Wait Baysians are neoliberals now? I thought Baysians were infamously right wing?
Frequentist hypothesis testing falls somewhere in the middle, and as long as it's not over-interpreted is fine as it is, with the advantage being it's easy to do. Though the downside is that it's not easy to interpret.
The downside of Bayesian statistics, in my experience, is that it's really hard to teach it to less-than-very-bright people, even in the academy. I mean, those who don't even understand what "falsifying a null-hypothesis" means (and doesn't mean) will have a very hard time doing Bayesian analysis properly.
In a more advanced setting, though, Bayesian approaches provide a much better tool for comparing a set of alternative hypotheses. But it requires that users understand the math, and are not just following some script, and also that those involved are willing to provide their priors before evaluating the data.
Is this an actual stereotype that Bayesians are right wing? It doesn't seem at all political to me, but I guess I've never met someone who self identified as a Bayesian either.
[0] https://open.substack.com/pub/argmin/p/is-the-reproducibilit...
I'm more of a Bayesian in interpretation of statistics and epistemology, and I'm pretty far left. N=1 of course.
Neoliberalism refers to a social order and doesn't have much to do with probability and statistics.
This can be contrasted to the preceding systems that had more regulation of markets and planned resource production and allocation. Roughly Keynesian or social democratic economics, with their associated view of social organization.
There has been a concurrent shift towards bibliometric assesment of researchers and institutions, to a large part to have metrics for the competition.
In general this is largely an application of the (neoliberal) New Public Management [2] model applied to academia and science.
Before this shift funding was based mostly on budgets akin to how e.g. schools or (public) healthcare and police are funded. Academics were mostly just hired to a (permanent contract) job when there was an opening. Anecdotally, my supervising professor was tenured almost straight after he got his PhD in the 1970s. And he didn't really have to apply for competitive funding until 2000's or so. And this was more or less the norm back then.
In angloamerican countries the neoliberal turn started already in the 1970s. Although there was also a contemporary explosion in funding of science much due to the role of scientific and technological progress in the Cold War.
The degree inflation likely plays a role too, and in research this shows as more PhD students who have to churn out papers to get their degrees (which is beneficial to the universities as they are assessed on how many affiliated publications they output). There's of course plenty of quality PhD-level research but it's also quite obvious that the quality is also affected by the students still essentially learning the ropes.
Academia's, science's and higher education's societial position and "clout" was quite different and smaller in the era of classical liberalism (roughly until WW1), and public funding had a lot smaller role.
It's of course totally arguable that competition leads to more efficiency. However, the academic world doesn't really have a natural market and establishing comparative value of different lines of research, academic institutions or individual researchers is very difficult. And due to this the resource allocation is done largely based on quantity of scholarly outputs (papers and PhD degrees) and salesmanship. These of course are very easy to play, and those who don't engage in the play tend to not survive. And it adds huge overheads.
[1] https://link.springer.com/article/10.1007/s10734-008-9169-6 [2] https://en.m.wikipedia.org/wiki/New_Public_Management
Well, according to the statistics...