3 ms·

The only reliable way to find out someone's gender is to ask them what gender they currently think they are. There are more than two genders and an individual's

by sambeau 13y ago

The only reliable way to find out someone's gender is to ask them what gender they currently think they are. There are more than two genders and an individual's gender can change with time. A better strategy all-round would to be ask yourself whether you need to know someone's gender. I can think of very few legitimate reasons to know and record a user's gender and many of them can be dealt with by simply asking them what they'd like to be referred as, perhaps in more than one scenario.

joaomsa 13y ago
One use I've come across for inferring genders was tackling record depupliction across multiple data sources. In one data set we might have the gender information of an individual but have it be missing in another. Turns out gender is great to include in a blocking keys to reduce number of comparisons. Extrapolating an inferred gender in the dataset without one was incredibly helpful.
- aw3c2 13y ago
  You are forgetting that the individual might consider the gender to be private information. Some people might want to use a different gender in different contexts. See the ESPN/Grantland suicide issue recently if you care/dare.
  - mseebach 13y ago
    An individual that considers gender to be private information , and that uses different genders in different situations is very unlikely to be using a name that can be classified with a high degree of confidence as one gender. A person using the name "Jack" is unlikely to be assumed to be a woman, even if that person selected "female" from a drop down somewhere. If the same person uses Jack/M and Cindy/F in different contexts, no fuzzy algorithm is going to resolve them as the same person (bar some other, stronger ID, such as a SSN). EDIT: I initially used "William" as an example. Ironically, it turns out that name is only 57.6% male. Both Jack and Cindy are 90% male/female.
    - drakeandrews 13y ago
      At least in the UK, Jack is a fairly common shortening of Jacqueline. The only way of determining a users gender is asking them directly, and if a person wishes to enter different values into different systems, all the more power to them.
    - dsr_ 13y ago
      "I initially used "William" as an example. Ironically, it turns out that name is only 57.6% male. Both Jack and Cindy are 90% male/female." You have just used the numbers from the API as evidence of its own accuracy.

by sambeau 13y ago

joaomsa 13y ago

One use I've come across for inferring genders was tackling record depupliction across multiple data sources. In one data set we might have the gender information of an individual but have it be missing in another. Turns out gender is great to include in a blocking keys to reduce number of comparisons. Extrapolating an inferred gender in the dataset without one was incredibly helpful.

aw3c2 13y ago
You are forgetting that the individual might consider the gender to be private information. Some people might want to use a different gender in different contexts. See the ESPN/Grantland suicide issue recently if you care/dare.
- mseebach 13y ago
  An individual that considers gender to be private information , and that uses different genders in different situations is very unlikely to be using a name that can be classified with a high degree of confidence as one gender. A person using the name "Jack" is unlikely to be assumed to be a woman, even if that person selected "female" from a drop down somewhere. If the same person uses Jack/M and Cindy/F in different contexts, no fuzzy algorithm is going to resolve them as the same person (bar some other, stronger ID, such as a SSN). EDIT: I initially used "William" as an example. Ironically, it turns out that name is only 57.6% male. Both Jack and Cindy are 90% male/female.
  - drakeandrews 13y ago
    At least in the UK, Jack is a fairly common shortening of Jacqueline. The only way of determining a users gender is asking them directly, and if a person wishes to enter different values into different systems, all the more power to them.
  - dsr_ 13y ago
    "I initially used "William" as an example. Ironically, it turns out that name is only 57.6% male. Both Jack and Cindy are 90% male/female." You have just used the numbers from the API as evidence of its own accuracy.