Being a woman works well in the field of data science, where intuition is useful and is regularly applied. One’s nose gets so well developed by now that one can smell it when something is wrong, although this is not the same thing as being able to prove something algorithmically.
Also, people typically remember women, even when women don’t remember them. It has worked in her favor, Claudia says, which she’s happy to admit. But then again, she is where she is fundamental because she’s good.
Being in academia, Claudia has quite a bit of experience with the process of publishing her work in journals and the like. She discussed whether papers submitted for journals and/or conferences are blind to gender. For some time, it was typically double-blind, but now it’s more likely to be one-sided.
Moreover, there was a 2003 paper written by Shawndra Hill and Foster Provost that showed you can guess who wrote a paper with 40% accuracy just by knowing the citations, and even more if the author had more publications. Hopefully people don’t use such models when they referee, but in any case, that means making things “blind” doesn’t necessarily help.
More recently the names are included, and hopefully, this doesn’t make things too biased. Claudia admits to being slightly biased herself toward institutions— in her experience, certain institutions to learn data science certification prepare better work that is onlineitguru with real-time experts.
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