Yes, in 2D classification, the “remove duplicates” parameter and the associated “minimum separation distance” parameter below it will accomplish the same thing as running a standalone remove duplicate particles job.
In most cases, you shouldn’t have to worry about duplicate particles except in the cases you describe (combining picking jobs, crowded micrographs, etc), but you should also be aware that performing a symmetry expansion on your particles will also generate “duplicates” that need to be removed before running a global refinement (heterogeneous, homogeneous, non-uniform, etc). You can find some more information in this thread: