Topic: Canonizer Algorithms

Camp: Agreement / Peer Ranking Algorithms / Mind Experts

Camp Statement History

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Statement :

Mind Expert


This topic enables peers to rank each other in this “Mind Expert” topic.

This algorithm is an important component of the Consciousness Consensus Project, in particular for building and tracking consensus around the best “Theories of Consciousness”.

Edit summary :
Submitted on :
Submitter Nick Name : Brent_Allsop
Go live Time :
Statement :

Mind Experts


The goal of this Mind Experts canonizer algorithm (selectable on the side bar) is to be a rigorous quantitative measure of scientific consensus on topics about theories of mind. An example topic being this one on the best Theories of Consciousness.

This algorithm uses the survey data in the peer ranking Mind Experts topic where experts can rank each other resulting in a quantitative measure of expertise. When the Mind Experts algorithm is selected on that topic, the camp scores for each camp indicate the votes each expert has for any camp they support on any other topic.

Since this algorithm uses the data in the Mind Experts topic, it necessarily works differently on that topic than all other topics. This is because of the recursive self referential nature of what is being done in this case.

The current draft of this algorithm uses two passes. First it does a one person one vote pass to determine who the general population thinks are the experts. Then these experts are given the values for the first pass 'votes' based on this. These first pass votes are indicated for each of the experts supporting camps on the Mind Experts topic in the support section of that camp.

The second pass is achieved by totaling up all the votes of all experts in each camp resulting in the final camp score indicated next to each camp. These camp scores indicate how much of a vote each expert gets when they support any other camp at canonizer.com when this scientific consensus algorithm is selected.

There is also currently a significant reward being added to the first pass for experts that vote for more than only themselves. In other words, if an expert supports more than themselves on this topic, their top vote has more value than if they only vote for themselves.

As always, the code is open source so any request to examine the implementation are always granted. And anyone having ideas about possible ways to improve things are always accepted and recognized. Also, similar algorithms can be created for any field of expertise, as they are needed or requested.

Edit summary : Modernize the URLs
Submitted on :
Submitter Nick Name : Brent_Allsop
Go live Time :
Statement : The goal of this Mind Experts canonizer algorithm (selectable on the side bar) is to be a rigorous quantitative measure of scientific consensus on topics about theories of mind. An example topic being this one on the best Theories of Conscoiusness.
This algorithm uses the survey data in the peer ranking Mind Experts topic where experts can rank each other resulting in a quantitative measure of expertise. When the Mind Experts algorithm is selected on that topic, the camp scores for each camp indicate the votes each expert has for any camp they support on any other topic.
Since this algorithm uses the data in the Mind Experts topic, it necessarily works differently on that topic than all other topics. This is because of the recursive self referential nature of what is being done in this case.
The current draft of this algorithm uses two passes. First it does a one person one vote pass to determine who the general population thinks are the experts. Then these experts are given the values for the first pass 'votes' based on this. These first pass votes are indicated for each of the experts supporting camps on the Mind Experts topic in the support section of that camp.
The second pass is achieved by totaling up all the votes of all experts in each camp resulting in the final camp score indicated next to each camp. These camp scores indicate how much of a vote each expert gets when they support any other camp at canonizer.com when this scientific consensus algorithm is selected.
There is also currently a significant reward being added to the first pass for experts that vote for more than only themselves. In other words, if an expert supports more than themselves on this topic, their top vote has more value than if they only vote for themselves.
As always, the code is open source so any request to examine the implementation are always granted. And anyone having ideas about possible ways to improve things are always accepted and recognized. Also, similar algorithms can be created for any field of expertise, as they are needed or requested.

Edit summary : correct spelling pas -> pass.
Submitted on :
Submitter Nick Name : Brent_Allsop
Go live Time :
Statement : The goal of this Mind Experts canonizer algorithm (selectable on the side bar) is to be a rigorous quantitative measure of scientific consensus on topics about theories of mind. An example topic being this one on the best Theories of Conscoiusness.
This algorithm uses the survey data in the peer ranking Mind Experts topic where experts can rank each other resulting in a quantitative measure of expertise. When the Mind Experts algorithm is selected on that topic, the camp scores for each camp indicate the votes each expert has for any camp they support on any other topic.
Since this algorithm uses the data in the Mind Experts topic, it necessarily works differently on that topic than all other topics. This is because of the recursive self referential nature of what is being done in this case.
The current draft of this algorithm uses two passes. First it does a one person one vote pass to determine who the general population thinks are the experts. Then these experts are given the values for the first pas 'votes' based on this. These first pass votes are indicated for each of the experts supporting camps on the Mind Experts topic in the support section of that camp.
The second pass is achieved by totaling up all the votes of all experts in each camp resulting in the final camp score indicated next to each camp. These camp scores indicate how much of a vote each expert gets when they support any other camp at canonizer.com when this scientific consensus algorithm is selected.
There is also currently a significant reward being added to the first pass for experts that vote for more than only themselves. In other words, if an expert supports more than themselves on this topic, their top vote has more value than if they only vote for themselves.
As always, the code is open source so any request to examine the implementation are always granted. And anyone having ideas about possible ways to improve things are always accepted and recognized. Also, similar algorithms can be created for any field of expertise, as they are needed or requested.

Edit summary : "canonizer algorithm" not just "canonizer"
Submitted on :
Submitter Nick Name : Brent_Allsop
Go live Time :
Statement : The goal of this Mind Experts canonizer is to be a rigorous quantitative measure of scientific consensus on topics about theories of mind. An example topic being this one on the best Theories of Conscoiusness.
This algorithm uses the survey data in the peer ranking Mind Experts topic where experts can rank each other resulting in a quantitative measure of expertise. When the Mind Experts algorithm is selected on that topic, the camp scores for each camp indicate the votes each expert has for any camp they support on any other topic.
Since this algorithm uses the data in the Mind Experts topic, it necessarily works differently on that topic than all other topics. This is because of the recursive self referential nature of what is being done in this case.
The current draft of this algorithm uses two passes. First it does a one person one vote pass to determine who the general population thinks are the experts. Then these experts are given the values for the first pas 'votes' based on this. These first pass votes are indicated for each of the experts supporting camps on the Mind Experts topic in the support section of that camp.
The second pass is achieved by totaling up all the votes of all experts in each camp resulting in the final camp score indicated next to each camp. These camp scores indicate how much of a vote each expert gets when they support any other camp at canonizer.com when this scientific consensus algorithm is selected.
There is also currently a significant reward being added to the first pass for experts that vote for more than only themselves. In other words, if an expert supports more than themselves on this topic, their top vote has more value than if they only vote for themselves.
As always, the code is open source so any request to examine the implementation are always granted. And anyone having ideas about possible ways to improve things are always accepted and recognized. Also, similar algorithms can be created for any field of expertise, as they are needed or requested.

Edit summary : First Version
Submitted on :
Submitter Nick Name : Brent_Allsop
Go live Time :