Netflix used to do that. You used to be able to rate programs between 1-5 stars and see the average rating. I believe it also recommended other programs to watch based on what you rated highly.

They did away with that system and replaced it with their custom recommendation engine. I believe, without any evidence, they did this to make bad shows look better. They once hosted a documentary about sex workers (can't recall the name, sorry) that had an average rating of around 2 out of 5 stars, and after the recommendation system change, it turned into a "75% match" on my account.

A movie may have an average rating 2/5 but still be a 75% match for you personally, there's no discrepancy here.

That sounds like functionality tunnel vision, to me. Matching users to movies isn’t an abstract metadata networking exercise— the larger goal is recommending things users enjoy so they keep watching. I’m far less likely to suffer a bad movie if it closely aligns with my interests. Poor representations of my passions and crafts frustrate the hell out of me.

Why don’t they want to collect accurate user ratings? Also, they know whether or not you finish something, how many episodes you binge, etc. There are many rating-independent signals.

can you elaborate on this? can't they collect ratings for internal use and not surface them, if that's the issue?

they should be able to tune the recommender so that it doesn't completely forget about lower-rated content the way you're saying