Canonizer Algorithms

This topic is about Canonizer.com Canonizer Algorithms. These are algorithms used to prioritize or filter statements. The canonizer (algorithm) currently being used can be selected by people in the Canonizer section on the side bar. Changing the canonizer algorithm can reorder or filter the list of POV statements according to the person's desires. If you wish your camp to be properly credited by canonizer algorithms, you should go to the statement for that canonizer algorithm to find out which topics and statements are used to determine votes. Then you can join the appropriate camps. Once this is completed, canonizer algorithms will then count the value of your support appropriately. We welcome all feedback about what canonizer algorithms are most preferred, what the specific algorithms should be, and proposals for new canonizer algorithms to be implemented.

Please cast your vote on these canonizer algorithms showing which ones you think are most credible or most valuable. Or propose new canonizer algorithms to be added. The main goal of a canonizer is so people can specify a set of attributes of people they trust. We want to provide a way for people to filter out support of people they don't trust, or with less than reputable histories. In this way it allows people to survey people on moral and value issues, giving more weight to people that have the attributes and values they are interested in or respect and trust. The goal is to provide a way for people to obtain reliable moral or value advice from large groups of people they chose to trust.
We would like to push in a direction of making any and all possible data available to canonizer algorithms that might help people to determine quantitative values for respect and legitimacy.

Multi Support Scoring

A score of one is given for users who support just one camp in a given topic, supporting more than one camp will cause the user's support to be diluted but will always add up to one. Their first choice is reduced to 50%, and the second vote is reduced by half of that, or to 25%, and to 12.5% after that and so on. Optionally, when using the Refine tools no dilution will be considered and each camp a supporter belongs to will get one whole vote by checking the “100% of canonized score on all supported camps” . We know this is a bit confusing at first, to help understand dilution the table below shows what the score will be given its order out of the total number camps joined in a given topic. If(SupportOrder = 1, 0.5 + 0.5^TotalCamps, 0.5 * 0.5^{SupportOrder - 1})

Total Number of Camps / Support Order	1	2	3	4
1	1
2	0.75	0.25
3	0.625	0.25	0.125
4	0.5625	0.25	0.125	0.0625

Source code for all algorithms can be found on GitHub.