The primary issue (IMO) is the remarkably large number of scientists and physicians who abandoned facts and science in favor of ideology. A large number did not abandon their patients, but their voices were ignored or silenced. Which of course takes us back to the death of journalism, but that is another topic.

The lethality of COVID in 2020 before much was known (released?) about it would make exposure to even healthy willing volunteers problematic; some young healthy people died from COVID, so a study where one of the reasonably foreseeable outcomes is death for the participant is not ethical.

The death rates FROM COVID in 2023 are now (as best I know, I haven't looked specifically but I do work in an busy emergency department and the last sick person I've seen who was sick from COVID is quite a while ago) much lower as the virus has mutated, so it would probably be reasonable to do actual masking studies with young healthy volunteers. You can approximate the efficacy of masks by using non-infectious particles, like radioactive substances that are the size of the virus and track where they go when someone talks, coughs, etc, but the uncertainty around how infectious that substitute "viral load" would be is pretty high. And all you could really get is a measure of how effective the various masks are at decreasing the exposure rather than decreasing the infection rate.

The choice of mask mandates for children was always farcical on its face. Reasonable data from Sweden, who did not lock down and did not stop in person school, followed shortly thereafter with pretty good data from the US, all pointed to no benefit for masking children (or ending in person school...). But by then the politics had taken over.

If President Trump said XX, the media, CDC, NIH etc said NOT XX. Science was not involved even when scientists were making recommendations. There is no other way to explain the banning of one of the most well-studied and safest medications available to POTENTIALLY treat COVID, namely Ivermectin. The number of medications used in the US off-label is staggering, and the regulation of that phenomenon is generally left to doctors and their patients. That was not the case with Ivermectin despite a fair amount of data that suggests it is better than most of the (poorly studied) anti-virals pushed by the FDA over the course of the height of the pandemic.

Asking good questions is the mark of good science, and understanding that the answers have some amount of uncertainty is the mark of good scientists. When scientists suggest some science is settled, be skeptical...1 mole of HCl and 1 mole of NaHCO3 pretty much always yields NaCl, water, and CO2, but science involving humans is never as settled as that.

Randomizing and blinding for human clinical trials is done in part because of the enormous complexity of a human; controlling for all the variables except the variable of interest is not possible (unless you are doing an N=1 trial, which is a different discussion). Randomizing is done in part so that all of the other uncontrolled variables are spread evenly across the participants, and succeeds sometimes, and not so much other times.

Blinding is done primarily to remove conscious and unconscious bias, but in a study examining the transmission of COVID, the only person who really needs to be blinded is the person doing the nasal swab. Positive and negative tests are fairly objective, so once a sample hits the lab bias is no longer an issue.

SO the real question appears to be something along the lines of "if we want to live as normal a life as possible and reduce the spread of COVID, do masks reduce the transmission, and by how much?"

Let's take one infected unmasked person, and put them in a room. We can take 16 uninfected people, each wearing one of 4 masks (no mask, a cloth mask, a surgical paper mask, and an N95 mask). The participants could sit around a table and recite some text, while the infected person walks around the table reciting similar text. Let's leave everyone in the room for 30 minutes.

THEN we check the exposed folks daily for a number of days, and determine the infection rate based on those condition and their masks. While we are waiting for those results, we repeat the experiment every hour (deep cleaning the room in between runs) with the same infected person, and 16 new uninfected people. For the second run, the infected person wears a cloth mask, then on the third run a surgical paper mask, and then an N95 mask for the last run.

You could add more layers; what happens if the air system in the room has the same operating parameters as an airplane cabin? Now you can do 4 more runs, ideally on the same day with the same index infected person.

What are the confounders that will add uncertainty to your results? The immunization status of the participants, whether or not they have previously had a COVID infection (and when), their underlying health status, and a myriad of other variables inherent to each person.

You also need time, space, and money to do such an experiment, and in 2020 that would not have been an ethical experiment so it could not be done. It MIGHT be an ethical experiment in 2023 with the current variants of COVID, but even that is unclear.

And depending on the transmission rates with and without masks, 65 people might not be enough to find significant difference. There are sample size calculators that help us with that; we just need to estimate the transmission rate with and without masks to decide how big we need to scale our study to determine any effect, and the uncertainty around that effect.

Many things, none of which are particularly important as the feelings of the patient don't override the science of the sex. I haven't met a surgeon yet who planned a hysterectomy only to find out in the middle of the operation that the patient identified as a woman but was randomly assigned male at birth.

The history and an initial planned workup can be jumbled if it is not obvious which sex the patient is, but that is easily addressed once a physical exam or a more detailed history is taken, when they are important. For example, if you have a sprained ankle, neither your sex or gender identity alter the treatment for the injury. If you have abdominal pain, your sex and the presence or absence of various genitalia do become important in the workup regardless of your gender identity.

Nope; it's a response to a stimulus with numerous psychosocial aspects.

Choose a stimulus, say, insert a specific size needle a specific distance into a specific part of the body. If you do that with 10 people, and ask them to measure the amount of pain they experience, you will get a range of answers.

More importantly, if you do the same "test" on the same person, say, twice a day for a week, you'll also get a range of answers. How we perceive a stimulus is influenced by many variables which can change day to day, or even hour to hour.