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Yes, but that makes it a singular factor like testosterone rather dubious. And again, we are switching between elite sports (which is part of OP) and the biology a fair bit through the thread a fair bit. And as your link actually argues, the biological concept of sex (regardless whether one agrees with the author's definition or not) is not really helpful or applicable to human questions (such as sports). And for the latter, the key element is still more information. Studies are indicating that testosterone as sole indicator is too weak to assess risks, for example. Clearly in sports like boxing better indicators appear to be weight, and muscle mass, for example. And if there are better indicators, it would be time to ditch traditional but inferior methods. Some of the papers measuring testosterone levels among athletes are arguing that precisely. For example: There was a recent paper suggesting that testosterone might have been a factor in male performance (or something to that effect) but then they issued a correction and stated that they actually do not have the data to suggest that (as they did not measure other data such as LBM (lean body mass) as the paper above. As suggest previously, depending on the types of sports it might be worthwhile to look at a) demographic input and b) potential indicators for class formation (e.g. using LBM or other factors as appropriate). Demographics can be important as some sports may have large differences in term of participation. Different groups are then sometimes created not because of performance differences, but to strengthen participation. Trans folks are more likely to cross categories that way, but at least they would not be fundamentally excluded based on assumptions. I.e. there is a need for evidence-based inclusion strategies rather than assuming things and then go from there.

If we look at this individual dimension and ignore e.g. the fact that individuals can react very differently to the same hormonal levels). Problem is data is scarce for the few that do not fit the binary definition. That being said, there are profiles in athletes and some indicate overlap between male and demale athletes in the extremes. https://doi.org/10.1111/cen.12445. However other cohorts show less overlap and there was one study with longitudinal showing overlaps when one considers the fluctuations through life but I think. But that is only part of the issue. The other is that folks have different sensitivity to hormones. In the extreme case e.g. insensitivity to testosterone leads to development of female features. In sports they tried to implement a testosterone threshold, but now several women have run afoul of it without any drugs (just genetics). And finally, because bodies react differently there is still no clear correlation between testosterone level and performance. Athlete surveys don't show that top performers have the highest levels, and there seem to differences between disciplines (power lifters were among the lowest in testosterone in the male group, iirc).

Sorry, cross-posted, and added some more details. But overall I think that the authors attempted to simplify the model, which, in for all purposes has worked fairly well. But more recent research focusing on aspects of sexual selection and evolution of sex has put some dampers on prior assumptions. I am no expert in this field, so I cannot interpret the whole situation accurately, but depending on how good the data and experiments are, (some of which are at least mentioned in the paper I linked above), there might be a broader rethinking needed. But that is nature of science, the more details we get, the more we chisel on grand old concepts.

I think the idea was to reframe into a gamete specific discussion, but then they kind of got selective and used a fair bit of handwaving without getting into the necessary weeds. The paper I linked picked up on those bits. But I would still characterize the whole discussion as "what is useful" rather than "what is true" and perhaps ironically they claim anthropocentrism as the reason for this issue, but at the same time they use the same to form their argument and kind if try to simplify things down. I.e. if an organism changes its sex it is clearly still a binary situation, either they produce ova or sperm. Yet developmental it is not necessarily a full switch. They say that beyond humans there are all kind of changes from being both, to switching between asexual and sexual reproduction or have no sexual reproduction at all. That is all true, but unclear why that would be an argument for binary states? They then further argue that sex can be a stage in life, and they say that But it does not appear that the follow up on what it means to the definitions we use under these assumptions. I.e. a menopausal person would then be considered, well asexual, I suppose as they would never produce ova or sperm. They do acknowledge that these definitions therefore are not great to describe the human condition (i.e. applying those concepts would define things very differently, as in my example) but ultimately fail to support why then all things considered a binary definition would be useful.

I don't think that science would be necessarily poorer, at least not directly. Though science popularizers can indirectly improve science by raising general interest (though I have the feeling that things are getting a bit worse now). Many scientists I know are more of the nose to grindstone types of folks and they (we) are often a bit suspicious of the more showy scientists. Generally speaking, I tend to be a bit more suspicious of highly charismatic or influential folks as there is always the risk that their work faces a bit less scrutiny than junior scientists. I.e. the persona might at some point start to influence their science.

l and social scientists are,rather than a binary trait. "Biological sex is binary, even though there is a rainbow of sex roles Abstract Biomedical and social scientists are increasingly calling the biological sex into question, arguing that sex is a graded spectrum rather than a binary trait. Leading science journals have been adopting this relativist view, thereby opposing fundamental biological facts. While we fully endorse efforts to create a more inclusive environment for gender-diverse people, this does not require denying biological sex. On the contrary, the rejection of biological sex seems to be based on a lack of knowledge about evolution and it champions species chauvinism, inasmuch as it imposes human identity notions on millions of other species. We argue that the biological definition of the sexes remains central to recognising the diversity of life. Humans with their unique combination of biological sex and gender are different from non-human animals and plants in this respect. Denying the concept of biological sex, for whatever cause, ultimately erodes scientific progress and may open the flood gates to “alternative truths.”" Essentially, human sex is binary, with a very limited grey area. 99+%. Most with intersex traits are still XX or XY. I like the fact that you are citing a paper (I really appreciate it) and it is true that there are discussions on this area in the scientific community. I won't bemoan that this an essay, as this discussion likely has to be at least partially argued outside of a more data-driven discussion. Since the paper is still very fresh, there is not a lot of follow-up, but I will put in here one alternative view on it.: https://www.biorxiv.org/content/10.1101/2023.01.26.525769v2.abstract The paper does provide a nice summary of the gamete-centric approach (apologies for the line counts). This is especially relavant as Goyman et al. argue about the scientific necessity of collapsing those terms. I.e. the base argument is not about what is "true" but what scientifically useful (an important distinction). A more philosophical/conceptional approach to this question can be found here: https://doi.org/10.1017/psa.2023.86 And an evolutionary view that questions the strong link between gamete dimorphism and and assumption of sexes can be seen here: https://doi.org/10.1016/j.tree.2023.04.013 While the latter is not necessarily a reject of binary biological sex definitions as such, it questions some of the basic tenets that make a binary definition useful for biological sciences. But again, to avoid any confusion, the discussion here (found JCM's link) is rooted in a gamete-focused definition of sex (i.e. not karyotype, sex chromosomes etc.), which is often used in science, but less in common parlance. Here the definition is base on the size of gametes produced by a group (e.g. small like sperm or large like an ovum). The papers I added discuss why even with this definition things are trickier than outlined in the essay. Also, the definition is centered around an evolutionary view (in terms of e.g. establishing and maintaining gamete dimorphism), sterile organisms are not present in this category. There is quite a bit to wade into scientifically, but it this actually shows that scientifically the distinction is not quite as trivial and straightforward as we have learned, especially when we want to find an universal (biological) system or model.

I should also add that the pandemic might have increased levels in at least some jurisdictions as infections have been associated with increased risk of developing either Type I or II diabetes. But considering the baseline, it is also very possible that the levels have not moved much.

You should re-read StringJunky's excellent response. We define things based on context, adding the moniker "true" does not make them more specific. Karyotype-based definitions are fine in many, if not most contexts, so do phenotypic definitions (e.g. based on presence of genitalia). The fact that one needs to add a "besides" in a categorization clearly shows the lack of rigidity as an universal system. This is something to keep in mind (i.e. don't confuse the model with the reality). For sports, the phenotype is going to be more important (as the karyotype alone does not define physicality) but there focusing on genitalia alone is a bit weird, as I do not know of any official sports where these are used. As mentioned before, other sex-associated attributes (hormonal levels, muscle mass etc.) are under investigation to figure out suitable categories, which in my mind seems to be more geared to solving the issue than trying to figure out what a "true" man or woman is. If there is a person with a XY karyotype (or has a penis) but is lightly built and with a low muscle to fat ratio then they probably should not be put into the same category as wherever Mike Tyson-type athletes would be put in. While this would eliminate most, if not all folks with an XX karyotype it is at least not based a priori on aspects unrelated to the issue themselves.

I get what you are saying, and it is a general issue in public health that folks tend to think in extremes (e.g. deaths) but forget about health burden, loss of quality of life, and associated cost and drain on the health care system. After all managing a a disease for decades is often more expensive than just dropping dead.

Well, I am not sure about corporate pressures. In some cases, where there is corporate funding or support, that could be the case, but often it is just the publish or perish pressure in academia that makes people fudge, encourage fudging or at least ignore evidence for fudging. Also remember in most labs much of the work is done by students who might not continue in the field but are desperate to graduate and/or postdocs who are desperate for a faculty job (or really, any job). There is a bit of a pattern here, I think. Medical research (which is very different from practice, but there also areas researching medical practice) is fundamentally biological, but requires higher precision and demands more impact than (but is also better funded) which may put more pressure on folks. At the same time I think it is quite self inflicted as medical research is also quite averse to fundamental research aspects, which could help creating a better foundation. Also the pessimist in me also sometimes thinks that stuff comes out more in medical research as there can be trials which ultimately invalidate results, whereas if someone messes up (knowingly or not) something regarding an exotic bacterium and has rather mundane results, know one would care to follow up.

The data is for total (including unclassified). But the vast majority is typeII.

Actually outright falsification (if done well) are really hard to spot in a peer-review process. While there are calls for open data to address these issues, there are a huge load of limitations (both structural and practical). There is no easy solutions, but one obvious red flag is the culture that he cultivated. If you force your team to get a specific result, well, there is a good chance that you get it, if you just demand hard enough... But I do agree, the fact that these issues are exposed is on a whole a good thing.

I am not sure why having a broad definition is an issue. In fact, it is rather necessary to assess health burden. I may be misunderstanding OP, but it sounds to me that it is potentially assumed that "chronic" is somewhat aligned with severity and should therefore be visible. However in this context the issue with chronic diseases is that they require ongoing management, regardless of severity. A lot of folks have hypertension, for example. Often it is well managed. Similarly, you would not easily notice folks with osteoathritis or osteoporosis other in their most extreme forms. Likewise, depression is a chronic disease, which has spiked a fair bit during the pandemic. And if you go down the list of common chronic diseases, it is rather easy to see how you would get to 40-60% of the population having at least one of the issues especially taking an aging (and/or overweight) population into account. It should also be noted that chronic disease information in various jurisdictions can vary or missing, so comparison between countries could be difficult. Some require multi-year treatment rather than 1yr to qualify, or could be based on self-reporting (as in some European databases). That being said, diabetes is a very strong indicator with enormous health burden and we can see here that the UK has a surprisingly low prevalence (about 4%), whereas Canada, Germany USA and Mexico are way higher (7.6, 10.4, 10.8 and 13.5).

So a person with gonadal dysgenesis (Swyer syndrome, fully developed female genitalia but XY karyotype) a real woman? Or a real man? Or do you consider them fake somehow?

That is the difference between a human classification system and what is in the natural world. Nature has all the variability, including non-viable, sterile and everything in-between. I.e. they exist. Our classification system is cruder and as you mentioned, mostly ignores rare conditions in most contexts. That does not make them non-existent. At minimum we have therefore XY, XX and one big box for all other configurations on the karyotpe level (which by my count exceeds two categories). It should be noted that this is not even all that determines the development of sexual organs. Folks with Swyer syndrome, for example have an XY karyotpe, but develop female genitalia. So the karyotype would be male, but the phenotype clearly female. Gender development is not fully genetic, but has strong developmental aspects. During childhood we develop something that we associate with our identity and including aspects like sexual orientation (which are further developed during puberty) but also gender identity. While there appear to be genetic dispositions (which are still under investigation), the link is likely quite a bit more complicated. As far as I can tell, no one decides out of the blue to be of a certain gender without some form of identify formed behind that.

Are you serious? Do you think that all the data in the papers I linked were gained from harmful interference? Do you think we should just assume things rather than quantify and measure actual differences?

Research.

Folks are investigating this issue, and I do not think it is helpful to use sweeping assertions without having the data. Muscle strength alone or even just looking at outliers (i.e. top performers) is insufficient to discuss the broader range of sports (after all, not all athletes are fall into the narrow range of record holders). For sports requiring explosive strength there is likely an advantage that might not be overcome by transition. Also, a careful look at full-contact sports makes a lot of sense for safety issues. For others, there is data suggesting various levels of adjustments are feasible. For example, in archery, data suggests that transwomen might compete with cis-women on equal footing after two years of treatment: https://doi.org/10.1080/17461391.2021.1938692 There are other studies underway that test multiple performance measures (e.g. multiple muscle measures, lung performance, heart performance etc.) in transgender athletes, which would provide better information on what sports might or or might not need adjustments. As such, little has changed from the start of the discussion in which it has been mentioned that better data is needed.

In that context one should also to keep in mind that absolute risk, is often not helpful for decision-making. Rather, one probably should think more in terms what the risk of taking a medication is vs not taking it, within a given context. Specifically for stomach cancer, the rates are fairly low, and even if doubled, it is not terribly higher. So if one was a smoker or live in an area with high radon levels, the risks are quite a bit more relevant, for example.

A paper was just published estimating heat-associated deaths in Europe during 2022, which was the hottest year on record until this year. Overall, the authors calculated 61,672 (37,643-86,807 CI 95%) heat-related deaths. Considering that the predictions indicate that things are not going to be better (quite the contrary), it show the immediate impact of heat on humans, even without considering broader ecological implications. https://doi.org/10.1038/s41591-023-02419-z

No one said that it should not be investigated. In fact, they are still underway. And many have been done in the past (I have seen studies going back to the 70s at least). None of them have found strong evidence for carcinogenic effects in humans so far. Required evidence is usually based on existing evidence levels, with clinical data (which is part of the approval process) having the highest weight. The actual evidence for cancer risk in humans is still low, and a bigger worry at this point is neurotoxicity during prolonged use. What ultimately has to be evaluated is the cost/benefit. Many drugs, including antibiotics, anti-cancer drugs etc. are highly toxic. The question therefore is whether there are groups which ultimately have more benefit than harm. Obviously, if there are alternatives that are lass harmful, they would be preferred. Some other antibiotics that can be used to treat certain conditions (such as Chron's disease) but depending on the person, the side effects can be more or less severe. There are basically no harmless drugs. Just various levels of harm. Again, the premise is not that we can only use drugs that have no risk of harming the patient. This is just not viable. It is about finding treatments for conditions that overall have the best risk/benefit ratio for a given condition and a given patient. So far, metronidazole makes the cut and with antibiotics efficacy waning, more toxic ones will be see increased use. If the intention was to create the perfect drug before use, well most of us would probably be dead before that happens. That all being said, I will agree that over prescription can be an issue. But that is not dealt with by kicking out drugs from the portfolio. Rather, we need better and faster diagnostics to ensure that we only prescribe antibiotics that are needed. With cancer risk, conclusive evidence under therapeutic limits is very difficult. It is looking for rare cases among rare cases requiring huge cohorts to see an effect. As such having enough statistical power to show no effect is going to be exceedingly difficult. I.e. the rate of stomach cancer is maybe around 10 per 100,000 persons. So even if you enroll 10,000 control cases and 10,000 folks taking the drug, you may have maybe one case, which could be purely stochastic. Even worse, you would need to track them for years which would make it a tremendously expensive study. So realistically you would need many individual studies and try to look at a meta-analysis, or more likely have retroactive surveys. The issue with the latter is that there are a lot of confounding factors beyond the drug under consideration that may affect cancer risk. So even those might not reach enough folks to figure things out. That all being said, some of the earlier studies in the 80s tracked over 700 patients for close to 10 years, seeing no effects for patients treated for trichomoniasis for any types of cancers (if adjusted for smoking). Another study was retrospective and looked at matched patient data (i.e. similar groups but one with and another without treatment) for about 10-12 years found no effects for short-term exposure, either. Since then, there have been follow-ups using similar designs but no smoking gun. That being said, other commonly used antibiotics are starting now also to be suspected to potentially be associated with cancers during long-term treatment. For example one retroactive comparison between clarithromycin compared to metronidazole (there was no untreated patient cohort) showed that clarithromycin had a higher overall death and cancer risk than metronidazole after follow-up. (And interestingly clarithromycin is also under discussion to be used as a potential repurposed drug for cancer treatment at some point...). Also, it is necessary to look at risk in context of overall risk we are willing to commit. For example, certain diets are associated with cancer, and we are likely to eat more of it and for longer than an antibiotics course. In summary, folks look at the available set of info to assess risk/benefit. Sometimes the assessment is wrong (thalidomide being one of the famous examples), but it always is based on need and empirical evidence. Otherwise, options would be really, really limited.

Helicobacter infections are associated with a potentially four to eight fold increase in stomach cancer. For metronizadole there is no clear linkage, hence no numbers. That is where the designation comes from. It is plausible due to the animal studies, but so far no human cohorts have found a difference between users and non-users. If a linkage was found, the designation would shift.

Reality is rather different from movies. There are cases when bullets are likely to cause issues (e.g. in joints, at nerves or blood vessels) where there are routinely removed. But beyond that, they are often left alone. Fundamentally there is no mechanism of the body to get rid of larger stuff that is deeply embedded in wounds. It can get isolated and then sticks around (literally). But there is not really a mechanisms to move larger things through the body cavity in mammals that I am aware of. In frogs and fish folks have identified mechanisms in which foreign objects were removed. In case of the frog it was eliminated through the bladder and I believe in some fish it was observed that the objects moved into the intestines.

Most folks are not saying that though. Rather if there are quantifiable differences, one should use those as much as possible. That also goes for race, but it has to be actionable. In other words, one needs to find better rules for sports to find the right balance to maximize inclusion. Likewise, rather than just saying we end racism and all is well, we have to look at the quantifiable harm and use measures to address them. Targeted, if possible, untargeted if it provides a net benefit. Also, I could turn this argument around. You say that skin color is superficial, whereas the sex differences are clearly impactful. However, at the same time we have got much, much, much more data on skin color, in practice, affects folks to huge degree in terms of all kind of life outcomes. Conversely, the studies on transgender athletes is only now starting and folks only recently have a handful of data points in terms of these quantifiable differences. While I do think that for some sports there is likely going to be disparities that need to be addressed somehow (I have speculated earlier in what form it could be), but ultimately we need more research. I think, to some degree your argument is guided by how you think the world should be (in terms of racial equality) and how you perhaps sense race, yet the reality of it it is very different. And policies need to address that.

Also, in the context of this discussion, you wouldn't just use taxon, but name what level you're speaking of. E.g. species x is extinct or genus y or family z. There are also different types of taxonomic systems (basically different ways to build the family tree) and you would refer to which system you are talking about. I.e. you define the sets you're speaking or you use the commonly accepted consensus. But you don't randomly fill it with a bunch of things.