One of the ideas that I am exploring in my work-in-progress book Breeders, Propagators, & Creators is that human beings face a fundamental trade-off between three activities:
- Breeding: behaviors that lead to the production of offpsring (which might — but does not necessarily — include parenting);
- Propagating: behaviors that spread existing cultural ideas; and
- Creating: behaviors that introduce novel cultural ideas.
If there is a trade-off between these three activities, we should see inverse correlations whenever we compare their prevalence. In other words, an entity that does a lot of breeding should do less propagating and creating.
This sounds logical, but the problem is this: measuring cultural propagation and creative output is far more difficult than measuring reproductive output. You can count the kids — you can even do DNA testing to confirm reproductive success — but it is hard to count cultural transmission and perhaps even harder to tally up novel contributions to culture. But these critical cultural behaviors occur, so even if they are hard to measure, we still ought to try.
Right now I am diving into the literature on cultural transmission, so I will tackle the propagation issue at a later date.
But I was particularly interested in the question of creation as it trades off with propagation and breeding. Perhaps my special interest stems from where I teach: a top-flight art, design, & architecture university. I see the incredible dedication that my students and colleagues have to their crafts, and I can’t help but imagine that that dedication has a cost. Do people give up the opportunity to participate in wider culture, or to have children, in order to make novel contributions to the culture?
To answer this question, you need data. That data needs to provide an estimate of culturally-creative output as well as fertility. There are a number of scales (“entities”) at which this data could be collected, but it would be ideal to have data points for individual people. In my dream research scenario, I would be able to measure the lifetime creative outputs and reproductive outputs of thousands of individuals.
Unfortunately, I don’t have this data. But I have uncovered an interesting source of data on the creative output of different countries. This data was compiled and (it is important to note) derived by the Martin Prosperity Institute (MPI), a think tank in Toronto, Ontario, Canada. Every year, the MPI publishes a report called the Global Creativity Index (GCI). I used their most recent report, published in 2015. This index is not a direct measure of success at introducing new cultural ideas; it is not a “creative fitness” metric. Instead, it is an indirect measure of the overall creative environment of a country; the authors of the index have shown that this measure correlates roughly with the creative output of these countries.
The GCI considers a variety of factors, including what share of the population is in the “creative class”: professions that create new ideas. The GCI also considers the creative environment of a country. The authors of the GCI argue that three environmental factors foster creativity — technology, talent, and tolerance — and they use various measures to estimate the quality of these environmental factors in each country. The GCI represents a rather monumental and aspirational effort to understand the factors that foster innovation in a country. It also is a rough and indirect metric, measured at a very coarse scale. For me it is valuable data, despite its shortcomings.
Apparently no one has ever asked a pretty basic question: how does the GCI correlate with fertility? As I have indicated above, I would be much more excited to have data on individual creative output compared to individual fertility, but this country-scale data is still interesting.
So I took the GCI 2015 data and added data on national fertility rates obtained from the Population Reference Bureau (these data can also be obtained from the United Nations Population Division). Here’s the resulting graph of national creativity versus national fertility:
I have not peformed any statistical analysis on this correlation yet, but the visual pattern tells a lot of the story. First of all, there are some “trends at the extremes” that frame a basic trade-off between fertility and creativity: all of the countries with the lowest GCI have relatively high fertility, and all of the countries with the highest GCI have below-replacement fertility rates. So the trade-off that I hypothesized must exist does appear to exist, albeit roughly.
But there’s also an interesting secondary trend here that complicates the story: many countries with very low fertility have a relatively low GCI. That is to say that lowered fertility is no guarantee of high GCI. I suspect that this result would not surprise the researchers who produce the GCI: while creative pursuits probably preclude having lots of offspring, it does not appear that lowering fertility necessarily results in higher creative output. A potential explanation of the “floored” quality of the data on this graph is that many countries pursue propagation in lieu of fertility. Perhaps the low-fertility, low-GCI countries propagate a lot of existing culture rather than being centers of creative innovation. I will be chasing that data in the near future, as I would love to have a three-dimensional graph of national fertility versus national creativity versus national cultural propagation.
I am well aware of how far away these data are from actually establishing a breeding-propagating-creating trade-off in individuals. But these national trends are intriguing, and suggest that my idea is viable.
You can download an Excel Spreadsheet version of this raw data here.A Major Post, Behavior, Breeders, Propagators, & Creators, Cultural Evolution, Data Limitation, Gene-Culture Coevolution, Human Evolution, Hypothesis Testing, Memetic Fitness, Reproductive Fitness, Sex and Reproduction, Sociology