[richmarr]

> That must be because your studies have glaring methodology defects...

How delightful it would be to live in such a simple world.

Here's a study for you:

Handley, Browna, Moss-Racusinc, and Smith (2015) found that men are more likely to judge evidence of gender biases as low quality, and that effect is particularly pronounced in STEM fields

[wanderer2323]

must be good to live in such a simple world where you can expect to bring a study about gender biases into a discussion about diversity studies and have it prove or explain anything. anyway, the problems with the study you linked are glaringly obvious -- poorly designed study, exceptionally poorly designed controls, no preregistration (that I can see mentioned at least), sample sizes that make me really want to check their math -- and these are just from the abstract.

If this is what you have in mind when you speak of research, then you can believe whatever you want, really. false -> true === true after all

[richmarr]

> must be good to live in such a simple world where you can expect to bring a study about gender biases into a discussion about diversity studies and have it prove or explain anything

As I'm sure would be clear to you if you stopped to think about it... you strongly implied that studies are evaluated based on merit alone. This shows that they are not.

Does the study look at precisely this situation? No, that would be an unlikely coincidence.

Does the study demonstrate a gender bias in the evaluation of gender-related research, even amongst those knowledgable in the subjects? Yes.

Does the study suggest that STEM fields could be more susceptible to that? Yes.

> If this is what you have in mind when you speak of research...

As I've been saying from the beginning, this is about the balance of probabilities. By all means create your own study (and get funding, and get it published) that counters the findings. Until you do that, or someone else does that, or someone finds that the studies in question are fraudlent, unreproducible, or so flawed as to have literally zero value, then the balance of probability is against you.

You're welcome to subscribe to the view that any evidence less than a large-scale randomised controlled trial is worthless, but there aren't the funds for that, and may never be.

So your choice is between learning nothing, or learning 'maybe something'.

If you choose to learn nothing, or more accurately to deny 'maybe something' then I'm curious to know why.