As far as I know all methods / models making assumptions about data distribution, data scale, etc. but whenever I read a paper (political sciences) the researcher(s) are violating them (some). E.g. treating ordinal data as metric or "pseudo-metric", don't care about normal distrbution. I always askmyself are they doing this for pratical reasons and are there findings valid? Or are violations not that serve in general or does it really depend on the method / model and if so, could you please give me some examples where it doesn't really matter and some where it does.
Here is a sample as suggested: Högström, J. (2013): Classification and Rating of Democracy: A Comparison. Taiwan Journal of Democracy, Volume 9, No. 2: 33-54 https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A683064&dswid=2340
The author compares three measurements of democracy. Two of them (Freedom House and Polity) are ordinal scaled. He rescales all of them to a 0-100 scale for comparison and uses a paired t-test.