The only way I've seen of identifying 'gendered' content is to find an external dataset where you know that people of different genders have explicit preferences for one item over another, and then to try to map that onto Wiki[pedia, data] content.
The one example of this approach of which I'm aware is a study done by the University of Minnesota
, where they compared the size/quality of Wikipedia articles about movies to an external dataset of movie reviews (provided by users of their own MovieLens product), where the gender of the people who rated those movies was known.
This approach should be possible, but it's hard to find a good comparison dataset that's openly available. For example, if you had access to the (declared) gender of people on Pinterest who pinned certain items, you could potentially use that dataset for comparison. But I expect that Pinterest keeps their user data secret--primarily because that's how they make $$$$.
There may be other datasets out there, but I can't think of any offhand :/