Tools: random dates, college degrees, names

I used these tools to fill out the large scale details on the friends-and-fam.

Popular names by gender and year. I tried to stay away from the most popular names, names I believed implied race/ethnicity that wasn’t applicable to the character, or that struck me as implying the families were more religious than they actually are (which is not very). I did some searching on LinkedIn and Facebook, to make sure that the name combinations I picked weren’t real people who were the only people who had a given name combination, or which generated enormous numbers of hits.

Birth years were calculated. The main characters are supposed to be millenials, and their friends and coworkers (mostly) are also. I calculated parents age and sibling ages to fall within what I believe are typical patterns for boomer parents/millenial children. I then researched whether the fathers would have had to worry about the draft, and concluded that they probably thought about it while in high school, but given their birth year, it turned out not to matter.

The _general_ location is Pacific Northwest. However, I have not yet nailed down where everyone went to high school/college. I used this to pick common surnames, along with an FB group I am on that has members from my own high school.

I used this to come up with month/day of the month for birthdates and marriage dates. I threw out some dates, because I didn’t want a character born on September 11, and I didn’t want more than one character with a birthday that fell within one week of Christmas. I got one date twice, and threw out the second instance, so I wouldn’t have two characters in this group that shared a birthdate. I do want to point out that these all _reduced_ the believability of this group. Two characters sharing a birthday would have been expected with this size group.

I used this to help me pick college majors and careers for characters:

I did not want to write something that suffered from relentless whiteness or traditional gender roles/occupational choices. While some diversity is specific to the PacNW (some scandinavian last names in there), I wanted to reflect some of the diversity that I saw when I was working in tech in the area, and which I see in my town now, in part because a lot of the families living here are also working in tech.


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