For what it’s worth, I’m not particularly trying to make a point about society (I’ve rarely found it useful to talk about potentially controversial social issues online); it just seemed like an interesting and relatively straightforward thing to look at. I would guess that the reason it’s represented this way in Gemma is just that in the training data, when texts invoked gender, it was more often male (and that it’s more computationally efficient to treat one gender or the other as the default). There are presumably explanations for why men appeared more often than women in the training data, but those are thoroughly out of scope for me.
For what it’s worth, I’m not particularly trying to make a point about society (I’ve rarely found it useful to talk about potentially controversial social issues online); it just seemed like an interesting and relatively straightforward thing to look at. I would guess that the reason it’s represented this way in Gemma is just that in the training data, when texts invoked gender, it was more often male (and that it’s more computationally efficient to treat one gender or the other as the default). There are presumably explanations for why men appeared more often than women in the training data, but those are thoroughly out of scope for me.