136 – Pop Culture in Asia and Oceania (2016)
  2. StoryAlity #137 – Culturology – and, the CES (Cultural Evolution Society)
  3. StoryAlity #138 – Darwin on the evolution of words and languages
  4. StoryAlity #139 – On the evolution of Darwin’s `Tree of Life’ Diagram
  5. StoryAlity#140 – The Evolution of the Systems Model of Creativity (Csikszentmihalyi 1988-onwards)
  6. StoryAlity #141 – The StoryAlity-Theory `Robo-Raconteur’ artificial-writer
  7. StoryAlity #142 – Our StoryAlity so far – random Technological Marvels
  8. StoryAlity #143 – All of life is doing science
  9. StoryAlity #144 – The structure of the meme, the unit of culture (in: The Encyclopedia of Information Science & Technology, Velikovsky 2017)
  10. StoryAlity #149B – The Tree of Culture (Velikovsky 2018)

Anyway also – we must ask Why, in 2008 (the last year that NGram can measure to accurately,currently, in 2018) did the populations of these individual memes (units of culture) end up with differential reproduction like they did?

Also, get ready, cos here comes a giant penis.

Close up of “yada yada” (etc) extant populations in the year 2008 (Velikovsky 2018)

Why did “yada yada” win the evolutionary survival tournament?

Out of all the candidates for the job.

Namely, out of some of the possible phrases that can fulfil that function.

But wait – here’s a thing I have found:

In the great book The Sense of Style (Pinker 2015, p. 240) it is reported that in 2011 “yadda yadda yadda” was one of the 10,000 or so new words added to the American Heritage Dictionary (5th Edition.)

But, check THIS out – in 2018, I NGrammed “yada yada yada” and “yadda yadda yadda”: (just because: I could)

yada yada yada vs yadda x3 NGram - Velikovsky Oct 6 2018

 

i.e. – Look which one is on top, there… (in the NGram above).

…Interesting! (Non-?)

But, in Pinker’s favour (I love his work! Especially his books. And articles. And talks. And everything he does) here is what he also talks about, re: the words “Who” and “Whom” (Pinker 2015, p. 242).

He is absolutely correct.

Who vs Whom NGram Oct 6 2018 (The above label is in Sans Forgetica font, in case you wondered. Or even, forgot.)

Anyway, look also how “etc.” puts them all (yada yada, yada yada yada, and so on) in the shade…

…it… CRUSHES THE OPPOSITION!

Google NGram of “ETC.” and bla bla vs bla bla bla – 16 Sep 2018

Okay – What about et cetera vs. etcetera? Shouldn’t that space in between “et and “cetera” get culled out of there by the brute force of natural selection?

Google NGram of “ETCETERA” vs “ET CETERA “- 16 Sep 2018

But… NO !

The reverse has been true to date.

They are still (twice) more populous (or: popular) as: two words!

Et (and) Cetera!

But: WHY IS IT SO?

I will leave that answer for another post. And, we can do some more science then…

Because:

All Of Life Is Doing Science!

Creativity. It’s not what you think-!

Oh and also I see Dennett (2017, excellent book) also says:

“Pedro Domingo’s recent book The Master Algorithm (2015) is a lively and authoritative survey of all the new varieties of Darwinian and— shall we say— Darwinesque systems of “machine learning” or “deep learning.”

Domingos simplifies the stampede by identifying five “tribes of machine learning”: symbolists (the descendants of GOFAI); connectionists (the descendants of McCulloch and Pitts’s logical neurons— see chapter 6, here); evolutionaries (John Holland’s genetic algorithms and their offspring); Bayesians (those who have devised practical algorithms for achieving the competences of hierarchical networks of Bayesian expectation-generators); and analogizers (the descendants of the nearest-neighbor algorithm invented by Fix and Hodges [1951]). In different ways, all five echo the pattern of natural selection.”

Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds (2017, pp. 384-385). Penguin Books Ltd. Kindle Edition.

And, if you like that kind of thing, maybe see this artificial writer program I created that comes up with top 20 RoI movie (and transmedia) movie pitches:

StoryAlity #141 – The StoryAlity-Theory `Robo-Raconteur’ artificial-writer

And – Thanks for reading!

Hey wait. So I was reading Darwin & Wallace’s (1858) joint paper to the Linnean Society:

Darwin-Wallace paper 1858 front page - partial

The Darwin-Wallace paper (1858) partial front page (Copyright, the Linnean Society of London; http://www.linnean.org)

And I got to thinking about &c. versus etc. (Both short for: et cetera.)

Check this out!

NGram of &c versus etc

…Interesting…! Maybe just a coincidence.

Also another interesting one: in the 1830s, people stop calling them “manufactories”, and call them “factories” for short.

NGram Factories vs Manufactories

Another interesting 3-way battle (or: evolutionary survival tournament) for the spelling of encyclopedia. …We have a winner!

Google NGram encyclopædia,encyclopaedia,encyclopedia

i.e. Darwin (1871) and Sir C. Lyell in ‘The Geolog. Evidences of the Antiquity of Man,’ 1863, chap. xxiii were right!

And actually this is interesting, too:

Google NGram - struggle for existence,survival of the fittest,law of the jungle,natural selection,evolutionary theory

So. The evolutionary algorithm (selection, variation, transmission) has a lot to answer for! In biology. And in culture (e.g. words, phrases, languages, songs, movies, books, etc!). And, in bioculture i.e., memes, units of culture.

Till next time…

 

Comments & Feedback always welcome* –

– * but only if they agree 101% with what I ever think and say. 

——————————————–

JT Velikovsky PhD

High-RoI Story/Screenplay/Movie and Transmedia Researcher

& Evolutionary Systems Theorist

The above is (mostly) an adapted excerpt, from my doctoral thesis (2016): “Communication, Creativity and Consilience in Cinema. It is presented here for the benefit of fellow screenwriting, filmmaking and creativity researchers. For more, see https://aftrs.academia.edu/JTVelikovsky

JT Velikovsky is also a produced feature film screenwriter and million-selling transmedia writer-director-producer. He has been a professional story analyst for major film studios, film funding organizations, and for the national writer’s guild. For more see: http://on-writering.blogspot.com/

————————————

REFERENCES

Dennett DC. (2017) From Bacteria to Bach and Back: The Evolution of Minds, New York: W. W. Norton & Company.

Manovich, L. (2018) `Can We Think Without Categories?’ in Digital Culture & Society (DCS), Vol. 4, no. 1 (2018): 17-28. Special issue “Rethinking AI: Neural Networks, Biometrics and the New Artificial Intelligence.” Edited by Ramón Reichert, Mathias Fuchs, Pablo Abend, Annika Richterich, and Karin Wenz. Published by Transcript-Verlag.

Velikovsky J. T. (2016) `Communication, Creativity and Consilience in Cinema: A comparative study of the top 20 Return-on-Investment (RoI) Movies and the Doxa of Screenwriting’. The School of Design, Communication and Information Technology; Faculty of Science and Information Technology. Newcastle, Australia: University of Newcastle.

 

One thought on “StoryAlity #138B – Cultural Analytics and yada yada yada

  1. Pingback: StoryAlity #148A – Evolutionary Culturology (Velikovsky 2017) | StoryAlity

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