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June 15, 2016

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"According to this analysis, none of the contributors top C++ projects on GitHub are male; by contrast, almost 10% of contributors to R projects are female." ... do you mean ' none of the top C++ projects on Github are by female;' ?

I think the most interesting story is the male bias in programming and would like to see the vertical axis go from 0 to 1. That, and they're proportional data and we could still see differences between languages. Thanks for the post.

Thanks for pointing that out, @Debajyoti. I've corrected the error in the post above.

The reasons you state this should be taken "with a grain of salt" I think are much worse than just a grain of salt. The implication is that these figures represent actual trends with some small error for the stated reasons, but it is possible those reasons are enough to obliterate the reported trends entirely. Although it is interesting to use resources like this to do some analysis, I don't think we should ignore methodological rigor when reporting results.

Are the percentages above the percentage of all avatars that were identified as female or the percentage of those where the gender could be identified?

It would be interesting to see the percentages of male, female and unknown.

The ratio is not surprising, however It would be nice to see the actually counts of these categories, A non probabilistic sample (top 100) on top of a probability sample (gender) can really skew results.

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