Go through the list, look at the entries which are either <20% female or >80% female, and tell me if you don't see the same pattern:

https://www.bls.gov/cps/cpsaat11.htm

We study diseases by (first) looking at people who have severe forms. Ie it would be tough to come up with an understanding of autism just by studying the brains of people who are "a little aspy". If you can figure out what causes the gender segregation of train drivers / pediatricians, maybe you can apply that knowledge to relatively-mildly-imbalanced tech fields.

Obviously with animals is different, but there might also be other things at play that we are not aware.

Happy to be wrong, but I think there are so many layers to make a call at this point that sure, there might be an influence, but society is probably what affects this the most.

What is dangerous about analysing data?

Or do you mean it's dangerous to form absolute conclusions just on a subset of available data?

P-hacking is a known issue in many scientific fields. So is drawing conclusions from over collection of data without repetition of the study... As the number of data points you collect approaches infinity, the chance of finding at least one meaningful-seeming correlation approaches 100% because having an unlimited number of data points to bash against each other makes you more likely to observe an improbable correlation.

I speant most of the last 18 months in and out of the hospital, and I noticed that doctors are more things oriented, and nurse practitioners are more people oriented. Even though they do the same job.

I want the nurse practitioner when I'm feeling awful, I want the doctor to explain their thought process in technical detail. Even if it's over my head.

And to be clear, I didn't read the article, but I had doctors and nurse practitioners of different sexes.

'doctors'

A quick LinkedIn search for Surgeon shows that about 70% of surgeons in the SFBA are male.

80% of pediatricians are female.

'engineers'

Prior searches showed that 90% of electrical engineers were male.

50% of SQE were female.

Depends on the specialty. Scott Alexander once observed:

> A look at percent female physicians by subspecialty is instructive. The specialty with the most women is pediatrics, followed by child psychiatry, followed by obstetrics, followed by – you get the picture. The specialties with the least women are the various surgeries – the ones where your patient is immobilized, anaesthetized, opened up, and turned into a not-quite-color-coded collection of tubes and wires to poke and prod at – the ones that bear more than a passing resemblance to engineering.

Source: https://slatestarcodex.com/2015/01/01/untitled/ —please note that the bulk of the piece is not strongly focused on this particular issue and is not a very representative context for this point. Scott restated the same point in a better context later on in https://slatestarcodex.com/2017/08/07/contra-grant-on-exagge..., but left out the “not-quite-color-coded collection of tubes and wires” bit which makes the point significantly less punchy and quotable.

…

For the record, there’s a similar pattern in veterinary medicine. The majority of vets who treat pets are women, but livestock veterinarians are predominantly men. IOW, whether or not animals are treated more like people or things correlates to a significant disparity in the predominant sex of the veterinarian treating them.

I'd look at this from a... step back.

"Software Developer" is all you need to know.

For example a Mechanical Engineer designing a product on a CAD-- Product A is a machine interface Product B is a car seat for young children. One could argue Product B is more people-oriented. But that's irrelevant. We're talking about the occupation, not the product. The occupation is making things primarily on a computer in this case.

Software Developer --> Spends XX% of time working with Things (computer) and XX% of time working with People

vs

<other occupation> --> Spends XX% of time working with Things (<occupation-pertinent inanimate object(s)>) and XX% of time working with People

...And sure, there are different types of Software Engineers ("SWE")-- Some SWEs are heads down programming 80% of time w/ 20% of meetings (for example). Solutions Engineers ("SE") are the reverse-- 20/80. The latter is more social. But to become a SE is dependent on SWE skills, therefore I consider it a variant of the primary category of SWE, whose main focus is working on a computer. Not working face-to-face with a human to participate with them in some social activity (such as sales, nursing, management, or a job with a lot of meetings).

Both are thing oriented because you’re doing work for people as an abstraction, not individual people.

User stories might be based on actual people, but they’re ultimately meant as archetypes.

It also identified "face to face interactions" as a requirement for being people-oriented. So dating app developer is clearly not included.