“It’s winner-take-all in the lobster world, just as it is in human societies….”Page 8 – 12 Rules for Life
Derek J. de Solla Price in 1963 noticed something rather interesting, namely that half of the published papers within a given area came from the square root of all the authors of those papers.
If there is a scientific area that has 100 papers published, written by 25 different authors. 50 of these papers will have come from just 5 authors.
This is “Price’s Law” and it doesn’t seem to just describe the authorship of scientific journals. It seems to suggest: 50% of Something, will be attributed to the square root of those contributing to the something.
Dr Peterson in 12 Rules mentions it also applied various things, including to the population distribution in cities. I was interested in taking a look at that claim.
In the United Kingdom, there are 69 Cities, so we can predict that just 8 of them will hold 50% of the population of all of them. Let’s have a look.
I calculated the total population of cities within the United Kingdom to : 22,800,000 (With the inclusion of London as a City, though not strictly a city as per the definitions of other cities within the list – Data from Wikipedia)
Therefore, we expect the first eight cities to have 11 Million People.
So we ended up with 13,093,892 – This is 59% of the total population of all the cities within the United Kingdom. This isn’t far off what is predicted when we modelled the population using Price’s Law.
Inequality is inevitable?
It appears, given that Price’s law describes with reasonable accuracy certain systems, and Pareto distribution[ Editorial Note: Post about Pareto will follow] describes others. That large scale systems tend towards inequality. No matter if its the distribution of the population among cities, the mass of stars in a solar system, or the wealth among the population.
The successful get more successful exponentially, and the unsuccessful fail more and more exponentially!
What is the take away?
We can be mindful that the systems we are involved in will possibly tend towards inequality. It would be interesting for example, to monitor a classroom. Do the clever children get smarter and smarter, and the less well adjusted children full further behind (Perhaps the opposite?)
Maybe if you run a chain of shops, if one or two stores start outperforming the rest, do we subconsciously devote more resources to them allowing to continue their rise at the above their peers who fall further behind?
In my job, I considered the following; I was part of a team of ten, that contributed to on average 19,500 units of work a month. Therefore there were probably three people within that team who contributed 9,750 units, or 3,250 units each per month. I sat down with the supervisor and looked at my productivity from November.
We calculated that on average, despite not being at this location full time since November (I am primarily field-based but have spent a longer time than usual at one location recently for various reasons)and I was completing 4000 units of work a month so well within the bracket.
An analysis like this could possibly be utilized in say, a performance/pay review meeting. As a colleague, you could perhaps argue that you deserve a higher reward for sitting in the bracket.
How else could we utilize Price’s Law?
What studies are you aware of that involve Price’s law, please share with us!