Except they would be? Having breasts, especially large ones, changes where the seat belt sits. It can not be flat against the chest. Generally either is above the tits cutting into your throat, or underneath them doing…poorly as a restraint. Or maybe attempting to cut them in half but not doing well because bras won’t let that happen.
I was going to say there’s also the option of in-between but that is dependant on clothing, but you beat me to it 😅
You’ve convinced me that it’s reasonable that it could effect the outcome. But in that case, we’re averaging out a large variance in size, which as you said (and I agree) could change the outcome dramatically.
This was my original problem with the “anatomically correct” part of the statement. There is no “anatomically correct” male or female, only approximations. This effectively excludes people at the extremes of physical characteristics from these safety tests
You’re not wrong here about how a dummy designed to “the average male” proportions" is going to exclude men whose proportions exist in the statistical extremes (and likewise for women), but a phrase that comes to mind is “All models are wrong, some are useful”. Whenever we are making a model for gathering and analysing data, it’s because the real phenomena we’re studying is too complex to be able to effectively analyse without a model. Even if we had a wide array of anatomically correct crash test dummies for many different body types, it would still be a huge simplification of reality. A huge part of research is about trying to always be mindful of this tension, and to be constantly evaluating whether our model is a good enough for reality.
The stats for injury rates in women indicated that no, our model was failing pretty significantly in this area, so we designed different dummies, effectively updating our model. There will be more research that looks at other kinds of variation between people, and that will mean trying to account for extremes while not overcomplicating our model.
Except they would be? Having breasts, especially large ones, changes where the seat belt sits. It can not be flat against the chest. Generally either is above the tits cutting into your throat, or underneath them doing…poorly as a restraint. Or maybe attempting to cut them in half but not doing well because bras won’t let that happen.
I was going to say there’s also the option of in-between but that is dependant on clothing, but you beat me to it 😅
You’ve convinced me that it’s reasonable that it could effect the outcome. But in that case, we’re averaging out a large variance in size, which as you said (and I agree) could change the outcome dramatically.
This was my original problem with the “anatomically correct” part of the statement. There is no “anatomically correct” male or female, only approximations. This effectively excludes people at the extremes of physical characteristics from these safety tests
We might need redesigns for seatbelts then, one that can be easily adapted to a variety of body widths, heights and chests.
Ahhh the ol’ isadora duncan
You’re not wrong here about how a dummy designed to “the average male” proportions" is going to exclude men whose proportions exist in the statistical extremes (and likewise for women), but a phrase that comes to mind is “All models are wrong, some are useful”. Whenever we are making a model for gathering and analysing data, it’s because the real phenomena we’re studying is too complex to be able to effectively analyse without a model. Even if we had a wide array of anatomically correct crash test dummies for many different body types, it would still be a huge simplification of reality. A huge part of research is about trying to always be mindful of this tension, and to be constantly evaluating whether our model is a good enough for reality.
The stats for injury rates in women indicated that no, our model was failing pretty significantly in this area, so we designed different dummies, effectively updating our model. There will be more research that looks at other kinds of variation between people, and that will mean trying to account for extremes while not overcomplicating our model.