If categorical variable has some hierarchy, should I just label them or split into dummy variables (One-Hot encode)? I have a column which has 5 unique categories. There's a hierarchy between these categories (Best > good > OK/Not Sure > Bad > Worst)

In this case, should I label them based on hierarchy like:

Best: 4

good: 3

OK/Not Sure: 2

Bad: 1

Worst: 0


Or should I perform one-hot encoding/Dummy encoding? What's the intuition behind how the model perceives the two things?

Note: I should also mention that this is for predictive modeling using Logistic Regression.
One hot encoding should be performed between independent values like flowers type etc.
Values that you have mentioned are relative rank where bad is better than worst and so on.
So it should not be one hot encoding except converting it into numerical values.