This new paper may be of relevance (H/T Steve Hsu). The abstract:
The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, efforts or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success. But, as a matter of fact, it is rather common to underestimate the importance of external forces in individual successful stories. It is very well known that intelligence or talent exhibit a Gaussian distribution among the population, whereas the distribution of wealth—considered a proxy of success—follows typically a power law (Pareto law). Such a discrepancy between a Normal distribution of inputs, with a typical scale, and the scale invariant distribution of outputs, suggests that some hidden ingredient is at work behind the scenes. In this paper, with the help of a very simple agent-based model, we suggest that such an ingredient is just randomness. In particular, we show that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals. As to our knowledge, this counterintuitive result—although implicitly suggested between the lines in a vast literature—is quantified here for the first time. It sheds new light on the effectiveness of assessing merit on the basis of the reached level of success and underlines the risks of distributing excessive honors or resources to people who, at the end of the day, could have been simply luckier than others. With the help of this model, several policy hypotheses are also addressed and compared to show the most efficient strategies for public funding of research in order to improve meritocracy, diversity and innovation.
Huh, I am surprised that this got published. The model proposed seems almost completely equivalent to the O-ring paper that has a ton of literature on it, that had roughly the same results. And it doesn’t have any empirical backing, so that’s even more confusing. I mean, it‘s a decent illustration, but it does really seem to not be saying anything new in this space.
They also weirdly overstate their point. The correlation between luck and talent heavily depends on the number of iterations and initial distribution parameters their model assumes, and they seem to just have arbitrarily fixed them for their abstract, and later in the paper they basically say “if you change these parameters, the correlation of talent with success goes up drastically, and the resulting distribution still fits the data”. I.e. the only interesting thing that they’ve shown is that if you have repeated trials with probabilities drawn from a normal distribution, you get a heavy-tailed distribution, which is a trivial statistical fact addressed in hundreds of papers.
I am surprised that you are surprised that this got published. It reinforces and claims to provide proof towards the worldviews currently ascendant in academia, strengthening politically convenient claims and weakening inconvenient ones. Overstatement of the result also seems par for the course. That doesn’t make it useful, or anything, but it all seems very unsurprising.
Yeah, I was just thinking about me saying that while I was standing in the shower. I actually planned to remove the “I am surprised that this got published” line, because I wasn’t actually surprised. I think implicitly I probably just wanted to reduce the status of the associated paper, and question its legitimacy, and it seems that the cached phrase I currently have for that is “I am surprised this got published”, which really doesn’t seem like the ideal phrase for that, but does seem pretty commonly used for precisely that purpose.
This new paper may be of relevance (H/T Steve Hsu). The abstract:
Huh, I am surprised that this got published. The model proposed seems almost completely equivalent to the O-ring paper that has a ton of literature on it, that had roughly the same results. And it doesn’t have any empirical backing, so that’s even more confusing. I mean, it‘s a decent illustration, but it does really seem to not be saying anything new in this space.
They also weirdly overstate their point. The correlation between luck and talent heavily depends on the number of iterations and initial distribution parameters their model assumes, and they seem to just have arbitrarily fixed them for their abstract, and later in the paper they basically say “if you change these parameters, the correlation of talent with success goes up drastically, and the resulting distribution still fits the data”. I.e. the only interesting thing that they’ve shown is that if you have repeated trials with probabilities drawn from a normal distribution, you get a heavy-tailed distribution, which is a trivial statistical fact addressed in hundreds of papers.
I am surprised that you are surprised that this got published. It reinforces and claims to provide proof towards the worldviews currently ascendant in academia, strengthening politically convenient claims and weakening inconvenient ones. Overstatement of the result also seems par for the course. That doesn’t make it useful, or anything, but it all seems very unsurprising.
Yeah, I was just thinking about me saying that while I was standing in the shower. I actually planned to remove the “I am surprised that this got published” line, because I wasn’t actually surprised. I think implicitly I probably just wanted to reduce the status of the associated paper, and question its legitimacy, and it seems that the cached phrase I currently have for that is “I am surprised this got published”, which really doesn’t seem like the ideal phrase for that, but does seem pretty commonly used for precisely that purpose.
Link to the O-ring paper?
Wikipedia: https://www.wikiwand.com/en/O-ringtheory of_economic_development
Original: https://www.jstor.org/stable/2118400