<a href="/en/Connection-Oriented%20Cluster%20Matching">Connection-Oriented Cluster Matching</a>
<ul>
<li>QF voting behavior is a high-dimensional vector</li>
<li>Cluster it and use the variation as a coefficient of voting power.</li>
</ul>
<a href="/en/Polis">Polis</a>
<ul>
<li>Voting behavior is a high-dimensional vector</li>
<li>PCA it, cluster it, and multiply the support in each cluster by the consensus index.</li>
</ul>
<a href="/en/Community%20Notes">Community Notes</a>
<ul>
<li>The evaluation on the note is a high-dimensional vector</li>
<li>Decompose it into attribute information and bias terms in the note/voter 1 dimension<ul>
<li>This one dimension roughly corresponds to the political left and right</li>
</ul>
</li>
<li>High bias terms in the notes mean that they are &quot;supported by both the political left and right&quot;</li>
</ul>
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A mechanism for evaluating support from diverse entities