Sex redefined: the idea of two sexes is simplistic
nature.com
nature.com
If the "simplistic" male/female binary explains >99% of observations, there does not seem to be a strong case for describing biological sex as a "spectrum"...
I am 10,000% behind tolerance and acceptance for people of all genders and sexes and orientations, and it's very useful to understand how much biological complexity and variation is possible. But... any honest interpretation of the data would suggest that "the idea of two sexes" is an highly accurate approximation for Homo sapiens.
1% of the world population is nearly 70 million people. That is not a small population. One would hope that we might be more flexible in our descriptions considering how large of a population that is.
At what point is it acceptable to say that something is an approximation, and should not expected to be precise and accurate in perfect detail?
What we have right now is not an approximation, but a binary measurement. Turning sex into an approximation would be considered a significant step forward considering science tells us it is not binary.
Regardless, my earlier question stands. At what point is it acceptable for an approximation to not be accurate in detail? What's the acceptable level of error in approximations?
I'm fairly sure the lifes of those affected negatively by the error are outside the "acceptable level". We're talking about humans here, not mathematical rounding errors.
Boolean is simply a binary variable, having two possible values: true and false.
Does this mean approximations should not be used, or does it mean that one should be aware that the map is not the territory?
The important question is the second one I posed. What is the acceptable level of error in an approximation?
We're dealing with people.
> and the significance of it.
People are generally pretty significant. 70 million people is very significant.
> 70 million is not a significant number of atoms of most things, for instance.
70 million people is a pretty significant number of people.
> The important question is the second one I posed. What is the acceptable level of error in an approximation?
Since you seem to have mistaken my rhetorical question for an actual question, I'll restate it as a statement: 70 million people is not an acceptable level of error in an approximation.
Is that a correct assessment of your position?
That's a reasonable approximation, yes. :P
Who says those are not useful? The point is to not make therm exclusive by forcing everybody to be identified by one of them when it's not a good fit.
But that doesn't really work in this analogy because quantum physics essentially assumes Newtonian physics as axiomatic, so there is no way to avoid it no matter how 'serious' you're trying to be.
The article stands well on its merits. It's not political. It's talking about specific, measurable things with specific measurable effects, and 1% of a large number is still a large number.
For example it did not surprise me that the woman described in the beginning had no idea about her chimerism - after all her sexual organs were straight female (proved by the fact that she got pregnant, three times), so her blood was probably circulating lots of estrogen instead of lots of testosterone. Sure, her color vision was maybe working at the reduced, male level, but really - it is not that important.
On another note it is worth remembering that in vitro fertilization increases the risks of mosaicism and chimerism.
I'll admit that what you're willing to call a "highly accurate approximation" is pretty arbitrary. There are some systems where I would call an approximation with a 1% margin of error a highly accurate approximation. But it's a pointless argument to make when your 1% margin of error includes 70 million people. I think we can all agree that issues which affect 70 million people are not negligible.
[1] http://www.worldometers.info/world-population/ [2] https://en.wikipedia.org/wiki/List_of_countries_and_dependen...
You say that like it's some huge number. 70 million or not, it's still 1%. Numbers get their significance relatively, not in themselves.
Relative to what? I can't believe I'm having this conversation.
70 million people is more than the number of people killed in both world wars. 70 million people is more than the population of the UK or Canada. Are you claiming that the world wars caused negligible deaths, or that the populations of the UK or Canada are negligible?
You can't just say 1% is a negligible amount without context. Whether 1% is a negligible margin of error is entirely dependent on context. 1% blood alcohol will probably kill you, 1% error on your taxes, if intentional, is enough to put you in jail, 1% error in floating point arithmetic is the difference between a missile that hits its target and a missile that lands in a civilian residence. But numbers get their significance relatively, right?
70 million people is a lot of people.
Not that I necessarily disagree with your sentiment, but the world population was lower when those wars happened, so the the same number of people dying was far more than 1% at the time. Looks like WW2 alone was 3-4% of the global population. The world wars were also important for reasons other than number of deaths anyway.
However, I think that the atypically-sexed population is important for reasons other than numbers, too.
We aren't talking about killing 70 million people. We're talking about the strength of constructs in terms of scientific utility.
This is also the problem with huge numbers. It's very hard to process and we are intuitively intimidated by the largeness, such as with numbers from the state budget. $70 billion? Oh my god. How am I supposed to process that number?
Also note that 1% is a figure arising from the most inclusive definitions.
What about scientifically? Scientifically, there's no concept of negligible or not negligible. On what scientific grounds did you decide 1% was negligible?
The negligibility of a percentage is only choosable based on your values and how much you value what exists in that percentage. My argument is that in most contexts, you probably care about 70 million people. If that's not the case, you may be a sociopath. But my guess is that you aren't a sociopath--you're just operating under some temporary delusion that because you've decided to say 1% of people instead of 70 million people, your decision that the group of people in question is negligible is scientific.
> We aren't talking about killing 70 million people. We're talking about the strength of constructs in terms of scientific utility.
If you're claiming that 70 million people have no scientific utility, I'd like to see what utility function you're using.
> This is also the problem with huge numbers. It's very hard to process and we are intuitively intimidated by the largeness, such as with numbers from the state budget. $70 billion? Oh my god. How am I supposed to process that number?
I'm not sure how the fact that large numbers are hard to process means that 70 million people is negligible. Certainly saying 1% instead of 70 million makes it easier to process, but playing to human mental limitations isn't a particularly good source of truth.
> Also note that 1% is a figure arising from the most inclusive definitions.
I'll happily make similar arguments about 7 million people instead of 70 million.
The researchers found that, in the most inclusive definitions, 1% of the population isn't sufficiently accounted for by traditional constructs.
But there's no new theory here. How do I predict complications based on what factors? What's the new model? The "spectrum"? A spectrum is a scale with escalating and deescalating values as you travel up and down, where jumps in the spectrum are connected to jumps in prediction. As for abnormal and discrete bins, well, the scientific community already has that. What's new to the table? A reformation of language so that we avoid the word "abnormal"? But where's the improved model?
Also note that you propose that there's no way to think about scientific or construct "betterness". Yes there is. You can measure by complexity, prediction, explanation, or generalizability. These are just a few ways. But you waved away scientific discussion, and instead choose only to use the moral lens, and bring up sociopathy.
Also, the reason I am talking about human limitations in processing large numbers is because I am accusing the opposition of abuse. I am not saying you should believe me because of X, I'm saying beware of opposition arguments because they are abusive to human minds.
And on the matter of using percentages to interpret numbers, I return to my example of state budgets, because that is a place where politicians often abuse psychology by stating what appears to be extravagant numbers. By extending your statements, I might say that not only is $70B a lot of money, but so is $7B. But then what if you told me that $70B is less than 1% of the state budget? What did you just do to that number?
Honestly, 10,000 people dying is a lot. Therefore, let's not talk about construct validity?
Not in a general sense, there isn't. "Better" can only be scientifically defined in terms of a utility function, a goal. If you're trying to conduct, copper is better than rubber, if you're trying to insulate, rubber is better than copper. If you're trying to provide adequate healthcare and social protection to people, then a lower margin of error would be better.
> All you have to show is that your construct is competitive within the ecosystem of constructs.
Competitive based on what utility function?
> But there's no new theory here. How do I predict complications based on what factors? What's the new model? The "spectrum"? A spectrum is a scale with escalating and deescalating values as you travel up and down, where jumps in the spectrum are connected to jumps in prediction. As for abnormal and discrete bins, well, the scientific community already has that. What's new to the table? A reformation of language so that we avoid the word "abnormal"? But where's the improved model?
I think an admission that the current model is inadequate goes a long way towards motivating the discovery of better models.
> Also note that you propose that there's no way to think about scientific or construct "betterness". Yes there is. You can measure by complexity, prediction, explanation, or generalizability.
Okay, so you've named a bunch of utility functions. Now do you really want to apply those to this situation? How do we apply these to the question of whether 1% is a negligible margin of error. Let's optimize for those:
1. Lower complexity: "everyone is a man" seemed to work back in the day. 2. Higher complexity: let's subdivide male and female. There are certainly other genetic traits besides X and Y chromosomes that we could include in our definition of sex. (Hint: It's silly to optimize for higher complexity, but why? I propose that the answer is based on your values.)
Everyone here knows that if you make the population arbitrarily large, the 1% sample becomes large too. But can you really argue that being able to represent 99% with a binary spectrum isn't a pretty good approximation? What percentage would be good enough for you? Or are you going to say "99.9% isn't good enough because 7 million is a lot of people. that's more than died in X'?
So you agree then that whether 1% is negligible is based on context?
> Everyone here knows that if you make the population arbitrarily large, the 1% sample becomes large too. But can you really argue that being able to represent 99% with a binary spectrum isn't a pretty good approximation? What percentage would be good enough for you? Or are you going to say "99.9% isn't good enough because 7 million is a lot of people. that's more than died in X'?
Yes. In case you didn't notice, 7 million people is a lot of people.
Yeah, or as I put it: "Numbers get their significance relatively, not in themselves".
Whereas you repeatedly stated how 70 million people is a huge number in itself.
E.g. If I told you there are 70 million people that have blue eyes, is that "a huge number?" No, it's actually a small number. One would expect blue-eyed people to be in the 100s of millions or billions.
I haven't claimed that at all. I've said over and over that context indicates whether it's important.
> Whereas you repeatedly stated how 70 million people is a huge number in itself.
No, I've said 70 million people is a lot in terms of medical and social policy. It would be very possible, for example, for 1% of people to account for 10% of medical expenses--an amount you would probably care about at tax time. I think that's a number that matters to almost anyone's political goals.
In contrast, you've been repeatedly stating how 1% is not a large number. Based on what?
> E.g. If I told you there are 70 million people that have blue eyes, is that "a huge number?" No, it's actually a small number. One would expect blue-eyed people to be in the 100s of millions or billions.
Science doesn't give a shit about your expectations. "Expectations" are entirely irrelevant to whether a number is big or little. A number is big or little depending on what effects it causes and what effects you're trying to achieve.
You're accusing me of arguing that 70 million is inherently a large number, but you're arguing that 70 million is inherently a small number, completely arbitrarily. I'm not even saying 70 million people is a big or small number inherently, I'm saying that 70 million people is a huge number when the properties of that group have medical and social implications. 70 million blue-eyed people isn't a small or large number, it's an irrelevant number, because whether or not someone's eyes are blue has almost no implication that I care about. If you understand why it's not a big or small number, but an irrelevant number, you'll understand my point.
Language.
Also, I didn't say it's about "MY" expectations. It's about what the expected distribution is, which is the whole context that makes something big or small.
"Expectations" are entirely irrelevant to whether a number is big or little.
Actually, it's all about that. Bringing 10,000 times 6 by throwing dice 20,000 times is too big, because the expected outcome is about 1/6 throws to be 6.
0.1% of people fart right before falling asleep. 0.1% of people will commit murder in the next week. Now change the numbers to 20%.
In once case it matters a lot, another case it doesn't. Context matters when discussing populations also..
I've seen some estimates that suggest 72 million were killed in WWII alone, either from direct involvement or as civilian casualties. Considering the world population was ~2 billion at that time, close to 3.6% of the total world population died as a consequence of the war.
Oftentimes, it's helpful when comparing approximate statistics from different eras that you use the same relative baseline--in this case world population at the time those statistics were estimated rather than now.
Edit: Didn't see esrauch's sibling comment. Give 'em an upvote.
So one person isn't a lot of people ... are you saying one person is negligible? That one person's life doesn't matter?
Two can play this game.
1% is 1%. Every life is important, but 1% is still 1%. And 1% is not a lot. Whether it's people, apples, or pencils doesn't matter. It's a ratio.
Can we make laws, do medical research, etc. that will effectively help 1 person? I don't think so. If I see one person by the side of the road with a flat tire, I'll help that 1 person, but in the context of policy and research, 1 person usually doesn't matter because policy and research can't usually create a meaningful impact.
We can, however, make laws and do medical research that has an impact on 70 million people. I present as evidence for this the fact that life has gotten better (according to a variety of shared values which we could agree upon--fewer suicides, less violence) in the last few decades for people of atypical sexes.
> 1% is 1%. Every life is important, but 1% is still 1%. And 1% is not a lot. Whether it's people, apples, or pencils doesn't matter. It's a ratio.
No, context matters. If you don't think 1% is a lot in any context, maybe let's get you up to a 1% blood alcohol and see how you feel (hint: you won't feel).
Which is nothing this thread of discussion was about.
Nobody said not to study or legally hep those people.
Just that 1% is not enough to describe the total of cases as a "spectrum".
> Nobody said not to study or legally hep those people.
> Just that 1% is not enough to describe the total of cases as a "spectrum".
Assuming that your medical and social policies are at all data-driven, failure to include people in your data is a guaranteed way to ensure that they are not studied or legally helped.
Relative to the total population. Whether it's Canada, the US, France, or the Whole World you're taking into account, it's still 1% of it.
>You can't just say 1% is a negligible amount without context.
Probably you missed TFA and the whole conversation thread you're answering to?
The context was if only 1% of the population doing them is enough to call sexual preferences "a spectrum" (with regard to those "atypical sexual practices"). Something divided in 99% and 1% is not a "spectrum" by any stretch of the imagination. In fact there's a word for that 1%, outliers.
>1% blood alcohol will probably kill you, 1% error on your taxes, if intentional, is enough to put you in jail, 1% error in floating point arithmetic is the difference between a missile that hits its target and a missile that lands in a civilian residence. But numbers get their significance relatively, right?
Of course. 1% blood alcohol gets its significance not in what it is ("1% oh, so much") but RELATIVE to the amount that's OK for a human to stand.
1% error in missile calculations gets its significance RELATIVE to the target area it has to hit and the acceptable margin of error.
TFA and whole conversation are exactly the context which makes it ridiculous to claim that 1% is an acceptable margin of error.
> Of course. 1% blood alcohol gets its significance not in what it is ("1% oh, so much") but RELATIVE to the amount that's OK for a human to stand.
> 1% error in missile calculations gets its significance RELATIVE to the target area it has to hit and the acceptable margin of error.
Agreed. 1% error in judging the gender of people is significant relative to medical and social policy targets. On what grounds are you claiming that 70 million people are ignorable in medical and social policy?
Ironically, the only argument from you I've seen so far against sex being considered a spectrum is basically, "1%, oh, not so much". You said: "You say that like it's some huge number. 70 million or not, it's still 1%."
And ultimately, this is in research before we are even talking about medical and social policy. I'm not sure why we should just discard that 1% of data at all--there's no reason to artificially create error in reasoning that isn't imposed by data collection methods.
Keep in mind that social media generally exemplifies the dregs of humanity. The people who make a fuss about "Other" on the internet are not representative of the everyone in that 1%. I'm pretty sure you don't have enough information to make the statement you did above.
Moreover they'd probably be quite offended if you suggested they didn't belong in those categories, even if the wonders of medical science revealed they had certain abnormalities they might not even have been aware of or otherwise might have attempted to surgically "correct". Men with low sperm counts, men that discover they have a womb in their late seventies after fathering several children and even intersex people who had an operation a very long time ago are probably happier being bracketed as "men" than "somewhere fairly close to male on the gender spectrum", and the same goes for the women not wanting to be considered "further away from female on the gender spectrum" than their sisters because of polycystic ovaries. From this perspective we don't want to redefine gender as a spectrum so much as to accept that our definitions of "male" and "female" need to be sufficiently broad to encompass small quantities of genetic material transferred across umbilical cords and even the odd phenotypical abnormality.
Frankly, arguments against the gender binary are much better rooted in cultural phenomenon like South East Asian Katoeeys and Samoan Fa'afafine who openly define themselves as a third gender rather than medical abnormalities which for the most part people prefer to overlook or even medically "correct" to align themselves with a binary gender identity they feel mentally comfortable with.
True, but sex has medical and social implications that go beyond people's preferred terminology. You've brought up some of these concerns yourself.
> Frankly, arguments against the gender binary are much better rooted in cultural phenomenon like South East Asian Katoeeys and Samoan Fa'afafine who openly define themselves as a third gender rather than medical abnormalities which for the most part people prefer to overlook or even medically "correct" to align themselves with a binary gender identity they feel mentally comfortable with.
I'm not sure what makes you think that nobody in Western countries defines themselves as a third gender.
I'm not sure what makes you think I think that. But it's certainly considerably rarer.
In my opinion, we should be supporting or phasing out concepts depending on its usefulness as a predictive instrument. I don't think the "spectrum" lens offers any power over "two major sexes with many small discrete bins". But the spectrum view does seem forced, as if the intended effect is a more inclusive "we". Better would be to say that there are two major sexes, as well as some rather rare cases (MOST inclusive definition ~1%). They each belong in their discrete bins as domain-specific studies.
I also think you are letting your concern for humanity cloud your constructs. You seem to be very concerned about exclusion from normal. 70 million sounds like a big number if you were living in Europe at the time of the Bubonic plague. But this is the same problem with large numbers when we hear about state budgets. We hear titanic numbers, but it's hard to grasp how big or small it really is. How big is $100 billion to the state? Medium? A lot? A little? What if I said, hypothetically, that it was marginally less than 1% of the state budget?
Are you going to say to me, "Well, think about how even Bill Gates doesn't have $100 billion. Think about how much that would mean to you." ? If I brought it down to an intimate level, I would never be able to talk about huge numbers because it hits my intuition too hard.
However, I don't think the researchers would accept testosterone as an adequate spectrum to contain human sex. So what spectrum is proposed, then? I have difficulty imagining, because I think having a spectrum of Maleness vs Femaleness would be antithetical to what the researchers want.
An approximation, by its nature, is simplistic compared to reality. That's what makes it an approximation.
Sex and gender are shoved in people's faces practically every waking moment which means this "highly accurate approximation" breaks down billions of times a day with consequences ranging from discrimination and depression to sterilization and death.
How certain are you that you or some close doesn't fall outside the binary?
I'd suggest that it all comes down to how we're making those observations and what we're then doing with the classifications we've derived.
Why are we trying to describe the idea of biological sex? If it's for the sake of a scientific classification, then simplistic is a horrific idea. Biology by definition (in a modern world) is dealing with the small scale deviances and the nitty gritty. We're 99% rat, but the differences are somewhat remarkable.
We've been observing the wrong thing for thousands of years. Your assertion is almost correct; 99% of the time the _outcome_ of observation might be male or female, but it doesn't actually _explain_ anything. All it does is answer the question "does it have a penis"[1].
Which in 2015 has far less medical relevance than it did in centuries gone. "Well Mr. Smith, she is of the weaker species, this little touch of the vapours is to be expected, of course." is a diagnosis heard less and less. We're now increasingly diagnosing and categorizing conditions a genetic level, never-mind just what your second sex chromosome is. [2] From a technical point of view, it's already far more complicated than male/female. Simplifying science to that degree does it a disservice.
The big problem with binary though is the way it permeates through culture, language society and even thought.
Essentially, at birth, we clumsily label and categorise people based on their sex organs and worse, refuse to officially acknowledge the grey area. It's like asking someone with severe allergies if they want the shell fish or the peanuts. "Oh I'm sure they would both kill you, Sir[3], but you will be eating one for your entrée"
Put bluntly, I don't effing understand why everyone is so interested in what I have down my pants? You'd think it's entirely irrelevant except for some very specific circumstances, but instead we all have to publicly broadcast this binary allegiance all day every day. Everything. Pretty much every trivial form online makes me choose between "Mr", "Mrs", "Miss" or "Dr"[4] and usually as a mandatory field and yet you really don't need to know if I have a labia or not to be able to print my name and address and post me a parcel. It doesn't need to announce this on my bus pass or in nearly every english pronoun.
Through childhood I repeatedly went through conversations along the lines of "Which football team do you support?" I don't. I don't watch football. "That's fine, but which team do you support?"[5]. Not having an allegiance, even a lapsed one, is not an option.
By simplistically describing homosapien sex as binary it means anyone who doesn't conform is left out. It's not a legitimate option. Not viable, abnormal, mistakes, a freak of nature if you will. We're essentially saying that these people are inhuman and unnatural, which is obviously untrue.
The UK has allowed people to change their legal gender for over 10 years now[6], which legitimises the idea that external observation and internal state might not be linked. Simplifying that disparity to a binary state though, does a great disservice to the human condition. It seems odd that it's now legitimate not to identify as M||F but you've still got to identify as M||F.
"No", "Other" or "I don't know" should be a completely legitimate answer in response to sex or gender. It needs it's own category, it needs words to identify it and language to be able to describe it otherwise it's not a real thing, it's just anomalous.
And anyway, I'm disappointed; this is hacker news. Define it as either binary value or a boolean, but we should all be aware that as well as TRUE or FALSE, 0 or 1, variables can legitimately be undefined and it's something you have to be capable of handling.
apologies for the rambling answer.
--------------- [1] Admittedly a bit glib, but ignoring the last 120 years of science this is probably the most distinct observation we've been able to make of a live subject. Talking points might include testis and eunuchs, the ability to give birth and the difference between sex, gender and gender stereotyping... oh, and sea horses.
[2] http://www2.le.ac.uk/departments/genetics/vgec/highereducati... vs http://en.wikipedia.org/wiki/XY_sex-determination_system
[3] Penis
[4] which until rather too recently has basically meant "penis", "already owned by a penis", "has no rights, available to be owned (warranty void if introduced to thinking)" or "even more respected penis".
[5] Feel free to make your own analogies; I recommend some of the misunderstandings between religion and atheism or the futility of voting for a political party you don't like as starting points.
[6] http://en.wikipedia.org/wiki/Gender_Recognition_Act_2004
That's true in the abstract (undeniably, some scientific fact is confounding -- I don't need to know about about quantum uncertainty to cook dinner) but I don't think it applies well to this issue.
This report may confound some people's understanding of sexuality, but to people who don't fit that conventional understanding, and to their loved ones, it does the opposite. Imagine a lifetime of being reminded that you don't belong -- every bathroom sign, do you attend the girls school or the boys, every form you fill out, every locker room experience, every medical procedure, etc etc. Addressing that seems much more important and fair than reducing the confusion that new ideas can bring.
This is the nature of change and progress: Humans naturally are very egocentric, and can be wholly unaware of others' experiences and perspectives. When the reality of those experiences is thrust upon us, we often object -- everything seems fine to us, after all, and our old theories explain our experiences.
Think of the responses to racial and gender discrimination, where many in the majority insist that it doesn't exist. After all, they haven't experienced it.
The point I'd like to make though is that sometimes we use science to justify intolerance, and time and again the science has caught up with what people have reported as their own life experience.
The problem is that most people's life experiences seemingly justify intolerance, in the sense that most people's experiences of most things are fairly typical. It's a serious epistemological problem with science, and is one of the major reasons why using science alone to create legislation is problematic.
Do you have any examples of this?
What? How can discovering the natural laws of the universe be a justification for intolerance?
Pretend for a second that science discovered convincing/rigorous evidence that white people were less intelligent genetically than other races. That isn't justification for intolerance against white people. We get to choose our values as a society, independently of the reality of the world around us. Science is a poor justification for intolerance, no matter what arguments people may attempt to make.
It is a poor justification for intolerance, and that's part of what the original poster was pointing out. But just because it's a poor justification doesn't mean it hasn't been done. People (as a collective) are not inherently rational or logical. They're easily led by the nose by charismatic speakers and those skilled in rhetoric. They want to believe they're special or that someone else is to blame and when someone presents something that helps them believe that they lap it up. It's happened throughout history, and it'll continue through the future. The best we can hope for is that our understanding of the universe and nature casts light on more things so those that would abuse it have fewer shadows to hide in.
I suppose. But the question still stands: what if there was rigorous evidence that one race was genetically more intelligent than another? We need to have an understanding that such data would in no way be justification for oppression or mistreatment. We get to choose our own values. That needs to be the message, IMO.
We would, however, expect white people to be underrepresented in positions that require high intelligence (medicine, STEM, politics, CEOs, etc) and understand that this underrepresentation would not be indicative of racial discrimination.
For example, this criticism of a woman expressing thoughts on her own experiences: http://jezebel.com/kirsten-dunst-thinks-ladies-in-relationsh...
For the overwhelming majority of organisms, including Homo sapiens, all proposed indicators of sex (anatomy, hormones, cells, chromosomes) give the same answer. Reading the final two paragraphs of the paper, it's obvious that attempts to muddy this naturally clear water are being made for political, not scientific reasons.
FTFA: > So if the law requires that a person is [sic] male or female, should that sex be assigned by anatomy, hormones, cells or chromosomes, and what should be done if they clash?
Easy, have laws not discriminate by gender. Isn't that the point? No need to discuss biology on and on to help some agenda.
Reality is never as neat as our models of it are. The question is what we do about it. This reads to me like a call to arms for handling the exceptional cases better. I could get behind that.
There's no need to throw out the male/female binary for most situations, though. Exceptions can be handled as exceptions, as long as you know they exist.
"[...] all models are wrong; the practical question is how wrong do they have to be to not be useful." ~ George E. P. Box
This seems more true for behaviour than it does for physiology, but findings like those in the article make it harder to draw even that distinction.
[1] http://www.cdc.gov/ncbddd/birthdefects/features/birthdefects...
Sounds to me like someone is reaching to make science match the way they feel about gender.
// and yes, we have to ask as their a whole lot of laws and scholarships that reporting requires the number
Of course, if you have external requirements to capture sex/gender, they probably also dictate the valid options. If you have multiple different external requirements, the options may be different for each and the correct value for the same individual may be different for different purposes. One value may not be sufficient.
If there are people in this world who wish to reject the concept of gender association with our biological reproductive systems, is there a need to provide additional classification, rules of governance, services, etc. other than "Denies classification"?
Otherwise, are we not chasing a long tail of specific situations in which everything can be deemed intolerant?
[1] http://en.wikipedia.org/wiki/Boolean
[2] http://en.wikipedia.org/wiki/Binary
note: this is a re-post of a comment made on a child of the OP.
In the very link you provided: https://en.wikipedia.org/wiki/Gender_binary
Being in a state of one of two mutually exclusive conditions such as on or off, true or false, molten or frozen, presence or absence of a signal