Fame and accomplishment

From Is fame fair? by Amy Yu and César A. Hidalgo reporting on this original research, Pantheon 1.0, a manually verified dataset of globally famous biographies by Amy Zhao Yu, Shahar Ronen, Kevin Hu, Tiffany Lu & César A. Hidalgo.
Hufton:

Is fame superficial? Or can it be a signal of accomplishment?

In a world where many media outlets seem dominated by characters of inexplicable fame (such as the Kardashians), asking ourselves if our social reward systems are misfiring is both a fair question and a relevant one. The relevance of this question stems from the fact that humans are social learners – we are a species whose success depends on the ability of individuals to learn from others. But choosing whom to learn from, in a world populated by more people than we can meet, is not easy. To facilitate those choices, humans have evolved cognitive biases that nudge us to learn from those who demonstrate skill, accomplishments, and also, fame or prestige[1].

So the question of whether social recognition is fairly attributed is relevant, because a world that attributes popularity unfairly is also a world where people are nudged to learn from inadequate models.

But the conspicuous fame of teen icons and reality show celebrities is not enough evidence to conclude that our social rewards systems have gone berserk. To test this conclusion we need statistical evidence, instead of anecdotes, since these examples could well be outliers in what is otherwise a world where the correlation between fame and accomplishment is strong. But how can we test that alignment? Do we even have the data that we can use to create proxy measures for fame and accomplishment?

In our paper published today in Scientific Data, we introduce the Pantheon 1.0 dataset, a dataset that measures the historical fame of all of the individuals in human history that are recorded in more than 25 languages[2] in Wikipedia. The Pantheon 1.0 dataset annotates each individual with their occupation, demographics (year and country of birth), and several metrics of popularity (derived from the number of language editions in Wikipedia and the pageviews received across different languages). But what makes the Pantheon dataset special is that it focuses on a multilingual corpus (more than 200 language editions of Wikipedia), and it introduces a detailed taxonomy of occupations that classifies biographies into 88 distinct categories. The multilingual nature of the Pantheon dataset allows us to focus on globally famous individuals, while discarding those who are only locally famous (for instance, most American Football Players, who are popular in the United States, but unknown for the rest of the world, do not make the cut). Our taxonomy of occupations, on the other hand, allows us to identify individuals that have made similar contributions, allowing us to test the alignment between fame and accomplishment for narrowly defined groups of individuals.

Read the rest of the article for further details. The researchers have done a good job of trying their best to remove biases of one sort or another. Charles Murray had a go at this back in 2004 with Human Accomplishment. His effort was understandable and well intentioned but the various compromises he had to make given the data sources with which he was working made the conclusions reasonable but suspect.

Based on the new data from Ye at al, does fame correlate with accomplishment? Yes!

In all cases we find a positive correlation between accomplishments and fame, meaning that more accomplished athletes tend to be also the most famous ones.

Yu et al go a reasonable way towards addressing some of the more structural issues faced by Murray. They are also very forthright about the limitations. There are two structural issues which they don't discuss much but which I suspect are material.

The first issue is that any one individual, in their approach, is slotted in a single category of achievement. There are individuals whose fame is for other reasons than just the field of their accomplishment and there are individuals who have multiple fields of accomplishment without associated fame.

As an example of the first issue take the anomaly that they point out.

Of course, there are clear outliers, like Anna Kournikova in tennis, who is more popular than what her accomplishments can explain.

Kournikova was accomplished as a tennis player but she was also blessed with good looks and a post-tennis celebrity status that almost certainly explains the discrepancy between achievement and fame.

An example of the second category are people who have achievements in multiple fields. Edwin Land who was a scientist, inventor and businessman with significant accomplishments in all three fields but apparently insufficient collectively to make the grade for this data set.

Finally there are those who one might argue deserve fame and recognition for the impact of their accomplishments but who have never received it. This is theoretically a real issue but the first five names I thought to test actually do show up on the list.

So there are still issues but this is a good move forwards. I tested a couple of hypotheses.

Over the years I have observed that in most fields of contemporary accomplishment women usually represent about 15-30% of the top performers in any given field. This has primarily to do with hours invested in the endeavor and continuity of effort over the years. High achievement is usually achieved primarily through endless hours of practice.

Does that rule of thumb play out with the new data set? Yes.

For the whole data set, 13% of the 11,341 exceptional performers are women. However, the dataset goes back 2,000 years. What about in contemporary times? I limited the search those born after 1945 as a demarcation of the modern era. With that restriction, 22% of the exceptional performers are women, smack in the middle of the range I had observed.

Interesting. From this whole database, we can conclude that if you are famous, there is a good chance that you are also accomplished. However, there is a missing element. We don't know whether, if you are accomplished, that will lead to fame.