I really like how Steemhunt implemented it's own curation system based on how much someone interacts with their platform... but it still doesn't quite work properly... Influencers get a much larger scare (x3 or x5) in order help cool but unvoted hunts up the ladder, but most influencers use their votes on their friends first...
When my coding skills are up to it, I'm keen to create niche-specific Steem front ends that curates based on quality. I'm sure it can be done, but I think it takes a lot of moderation to lead the group.
I think the moderation can be decentralized and incentivized, so that people like you and me will just do it automatically and our efforts can be combined to create an emergent network effect.
Yes... but people will always try and maximise... so I guess the trick is to find the behaviour that you like (ie, people upvoting the best content) and to figure out a way that that behaviour provides the maximum rewards.
In the case of Steemhunt, people were voting hardcore in the first minute because if you were one of the first to recognise a hunt that became popular you got a better score... then the algorithm changed so that unrecognized hunts gave a better score, so people looked for those... in neither case were the 'best' hunts found... and that's the tricky part.
Maybe some people will always maximise and there's nothing you can do about it, and maybe if it's good enough for most people than you'll get the desired effect. It's just tricky when most games, etc teach us to maximise above our own natural instincts.
I think the trick is to find accounts that don't maximize and give them the higher reputation scores.