Notes and References for ‘We’re just normal, why do you call us cis?’
The following notes and citations are in support of ‘We’re just normal, why do you call us cis?’
A scientific reader has (respectfully) called me out for failing to back-up the claims made in my story. I should know better. :-)
Here, then, are notes and citations supporting my claims.
Note: I was not able to rediscover most of the publications I had in mind when I wrote the original story. If you can provide additional references, academic or popular, I would be most appreciative.
(Content warning: sciency blather ahead…)
I am a scientist and my claims are, in part, based on extensive reading in the literature. Unfortunately I am not great at keeping notes when I am not working on something specific, so backtracking to sources is a rather time-consuming pain-in-the-butt, but I shall do my best…
A cautionary note: Until only recently, academic work on transgender and intersex was a highly stigmatised fringe, as were gender and sex before that. Virtually all the work has been done in only the past couple decades, with the vast majority of the good work being a decade old or less. Earlier work is sparse and almost uniformly very biased. Recent work is still rife with bias, small sample sizes, and poor methodology, so any reading should be done with a careful eye to those factors.
Additionally, trans and intersex populations are very hard to study due to the secrecy most trans and intersex people maintain for their own safety. This means that study samples tend to be taken from the small and atypical group of subjects who are willing to be ‘out’, so are unlikely to be generally representative. Even reliable gross population numbers are impossible to come by. Furthermore, for complex social and psychological reasons, a large fraction of these populations may not (yet) even know that they themselves are trans or intersex. Thus, getting suitable volunteers for studies is a fraught business, and prospective studies are a near-impossibility. 
Lastly, popular reportage of studies is almost universally dreadful, usually heavily slanted, misconstruing methods and results, and most often written to support a political or ideological position. Even reviews and editorials in peer-reviewed journals are often guilty of these sins.
With all that out of the way, I shall respond to the reader’s requests —
“Gender and sex do not exist as absolutes or as binary (either/or)” — is there any hard evidence to support this statement as it applies to humans…?
Let’s take intersex first, as it’s so easy: Intersex is defined by failure of the physical sex binary. First, let’s point out that intersex conditions are not all that rare: somewhere in the range of 1–2% of humans, or roughly as common as redheads, and probably about twice as common as transgender humans.
There are dozens of different intersex conditions, ranging from non-XX-XY genetics to hormonally generated variations (which can even go so far as to include fertile XY females) to chimerism. These rarest and most extreme variants will be found at the skinny tip of the inverted distribution shown in the graph above, with more common and less extreme intersex variants such as AIS and CAH falling more to either side.
So yes, physical sex in humans is by no means binary, the population which lies outside the presumed binary is not tiny, and this is well supported in the science.
Now let’s address transgender. Everyone (who deigns to accept transgender as a ‘real thing’ at all) accepts that there are binary transgender identities, i.e. women and men, so I’ll not address that.
There is a huge body of material addressing nonbinary (enby) gender identity, both in the literature and on the internet generally — indeed, the real problem is drinking from the fire hose. If you are genuinely interested, I suggest you spend a few relaxing days with Google… :-)
Human gender can run from ‘strongly female’ all the way through varying degrees of ‘either/neither’ to ‘strongly male’, as per the graph above, and may even be unstable over time. The ‘validity’ of these identities cannot be pinned-down in an objective sense, since by definition these are subjective identities. You will never ‘objectively’ prove that ‘liking chocolate’ or ‘seeing vermillion’ or ‘being bisexual’ or feeling nonbinary gender are ‘real’ — these things exist by self-description and by self-description only. Asking for ‘proof’ is fundamentally nonsensical.
That said, gender nonconforming people self-report identities all across the spectrum, as per the preceding paragraph, so yes, like physical sex, gender in humans is by no means binary, the population which lies outside the presumed binary is not tiny, and this is supported.
It is worth noting that research into nonbinary gender identity is in its infancy, even more so than w.r.t. binary transgender and intersex.
Additional reading: (But as I said, it’s a fire hose, and this hardly scratches the surface…)
And by the way, the above applies equally to ‘being cis’ and ‘being trans’ — subjective states — and some people are (by self-report) ‘cissier’ or ‘transier’ than others, thus this too is not a binary phenomenon.
…“normal” is roughly defined as “commonly attributed to, practiced or accepted by the majority”…In this context, any behavior or condition that is not attributed to a majority isn’t “normal”.
You are technically correct, but there is a problem.
When dealing with common usage (as I am in this piece), ‘normal’ comes along with additional meanings, such as ‘correct’, ‘healthy’, ‘acceptable’, ‘good’, ‘preferred’. In this context, technical definitions are insufficient and the common meanings as employed must be addressed.
Thus it becomes inappropriate and prejudicial to apply ‘abnormal’ to human minorities in any context whatsoever. For example, using your technical definition, it is ‘abnormal’ to be gay, left-handed, or African American. This is a (common) usage which cannot be permitted.
‘…the term “normal” can have no set definition because its meaning is unstable over time due to such factors as consensus, social legitimacy in classification, trait confirmability, and negativity bias.’