Maybe. Let's say there are broadly two hypotheses:
A: Women are systematically discriminated against in the workplace (sexism).
B: Women are systematically more inclined than men to perceive that they themselves are experiencing sexism.
(In the real world, we're going to have some mixture of the two, plus other factors, but simplified models are often useful.)
Systematic discrimination by gender in the workplace is well-documented. https://noidea.dog/glue is one example present in tech that's also applicable to research. At the level of this simplified model, A is true: that suggests that the 2023 WebSummit survey's results are a proxy for the level of actual discrimination.
Taking a step back… is this simplified model sufficiently-valid? From the page linked earlier:
> And they say "Look, you're great at communication. Your soft skills are outstanding. We just don't think you're an engineer. Consider becoming a project manager instead?"
> Kripa Krishnan, the legendary director of cloud product operations at Google once said that while she'd experienced some industry prejudice for being female and some for having an accent, it was nothing compared to the prejudice she experienced for being a TPM.
> The even more interesting part was that, when managers were asked to choose someone to do thankless work, they asked women 44% more than they asked men.
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Back to the original paper, I'd suggest that the relevant question is: what proportion of the qualified female population becomes an applicant, versus the qualified male population? If there's a higher bar for female would-be-applicants, leading to a lower-than-otherwise applicant pool, I'd expect a meritocratic multi-stage programme to pick proportionally more female applicants for the first stage, and then – having compensated for that bias – the proportions to be equal for follow-on stages. If I'm reading the paper right, that is what is observed:
> For the Veni tier, all models find significant differences between the succes rates of male and female applicants. The models also show a trend over time, where male applicants gradually have lower success rates and female applicants gradually have higher success rates. For the Vidi and Vici tier, no gender differences are found.
