Is there an appropriate use of adjusting class weights for a balanced dataset?
Class Weight can be important even for balanced data if, for example, some class is more significant than others, so loss wrt this class should count more.
One can even think of class weights as unique extra hyper-parameters with their own effect on the outcome (either positive or negative) and treat them as such without interpretation.
Related: How does class_weight work in Decision Tree?