A point a friend on discord made was
People with "mild" variations are often invalidated when they call themselves intersex and attacked, and not all people feel safe saying they are intersex for that reason and end up saying they are perisex. A term between the two would help with the safety of those people who do not feel safe and who are often forced to be put in a position they are not in.
Not all people with mild variations consider themselves intersex. However, they are not considered perisex because they have variations in sex.
Not everyone likes to use intersex. This is because they may find it very medicalizing (and sometimes the person has a variation in visible sex, but does not fit or does not want to see it fit into any medical term) or they may find it not medicalizing at all (some people really have problems with their sexual variation, causing disabilities, for example, and prefer to use more medical terms that define this). So, for those who feel that intersex is too medicalizing a term, you may prefer to use alternative terms
I'm the asker about spectrum and I wanted to let you know these points
Also. When I think about intersex as a spectrum, I meant in the linguistic/conceptual aspect. As like graysexual is in the asexual spectrum.
Myself, my intersex variation isn't studied yet (partial or mild EIS). And mesosex resonates with me. Even though in the end I could go with just being a dyadic ally or questioning/quoisex/extersex. I also feel as if like both the terms perisex and intersex could fit me
Some people also say sex is a statistically bimodal spectrum. What do you think about it?
Thanks for sharing! I'm glad the term mesosex resonates with you 😄 It's honestly really useful to hear from people who feel the term mesosex resonates with them. I put the word out there because I had a sense there's a demand but as somebody who feels solidly intersex I feel honestly weird having a say in a label I don't myself use.
If you didn't see it already, a mesosex person chimed into the original thread.
To me intersex is the anti-medicalizing term, especially in contrast to DSD, which to me is 100% medicalized. But that's just me!
Analogies about Biological Sex
So you also asked about my thoughts on sex as a "statistically bimodal spectrum", and the short answer is I think the term bimodal is misleading and possibly circular, and there are better analogies out there.
I already agree with what others have pointed out about sex not being a spectrum - a spectrum has one dimension (a line), and sex has dozens of dimensions (chromosomes, hormones, etc). Out of the analogies I've seen, I like most Hans Lindahl's train tracks analogy for sex development.
But I'm gonna guess that by "sex as a statistically bimodal spectrum" you mean "sex as a statistically probability distribution/density" and take this as something distinct from the sex-as-spectrum model.
As it turns out, I have a lot to say about "bimodal"
In my experience, people tend to have huge misconceptions about what statistically bimodal means. It understandably gets conflated a lot with the idea that there are two separate populations.
So let's think about height. People will say things like "height is bimodal" because they're conditioned to think that men and women are separate, and the average man is taller than the average woman.
And when they say things like "height is bimodal" they think the distribution for adults will look like this:
But here's what the adult human height distribution looks like:
The thing about normal/Gaussian distributions is that adding them together is tends to result in something that also looks normal/Gaussian.
If we look back at pink and blue distributions I hand drew, there's a visual sleight of hand going on there. Where the area under the curve is pink or blue, we can think of one pixel as representing one human in the data set. But in the part where they overlap, it's not one pixel per human, its one pixel for two humans - one from the womens' data set, one from the men's data set.
The result is that the size of the overlap looks half as small as it should be. It leads people to mistakenly think there is less overlap between men and women than there actually is.
So if we actually take that overlap and show how the distributions add together, we get something that immediately stops looking so "bimodal":
With the two probability distributions that I drew there might be a small dip in the middle, but it would be quite small. 🙃
Two probability distributions need to be really far apart for them to produce something that actually looks bimodal. (Specifically, the difference between the means needs to be smaller than twice the standard deviation - details here.)
True bimodal distributions are rare. They do exist in nature. But most of the time when people see a probability distribution with two peaks, it is a result of misleading visuals, noisy data, or poorly-binned histograms. 👀
In grad school I was taught that bimodality is a sign your data is suspicious: "Statisticians are trained to be suspicious of distributions with multiple modes. Such distributions usually indicate inhomogeneity in the system, or, in plainer language, different causes for the different modes. All familiar proverbs about the inadvisibility of mixing apples and oranges apply." (Gould, 1981)
In particular, the misinterpretation of (apparently) bimodal data has been used to confirm eugenicist ideas about racial differences, because when it comes to statistics we're always a step or two away from having to grapple with the legacy of eugenics. ⚠️
So let's get back the original question about seeing sex as statistically bimodal. The average person understands bimodal to mean "two populations", not statistical bimodality.
So before I even get into what sex even is, right off the bat this analogy is dangerously circular: sex is what it is because it's two separate populations.
Sex in humans is determined by a whole bunch of things that tend to correlate with each other (chromosomes, SRY gene, androgen levels, androgen sensitivity, estrogen levels, estrogen sensitivity, etc), so I can see the desire to illustrate that some things co-occur together more than others!
But I agree with @queercripintersex in the discussion of your previous ask that trying to project the multiple dimensions of sex into one dimension loses too much information, and is difficult to even do because so many factors are non-continuous (chromosomes, etc).
For the continuous variables, you can in theory try to find out if they have bimodal probability distributions. But quite rapidly run into issues of poor data. The data on testosterone levels in women is shockingly insufficient. Like I went looking for distributions of free testosterone levels and just look at how much noisier and sparse the data is for women (on the left) compared to men (on the right):
Even with all the noise in the data it's still unlikely that at any of the age categories, that the men's data and women's data added together would produce bimodal distributions. There's too much overlap.
As a general rule of thumb, any given physical difference (hormones, measurements, etc) has more variation within the sexes than between them.
Our culture has vastly overestimated the biological differences between the sexes. 😫 So I worry that adopting a sex-as-bimodal-distributions analogy will only feed this misconception. 🫤 I'm personally going to avoid using the analogy.
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