Table 2.

Analytic Themes, Subthemes, Definitions, Sample Quotes, Frequencies, and Cohen’s Kappas

Theme Subtheme Frequency Cohen’s kappa	Definition	Sample quote
Meritocratic frame Proving ability 20/22 (90.9%) κ = 1.0	Respondents’ belief that working hard and long will prove they are capable and eventually earn them respect and rewards in the workplace	“After a couple of years, you have opportunities. You keep a record of your accomplishments and when your supervisors feel like you’ve been there long enough and you achieved enough you can get promoted” (Linda, White)
Meritocratic frame Youth and inexperience 17/22 (77.3%) κ = .86	When faced with differential treatment, respondents explain it as a due to their relative youth, which related to having less experience as an engineer	“Age definitely plays a big factor. A lot of times, people do question my decisions a lot more, which makes sense because I haven’t been there as long. But, sometimes it is annoying because it’s like, I promise you I did this right” (Grace, Latinx/Asian)
Meritocratic frame Contradicting the meritocracy 6/9 White women (66.7%) κ = 1.0	White women express kinship with supervisors and/or co-workers	“One of my coworkers loves guns and has taken me to the shooting range. It feels like a family more than it feels like coworkers” (Beth, White)
Naming gender Gender essentialism 11/2 (50%) κ = .91	Respondents explain gendered interactions or job assignments as something natural, assuming women and men have different strengths or skill	“Having good social skills sets you apart, because not everyone can portray themselves in a positive manner. I feel like that’s one of the things that really worked to my advantage, which I don’t know if that’s necessarily something you can prepare for or if it’s more natural” (Christine, White)
Naming gender Exception to the rule 15/22 (68.1%) κ = .88	Sexist treatment is anomalous and not part of regular patterns in the workplace; it is committed by non-engineers, is unintentional, or in the past	“I really needed an operator’s help, [and after he finished] I remember I literally said, Thanks, Carl, so much. You’re the best. When I said that, all the operators did … you know in middle school when the guys would be like … showing you had a crush? Something stupid. In my head, I was thinking, If I had been a guy, and said the same thing, they wouldn’t have done that […] but that isn’t the people I’m working with on a day-to-day basis. That’s the operators” (Alexandra, Latinx)
Naming gender Standing out 11/13 women of color (84.6%) κ = .91	Women of color reported feeling like they stand out in mainly white, male-dominated workplaces	“I was the only female out of the three plants I sat in […] then I started to notice that there’s more white, older men in the room, pretty much over the age of 40" (Carol, Asian)
Naming gender Mental gymnastics 10/13 women of color (76.9%) κ = .91	Women of color name sexist treatment, but second guess themselves	“It’s like the all-male environment, they say some vulgar things, or they’ll say things like, Oh, I can’t say something because Patricia, is here. But for the most part, I get treated pretty fairly” (Patricia, Latinx)