"This model of estradiol’s role in improving resistance to wound sepsis predicts at least four “sexes” across two treatment groups: females who are in the proestrus phase, females who are in the diestrus phase, females who are postmenopausal, and males."
This is Sarah Richardson, of the Fuentes review.
Four "sexes", three of them female and the other male. JFC.
A cell line derived from an unusual cervical cancer (one that spontaneously immortalised) is not even "human", let alone "female", apparently.
It's cervical cancer cell line. Only women have cervices (pl?). JFC.
And the cells are grown in media that contains hormones, so that deffo makes the female origin basically meaningless. JFC.
"The propositions that “every cell has a sex—male or female” and that sex as a biological variable is sufficiently considered when biological materials derived from “both” sexes are included in research reflect an essentialist and binary biological concept of sex."
No Sarah, it means that cells derived from a male body might contain useful information and cells derived from a female body might contain useful information, and shall we check that? JFC.
She's literally arguing that we should classify people as with/without uteruses, or in another context with/without testes, or whatever. You lose the bigger picture. JFC.
Ironically, you lose the gendered contribution to medical care for which she is advocating.
"Age itself is not a biological variable, but the biomarkers that make up age in each of these different tissues and levels of biological analysis can be understood as causally related to age, conceptualized in a variety of ways. We speak of “age-related variables,” understanding that what these are in any instance will be specific to the tissue, field of research, current state of technology, and so on. This “age contextualism” is just how I propose we think of sex."
She's just arguing that we can disaggregate a data set by "biological age", should we wish. I mean, cool.
But she's missing the point. Here is a cohort of +60yo. Most of them of have This, but some of them don't.
Here is a cohort of -60yo. Few of them have This, but most of them don't.
Studying by age bin helps us find the stuff we might be interested in. The +60s who don't have This, maybe they have an odd gene variant. The -60s who do have This, maybe they don't eat their spinach.
But finding patterns requires a broad understanding of one of the key variables you think is associated with an outcome. She misunderstands what SABV tries to operationalise.
But then, she publishes with Madeline Pape, who is the IOC sociologist who has tried to destroy sex categories. So quelle surprise.
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Apparently-female athletes who test positive for SRY will have a consultation with WA, with a view to medical assessment to better understand any medical conditions (DSDs) they have.
It is this diagnosis that will determine eligibility (or not).
After a primer on sex development, Sinclair tries a gotcha.
Describing Swyer Syndrome and CAIS, he argues these athletes would be unfairly excluded.
But WA makes it clear that CAIS is exempt from exclusion. It’s in both the policy and the press release. I doubt Swyer would be excluded either.
Five years ago, I gave a speech comparing sex denialism to creationism.
At the time, my partner-in-crime, Colin Wright, and I were near-lone academic voices willing to stand up and say “Biology! We have a problem!”
@SwipeWright
Reflecting, back in 2020, on that state of affairs:
“[That] there are two sexes, male and female is apparently something that biologists do not think needs to be said.
I think they are wrong.”
Since then, biologists with far more authority than an unknown developmental biologist who was trying to work out how nerves navigate over muscles and an unknown evolutionary biologist who was studying what makes insects mad have spoken up.
Several people argue that if the metrics of a trans-identified male fall "within female range", it is fair for that male to compete in female sport.
But we need to look at what's typical .v. what's exceptional.
Male traits often overlap with female traits. Height, muscle mass and so forth all generate normal distributions within sex (bell curves), where the lower end of the male range overlaps with the upper end of the female range.