Doesn’t seem so. Sometimes the shown counter is higher than the number of ‘votes’. Maybe by ‘votes’ it’s showing the total number of users who voted (with varying voting weights)?
Yep, it’s showing the total number of users who voted (or like, the number of upvotes and downvotes, though my sense is we are using those words slightly differently). I agree that there is no way to see things broken down by points, though my sense is people can usually guess pretty well the distribution of upvotes and downvotes.
Well when it says ‘This comment has x overall karma (x-2 Vote)’ I’m fairly certain x-2 is not revealing much about the number of upvotes and downvotes, since I can’t guess how many were 3 weighted upvotes, 2 weighted upvotes, 1 weighted upvotes, 3 weighted downvotes, etc...
Hmm, I might be typical-minding here, but I can usually tell pretty quickly about the distribution, just from priors and combinatorics. Here are some examples:
Score: 22, votes: 3 ⇒ 1 small upvote, 2 strong upvotes from high karma users
Score: 3, votes 22 ⇒ A bit unclear, but probably like 1-3 strong upvotes, 1-3 strong downvotes and then a mixture of small upvotes and downvotes for the rest
Score −3, votes 4 ⇒ Either 3 small downvotes, or 2 small upvotes and 1 strong downvote from a high karma user
There is definitely ambiguity remaining here (which is somewhat intentional in the design for anonymization reasons), but seeing the total number of votes usually really reduces it down to 1 or 2 hypotheses for me on what is happening.
Your first two examples are less ambiguous since the differential is large, but when the differential is small, like my example, or your third example, how do you guess between:
Doesn’t seem so. Sometimes the shown counter is higher than the number of ‘votes’. Maybe by ‘votes’ it’s showing the total number of users who voted (with varying voting weights)?
Yep, it’s showing the total number of users who voted (or like, the number of upvotes and downvotes, though my sense is we are using those words slightly differently). I agree that there is no way to see things broken down by points, though my sense is people can usually guess pretty well the distribution of upvotes and downvotes.
Well when it says ‘This comment has x overall karma (x-2 Vote)’ I’m fairly certain x-2 is not revealing much about the number of upvotes and downvotes, since I can’t guess how many were 3 weighted upvotes, 2 weighted upvotes, 1 weighted upvotes, 3 weighted downvotes, etc...
Hmm, I might be typical-minding here, but I can usually tell pretty quickly about the distribution, just from priors and combinatorics. Here are some examples:
Score: 22, votes: 3 ⇒ 1 small upvote, 2 strong upvotes from high karma users
Score: 3, votes 22 ⇒ A bit unclear, but probably like 1-3 strong upvotes, 1-3 strong downvotes and then a mixture of small upvotes and downvotes for the rest
Score −3, votes 4 ⇒ Either 3 small downvotes, or 2 small upvotes and 1 strong downvote from a high karma user
There is definitely ambiguity remaining here (which is somewhat intentional in the design for anonymization reasons), but seeing the total number of votes usually really reduces it down to 1 or 2 hypotheses for me on what is happening.
Your first two examples are less ambiguous since the differential is large, but when the differential is small, like my example, or your third example, how do you guess between:
1 strong upvoter, several weak downvoters
1 strong downvoter, several weak upvoters
several strong upvoters and downvoters
etc.?