This topic is about canonizer.com canonizers. 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 canonizers (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, canonizers (algorithms) will then count the value of your support appropriately.

We welcome all feedback about what canonizers (algorithms) are most preferred, what the specific algorithms should be, and proposals for new canonizers (algorithms) to be implemented.

Please cast your vote on these canonizers (algorithms) showing which ones you think are most credible or most valuable. Or propose new canonizers (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 canonizers that might help people to determine quantitative values for respect and legitimacy.

Multi Support Scoring

For the most part, one of the goals of the canonizer is to find out the single most valuable POV choice of people. Allowing people to support more than one camp statement per topic and granting them a full vote on all non first choice camps, would distort the fidelity of such a system. It would reward people, giving them more influence or votes, simply by voting for more than one camp. Yet there are still cases where you want to allow an ordered list of multiple votes per topic, especially on topics like, What are your current favorite movies

With this in mind, canonizers use a standard multi-support scoring system that rewards a person with 100% of their canonized value if they only support one camp on any particular topic. If they support more than one camp, 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 than and so on. With this, voting for more than one camp can never achieve as much total voting influence per topic as simply voting for one camp.

For various reasons people may want to score multi support differently, such as only count votes of people that support only one camp, and so on. If there is demand for such, we may implement such additional multi support scoring methods that various canonizes can be configured to use. But for now, all canonizers use this "Standard" scoring system for multiple support.

Source code for all algorithms can be found on GitHub .