The author posts the data, then calls for further study. Isn't that the very basis of science? She admits fully its potential for inaccuracies and wonders aloud about its flaws. Isn't that what peer review is for? The women in tech say it feels true, and it matches their experience. So why isn't the Hacker News Community demanding a peer reviewed study and supporting it, and financing it? Why does it instead choose to ignore its substance, and tear down its conclusions based on its already admitted flaws?
Truly, the persistent and relentless attempts on the part of some Hacker News denizens to discredit any science about bias in technology is disappointing. Any and all attempts to quantify the problem are met with such resistance that it belies the community's own assertions about its objectivity.
Looking at the data, I don't think the author did anything with it than see initial numbers matched her feelings, and then called on people to undertake a massive, actual study because she just know this is it.
I certainly think that there are problems with gender in society in virtually every place we could examine, and that we have a long way to go before things are what anyone could call ideal.
I just have trouble with a lot of the statistics used in these discussions, and find that they're very often 20+ years out of date (ie, from or before 1994-1995), don't control for confounding influences, make misleading comparisons, etc.
I would take posts like this much more seriously if she posted the dataset, but I'm not sure how she could do this without revealing personal details or editing the text (which likely would bias the choice of recipients further, or could introduce a new bias). I would even settle for the details of how she did the bucketing, correlations between words and numbers of entries per person, etc.
The short answer to why I think that this article isn't a real source of data is that the study in it has about the statistical power of just asking everyone who's a friend of a friend on Facebook for people with a moderate number of friends.
Everyone already knows that there's a problem with gender in tech. This article does nothing about saying where it is and doesn't really contribute anything to the topic.
There is almost no science in studies like this. There are so many variables, that you'd need to collect hundreds of thousands of data points to narrow down the influence on just a couple of variables... and even then, you can't be sure you've found something significant and meaningful. To do science, you need controlled experiments, and these are practically impossible to do with people. Even the well-known psychological "experiments" have been disputed in the recent years [1] [2].
The author posts the data, then calls for further study. Isn't that the very basis of science? She admits fully its potential for inaccuracies and wonders aloud about its flaws. Isn't that what peer review is for? The women in tech say it feels true, and it matches their experience. So why isn't the Hacker News Community demanding a peer reviewed study and supporting it, and financing it? Why does it instead choose to ignore its substance, and tear down its conclusions based on its already admitted flaws?
Truly, the persistent and relentless attempts on the part of some Hacker News denizens to discredit any science about bias in technology is disappointing. Any and all attempts to quantify the problem are met with such resistance that it belies the community's own assertions about its objectivity.