A Gender Gap in Bicycle-Riding
buzzfeed.com
buzzfeed.com
- Data-processing scripts and HTML/JS/CSS for the maps and charts: https://github.com/BuzzFeedNews/2014-06-bikeshare-gender-map...
- Python parsers for the various bikeshare services' published data: https://github.com/BuzzFeedNews/bikeshares
- General guide to getting data from these services: https://github.com/BuzzFeedNews/bikeshare-data-sources
Riding a bike in a large city is dangerous - I've never done in it New York, but in London altercations between bikes, pedestrians, taxis and buses are quite frequent. There are few real continental-Europe-style bike lanes.
Perhaps same gender differences in appetite for risk also affects one's decision to ride a bike in a large city?
Bicycles in NYC are serious business though. I've known people who were slapped with hundreds of dollars in violations and summonses in one sitting. I know one guy who was car-doored on a narrow street and woke up hospitalized and missing teeth. I've also heard similar stories of males and females drunk bicycling home at night that also ended in serious hospital visits.
More often than not, males in their 20's are on skateboards, and certainly falling a lot, but usually with a degree of anticipation and a strategy for absorbing and surviving the fall. Otherwise, males under 40 and not on skateboards seem to be keenly aware of their own lack of athletic inclination and poorly trained physical coordination (myself included; I like my teeth).
Bicycling is an activity where you should be wearing a helmet for safety, and this is at odds with styling your hair in the morning since that helmet with mess up many styles of longer hair.
However, that being said, this data comes from city bikesharing services, which often don't involve helmet usage.
I also wonder how much clothing choices impact ridership. Unisex clothing choices (pants, shorts) are more convenient for bicycle riding than skirts and dresses.
I'm curious, if you normalize the data to discount women who spend a lot of time on their appearance (particularly their hair) and discount the percentage of women who are not wearing unisex clothes, do the numbers more closely hit a 50-50 distribution.
Lastly, I'd love to see what data Google has on bicycle ridership for Google Bikes on its Mountain View campus (relative to the ratio of men-to-women at Google of course)