The likelihood function, $L(\theta|x) = f(x|\theta)$, is sometimes mistaken to be a pdf. I have always thought that showing an example where $ \int_{-\infty}^{\infty} L(\theta|x) d \theta = 1 $ does not hold would be enough to conclude that the likelihood function is not a pdf, and I have not given it much thought beyond that.
Recently, I read some posts 1) What is the difference between "likelihood" and "probability"?, 2) What is the reason that a likelihood function is not a pdf?, 3) How to rigorously define the likelihood?, and in the comments to an answer of 2) it is stated that
"The $\theta$ has not even a sense in general because there's not even a $\sigma$-field in the parameter space!"
Whereas I have no reason to doubt this, it is not obvious to me why it is true, probably because my familiarity with $\sigma$-algebras is limited to the one page in Casella & Berger's Statistical Inference, and the post Why do we need sigma-algebras to define probability spaces?.
Since the comment is more than 10 years old, I gathered it would make sense to post it as a question. There are more recent discussions in the comments of Intuition for why likelihood function sometimes *is* a PDF, not mentioning $\sigma$-algebra specifically, so perhaps there exists some other statement regarding the senselessness of $d\theta$ without involving $\sigma$-algebra, but I have a feeling they might be connected.