This perspective on human performance is super interesting!
Many of our stories about "genius," "superstars," and high performers are grounded in assuming that the patterns of early learning will extrapolate to the rest of life - e.g., child prodigies, gifted students, and those with early steep curves on the achievement trajectory. But what happens when you expand the window of observation?
This review challenges some of our long-standing myths about high performance. They suggest:
"The pattern of predictors that distinguishes among the highest levels of adult performance is different from the pattern of predictors of early performance. Higher early performance in a domain is associated with larger amounts of discipline-specific practice, smaller amounts of multidisciplinary practice, and faster early discipline-specific performance progress."
Justice for multidisciplinary practice!
"By contrast, across high levels of adult performance, world-class performance in a domain is associated with smaller amounts of discipline-specific practice, larger amounts of early multidisciplinary practice, and more gradual early discipline-specific performance progress."
Parallels to my own developer science work:
- I have emphasizes that short-term payoffs can distract software teams from recognizing the long-term damage of cycles like learning debt, or engaging in contest cultures. Broadening the window of observation is crucial for seeing not just the "line go up" immediate response, but the "line crash down" that happens when your psychological environment is damaging
- aptitude is not achievement! It's important to know that we can see lower levels of achievement associated with certain strategies at a certain point in time, but those same strategies will yield HIGHER achievement over time! There are many complex effects here, like protective effects from certain strategies that only come to light under challenge, or thresholds after which the longer-term strategies pay off more.
This is all part of the beautiful, incredibly complex science of achievement!
This kind of pattern also challenges long-standing myths about coder talent and what we think predicts what.
Should you always prioritize demonstration of early hyper-specialization when you're hiring programmers? If we overweight that at scale (which cultural beliefs about genius and ability are good at making us do!), we may be cutting ourselves off from the multidisciplinary problem-solving that our organizations will need to face complex challenges.
One of the authors chatting about the selection effect issues I and others have wondered about and clarifying goals of the claims:
https://bsky.app/profile/brookemacnamara.bsky.social/post/3mahqgzo2hk2l
Exactly WTF is peak performance?
No developer/manager can be at peak daily
No task/solution can be written at peak always
So comes the classic books like ,The mythical Man-Month’ then ,Peopleware’ …
It is really important to focus on overall team performance/productivity/market goals
But then this is what separates an effective –to avoid peak— team/project managers to rise
Because aside dealing from distractions:
1 teams ideas towards innovate solutions vs simply basic tasks implementation delivers
2 customers/market demands towards last issue/trends vs delivering product solutions
3 top management availability to provide proper resources in time vs distractions
…
Hey, I may name overweight, but that has nothing to do with me being hyper or being a bad programmer.
- bad early morning social media reading skills
@grimalkina Hyper-specialization requires a societal substrate to support it. To early and the web is too fragile, the specialist needs the support of the generalist to fill the gaps.
Over time, if the society grows large enough, the gaps between the nodes in the mesh narrow as normal randomization within standard distribution spreads. This allows more specialization within the same structure without requiring changes to the constraints of the overall system.
The specialist can be equally well supported in either case, though that support must be there or they will collapse. Project the singular case upon an entire society where the ratio of specialist to generalist is skewed and my feeling is that would ultimately lead to collapse
Take what you would from that as metaphor for specialized or exceptional workers in a typical corporate environment.
@grimalkina The question would be whether hyper-specialization limits peak performance, or simply takes a person to their peak and then is not productive. People with a higher peak may need less hyper-specialized practice to reach it, and therefore have energy left to broaden their interests and reap the benefits of cross-disciplinary practice.
Hard question to test...
@grimalkina having digested this a bit, our question is
is interdisciplinary research and practice so fruitful because of something fundamental, or because that's the thing we've denied ourselves by shaping society to avoid it, so it's where the low-hanging fruit is?
@grimalkina Anecdotal: I've been a 99th percentile on every standardized test I've ever taken.
Being "smart" is tremendously overrated.
Tho, I will say, there are girls who are hot for a walking encyclopedia, and I found one. My stock has fallen somewhat, since cellphones and wikipedia, but I still got chops.
"British slang for narc, sweetpea."
"Henry is capo di tutti capo, but Norfolk is a very strong lieutenant."
"Lionel Hampton on the vibes, Benny played with equals."
@grimalkina A weak point: sephardic mediterranean men, strong noses, olive skin, curly dark hair, who are foresters.
Easily managed.
I was once on a gig in Maryland, a short drive, and she wanted to come up to hang with me on the weekend.
I was like, "No, my love, I will be working this weekend, I'll be no fun."
There was a fucking *forestry* convention at the hotel I was staying at.
There were *hundreds* of them.
@grimalkina Extremely interesting, though I've seen comments that this could be just collider bias, and I have to admit that this seems like a very valid counterargument.
EDIT: A more detailed version of the argument is at https://zenodo.org/records/18007684
Güllich et al. argue that among elite performers there is a negative association between early and adult performance, a pattern they link to distinct developmental causal mechanisms for early, and adult elite performance. Using simple simulations, we show that this pattern arises naturally from collider bias when selection into elite samples depends on both early and adult performance, and/or from other biases like base rate neglect. We then revisit the data leveraged by Güllich et al. and highlight how in numerous instances early and late peak performance are highly positively correlated. While associations estimated within elite samples are descriptively accurate for the selected population, they are causally misleading, and should not be relied on to infer developmental mechanisms of elite performance without explicit modeling of the selection processm, accounting for base-rates and minding other statistical biases.A Comment on DOI: 10.1126/science.adt7790
@modrak_m ah thank you for sharing this follow-up
I did actually wonder about the selection bias possibility here
This peek performance chart nerd snipped me for a couple days. Ended up having to blog about it to get my thoughts straight.
TL;DR: I got to thinking about it in terms of coding and realized my mental model didn't fit. Ended up thinking more about the importance of practice for the early stages. Post is here if you're interested:
felixlinker
Cat Hicks
Teixi
Franchesca
Three plus or minus five
Bill, organizer of stuff
graeme fawcett
Jimmy
M. J. Fromberger
Irenes (many)
Simon Hears
Roger Moore
GeePawHill
Martin Modrák
alan 
