| The OP said: "There are a bunch of silly beliefs that we witness even amongst us ... that having no gender parity in tech is both good and natural." I didn't make any statement on "good" because it was poorly defined. It could be defined as anything from the individual's opinion to measurable outcomes (society's productivity or reported happiness).
I think "natural" in this debate tends to mean "biological factors" and not "social and cultural factors". I simply questioned the scientific basis for the OP's belief. So, how can we know that the rates at which males & females choose to study and work in a given field reflects their "natural" inclination rather than social or cultural factors? 1) We can look at the rates cross-culturally. In search of the numbers relating to "tech", I found the Stack Overflow developer survey (admittedly a subset of "tech"). Stack Overflow references Quantcast visitor numbers in their developer survey[1], so I'll look at those numbers too, around the world. The stackoverflow.com visitors by gender in:
India: 94% Male, 6% Female[2]
USA: 88% Male, 12% Female[3]
UK: 91% Male, 9% Female[4]
China: 86% Male, 14% Female[5]
Germany: 95% Male, 5% Female[6]
Iran: 88% Male, 12% Female[7]. The numbers seem pretty consistent, suggesting that the imbalance isn't due to social/cultural factors. 2) We can look at differences in interest in newborns. There is much discussion about males on averaging being more interested in "things" vs females on average being more interested in people. Here's the abstract from a study I found on the topic:
"Sexual dimorphism in sociability has been documented in humans. The present study aimed to ascertain whether the sexual dimorphism is a result of biological or socio-cultural differences between the two sexes. 102 human neonates, who by definition have not yet been influenced by social and cultural factors, were tested to see if there was a difference in looking time at a face (social object) and a mobile (physical-mechanical object). Results showed that the male infants showed a stronger interest in the physical-mechanical mobile while the female infants showed a stronger interest in the face. The results of this research clearly demonstrate that sex differences are in part biological in origin."[8] Happy to be shown how my numbers & study are incorrect or insufficient. Personally, I'd prefer to work in a gender-balanced environment, but I wouldn't want those of either gender to be forced into a role they don't want - I think that would lead to unfair (non-meritocratic) treatment of members of the minority and majority gender. I want everyone to be free to choose their field of study and work, and to be free to fulfil their potential in that field. If that naturally results in male- or female-dominated professions, I don't think it's something that needs to be rebalanced with policy, if that's even achievable. P.S. Interesting that I was socially censored for this: "What evidence do you have that _______ is good and/or natural? The scientific evidence seems to suggest to me that widespread _______ in many fields is natural." I'd say that social censorship as opposed to free discussion plays into the formation of silly beliefs that the OP complains about. Bad ideas are destroyed with discussion. Bad ideas that can't be discussed can't be destroyed. I'm happy to be corrected on the science regarding the current state of affairs. References:
[1] https://insights.stackoverflow.com/survey/2017#developer-pro...
[2] https://www.quantcast.com/stackoverflow.com?country=IN#/demo...
[3] https://www.quantcast.com/stackoverflow.com?country=US#/demo...
[4] https://www.quantcast.com/stackoverflow.com?country=GB#/demo...
[5] https://www.quantcast.com/stackoverflow.com?country=CN#/demo...
[6] https://www.quantcast.com/stackoverflow.com?country=DE#/demo...
[7] https://www.quantcast.com/stackoverflow.com?country=IR#/demo...
[8] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.627... |
1 merely correlates gender with career prospects and assumes traits exist biologically that performs the causative effect.
2 merely correlates behavior traits and assumes that there is a causative effect to career prospects 10, 20, 30 years down the line.
I do not want assumptions since they make a donkey out of you and me.