Outside the realm of the testable isn't worth discussing to experimentalists so might as well be a non quantifiable field.
Although sociology is perfectly quantifiable and measurable. Even though arguably the underlying relationships between the measurements are extremely difficult to extract.
A better example is pure philosophy and maths rather than sociology to particle theory. But then again, nobody ever accused QFT of being too simple, so maybe I'm arguing against my own point there.
The moon example is painful, but I was assuming to be a "if the tree falls in the forest... yada yada yada..." Example to justify words on a page. Although at the time my brain was screaming about things like tidal forces and gravitational effects, asif I was about to start discussing the retrograde motion of Venus with a flat earther who doesn't actually want to learn anything with rigour...
Personally I'm more worried by the comparison of Planks constant in the small to c in GR. Yes they represent asymptotic limits in many regards but are certainly not equivalent imho.
NB: most people choosing not to take it in France tend to fall into the medically at risk, stubborn, or, "so far down the rabbit hole that you probably can't trust these people to make sensible life choices" groups.
(This alone being a good reason why this 'control' group had a slightly higher all cause mortality at 6months)
Remember, France was one of the wonderful countries where you couldn't legally shop or work if you were deemed to be 'not at risk' && 'unvaccinated' and achieved a very high rate as a result biasing the control group. (This is a purely statistical statement)
And for reference, I do think the vax is dangerous in terms of massive populations and we don't have mass graves due to mRNA problems (although several large cancer blips). In the same way in countries with low vaccination rates we don't have mass graves at 10% population or higher. Cv19 was always going to kill and an untested treatment is likely to kill those who were at risk.
(I'm willing to bet in the case of cv19 the ones who were hit hardest would have been hit badly by either vector, virus or mRNA. But we'll pretty much never be able to prove or disprove that...)
I'm sure both extremes will jump to the rallying cry of "2 more weeks..." So yes of course I'm wrong, I only worked on analysing early 'data' and pulling apart the models so what do I know.
If that's not obvious to you pray you're not over of them...
But in seriousness it's management failure to build up debt like that.
Either self management, middle management or out of touch management. There's a reason that good managers are needed. And unfortunately most management is dealing with people and/or real-world, not a fixed in stone RFC or list of vendor requirements from legal.
They're all awful. The ICL model used to "inform" the UK lockdowns had (probably still has) a serious race condition such that when running multi-threaded that meant all of the timelines had errors of +/-1week... (It's a miracle the code didn't crash)
After this was pointed out pandemic "planning" in the UK simply went from per-week to monthly plannings following the same broken model...
It still turned out to be crazily wrong and over predicted every, single, metric, by orders of magnitude that it was tasked with simulating.
Not too mention it couldn't load configs correctly. Work correctly on the national academic supercomputer. Or gracefully present any results/findings.
This was signed off _blindly_ by the cluster admins, academics, policy advisors and international "experts". And there was significant push back for over a week once this had been demonstrated that there must be a problem with the test methodology (simply running and *checking* the output multiple times). Ask me how I know there wasn't.
The whole field of pandemic modelling I'm sure has come on leaps and bounds in recent years, but it's a shocking sad truth most/all UG computing students with a 1st could have done a better job than these experts at the top of their field.
Last time I sat down with one of the groups modelling national food availability their model _needed_ a scratch fs capable of dealing with >1M 4kB files per folder.
When asked why not to use a db they replied databases don't work well with objects larger than 1kB in size and this would introduce network latencies into their code.
Needless to say I walked away from that glad that I couldn't help.
Refuses to learn tool so tool is broken... There is no problem with python for this. If you hate boiler plate job the club, get llms to generate it for you and move on to doing real work (or get involved in improving the language or libraries directly)
On the other hand it's literally never been easier. Seriously, don't so much spend the time learning a discipline as learning to learn with any of the free online LLM tools for any subject and if you've actually got the gumption you'll go far. The 2nd qualification in life is often the toughest but the 3rd and 4th are often the easiest.
Although sociology is perfectly quantifiable and measurable. Even though arguably the underlying relationships between the measurements are extremely difficult to extract.
A better example is pure philosophy and maths rather than sociology to particle theory. But then again, nobody ever accused QFT of being too simple, so maybe I'm arguing against my own point there.
reply