There’s a difference between “one factor that explains everything” and a dominant factor that explains most of the variation.

I just doubt that in many cases there is a dominant factor that explains most but I think that instead there are often several factors of more or less equal importance. We made that mistake already in nutrition ("fat is the main problem") and it caused decades of problems. The proportion of these factors is also highly individual.

Why do you believe that it’s more likely for several factors to have roughly equal importance than for one factor to be the most important?

As an aside, the mistake in nutrition was simply that it wasn’t true. And it also wasn’t a “mistake,” it was a lie that the sugar industry paid to spread.

the mistake in nutrition was to think that fat is the dominant factor. In reality, if you eat too much sugar, too much fat, not enough vitamins, exercise too little or too much, don't take care of your mental health, drink too much caffeine, smoke, drink too little or too much or just have bad genes you have a chance to get health problems. There is no dominant single factor you can focus on to be healthy for sure.

>Why do you believe that it’s more likely for several factors to have roughly equal importance than for one factor to be the most important?

if you pick n numbers at random, it's not likely that one of them is bigger than the half of their sum.

That really depends on the distribution of said numbers. You're probably assuming uniform distribution, but there are power law distributions like wealth where the 26 richest people own as much as the bottom 3.8 billion combined.

to be honest, I don't know much about probability.

but my intuition says that if you pick all variables from the same distribution, this should still hold.

At first, we don't know anything about the factors, so they are assigned a random importance. or am I missing something?

What if n=1 ? :)

You don't accept the possibility this could be true?

What's missing here are facts.

To dismiss something based on something anecdotally unrelated seems short-sighted.

Doubt =/= dismissal

> dominant factor that explains most of the variation.

A dominant factor can also only account for less than half of an explanation if there are enough factors. E.g. Peer group is 40%, parents are 30%, teachers are 20%, TV/videogames/groups-seen-but-not-interacting-directly-with 10%. Here peer groups would still be dominating but parents and teachers are significant factors as well. These percentages are close enough that it would be ridiculous to just focus on one (or even the first two alone).

For all X, if you study the effects of X on a complex system hard enough, it will look like X is the dominant factor that explains most of the variation.

I happen to believe peer groups are really important. But other things are important, too, including the adults.

Remove all the middle-aged and older men from a city, but still provide other necessities, and you'll see some terrible outcomes. (This is true in other species as well, like elephants where older males are hunted for tusks.)

Do you sometimes pick up a different child from kindergarten just for a bit of variety in complexion and looks at the dinner table, since that child will be essentially indistinguishable from your son in development and personality anyway, so you might as well?

How do you know what really influenced your life outcomes?

We all have stories about a great teacher or a terrible parent. But these are anecdotes. You don't actually know what would have happened if you had different parents, or different friends, or went to a different school.

It's perfectly possible that if circumstances were different, you would have gotten to the same place, by a superficially different path.

The specific stories would vary, of course. But when we talk about society-level policy, it's not specific personal stories that we focus on. It's things like income, marital status, job field, health, criminality. A lot of evidence suggests that even if your specifics were very different you would have actually ended up largely in the same place on these metrics.

“It's things like income, marital status, job field, health, criminality.”

Yes, it’s all of them. And they all need to be addressed instead of trying to pick the one all-dominant factor.

> How do you know what really influenced your life outcomes?

> ... these are anecdotes.

Combine a lot of anecdotes and add in more scrutiny and we can call that data.

In the spirit of over generalizations, Tim Ferris says that you are the average of the five people you spend the most time with. So let’s say mom and dad are gone by 6, you’re at school by 7. You get a different teacher every hour but the cohort of students in each class is substantially the same. You have soccer, gymnastics, karate, piano, etc after school and then you’re at home around 6. Dinner is a quick affair. Then it’s homework and bed. Mom and dad are spent by the time they get home and retreat to their device which is you’re queue to do likewise. Now I agree that throughout the day a kid might encounter dozens of potential mentors but when You examine time spent and substance of the encounter, it’s got to be enormously isolating to a child. Rather than five positive relationships where values are discussed and real mentoring takes place a kid basically receives empty knowledge via retail / transactional delivery. How is this anyway similar to how we grew up as kids?

>Tim Ferris says that you are the average of the five people you spend the most time with.

IMO this no longer holds true with the advent of the internet era. You're now spending equal amounts of time exposed to a countless number of people. Even if you aren't physically with them, and even if it's a one-way relationship (i.e. they are not aware of your observance and existence), they are still influencing who you are.

For planning and resource application purposes, you can only sell effort on one factor at a time to non-specialists (policy makers, parents, the public)

That's how you get terrible planning. Maybe we should just accept that things are not that simple and there are a lot of things that influence complex systems.