RE: A Radically Updated Steem Whitepaper
Consider other alternatives to full linear in order to mollify new users and users who are not well-versed on how to build their social media presence/following.
Why don't you be more specific? Do you mean increasing the slope of the reward and curation curves?
It could be interesting trying to improve behavior by allowing these curves to pass an array of float couples that represents a polynomial function. For example if you pass [['1', '1']] it's like the current flat reward curve. [['1', '-1']] for square root curation curve. [['0.5', '2'], ['-1', '1']] for f(x) = x²/2 - x and so on. Maybe in that case just doing a % of quadratic + a % of linear.
Would love Steem to be able to offer those choices, but as I have literally told you before, IME it hasn't been found to be safely implementable. However, you're of course free to code it up and propose it to the Witnesses
Maybe you can be more specific as well?
It's one thing to just ignore what I typed in my original comment. It's another thing to go off about "float couples" and "polynomial functions" instead of actually answering my initial questions honestly. You know...the ones about abuse mitigation that had previously existed but now does not.
If you willingly choose to be ignorant about what's been happening since the last hard fork(s), then just refrain from engaging in discussions about it. Send me one of your other team members to honestly talk about it. Drowning the discussion with posturing, deflections, and distractions gets us nowhere.
He is not ignorant. They know what they’re doing.
He is not ignorant. They know what they are doing.
Why not use an extended error function curve (A Half-Gaussian) for rewards, this would allow newer users to be restricted in their voting strength, with moderate users getting more of a vote (those who have published good content and have made enough in order to have a vote), while still keeping the higher-steem users having more of the vote, this would seem like a much better 'In the middle' approach between quadratic and linear reward system.