I think you're conflating "functions used to build a hash table" with "functions used to build a dictionary ADT." A hash table doesn't have to serve the purpose of storing items in a dictionary ADT. A hash table where everything that's similar collides into the same buckets is just as useful for finding "a linked list of similar items" in O(1), as a hash table where everything gets its own unique bucket is useful for finding items in O(1).
It's true that these functions are in some sense very different to traditional hash functions, because they are designed to create "collisions" (or at least be similar) for elements that are similar. But I still think it is intuitive to use the term, maybe qualified as a "similarity hash" (I've also seen "perceptual hash" or "semantic hash"). In both cases we are describing a (potentially) large object with a short code. In normal hashes, the hash is supposed to be the same for objects that are exactly the same - in similarity hashes, that is softened to similar hashes for similar objects.