Freebase has “place of birth” but that’s less well filled out than name and gender. It would be something to consider, though, as an option.

I take a somewhat different approach, which I’ll briefly sketch for added perspective on this challenging problem.

My need for deriving gender from names is for political organizing, when a strategy could involve targeting voters with gender as one attribute among others such as age, party, and so on. In voter registration records, many people do not provide a gendered title such as Ms, Mr, Mrs, or Miss (American English here). So I needed a way to guess their genders with some reliability.

I wrote a routine — in Perl, natch — that looks at the names of people who did provide gendered titles, and uses that to guess the gender of those who didn’t. The first thing I saw, of course was the ambiguous names, so I added a statistical threshhold below which the guess wasn’t allowed. Then I noticed the dimension that your method doesn’t account for, besides the limitations you mentioned: running the routine in different geographical areas gave different results. So for example in one county the name Guadalupe would come out as overwhelmingly female usage and in another county it would be too ambiguous to provide a useful guess.

So my approach differs from yours in that it is based on actual usage within a specific population. Still uses some assumptions, and would only be useful where one has an actual population to look at. But after several years of field testing, this method’s results have been consistently better than others I’ve been shown, measured by fewer people assigned ‘unknown’ gender and by higher degree of accuracy found in the field.

If I weren’t typing on such small device, I’d offer some code, and I’d like someday to do some more rigorous statistical analysis of thus method. Happy to follow up if anyone is interested.