Debate Reform: Organizing Truth-Seeking Conversations

Today's public debates are disorganized, repetitive, and prone to manipulation. This section outlines how we can structurally reform debate systems to promote clarity, evidence-based reasoning, and collaborative truth-seeking.

The five essays below make one argument in sequence: the platforms that host our debates rank by engagement, engagement rewards manipulation, and the fix is not better moderation but different infrastructure, where every claim links to its evidence, ranking is computed from evidence contact, and a retracted source automatically weakens every conclusion built on it.

The Series

1. Current Debate Systems Are Designed to Manipulate, Not Inform
   The diagnosis. Google ranks by links (PageRank counts endorsements, not evidence), Facebook by outrage, Twitter by virality; none rank by whether a claim is true. Why the problem is structural, and what building the alternative requires, layer by layer.
2. Linking Evidence to Conclusions Would Automatically Update Truth
   The kill switch for zombie arguments. Link every argument to its evidence, and a retraction cascades: the Wakefield fraud would have collapsed every conclusion resting on it in weeks, not decades. Includes the full mechanism: the evidence ledger, the T0 retraction tier, and the audit lock that keeps anyone from typing in a score by hand.
3. Grouping Similar Arguments and Detecting Fallacies Would End Repetitive Debates
   The end of Groundhog Day. The same debate runs in a thousand places and learns nothing. One Page Per Topic consolidates it; structured fallacy claims (scored arguments, not tribal accusations) keep it honest.
4. Evidence Tiers and Objective Criteria Would Make Quality Visible
   Quality made measurable. Peer-reviewed studies and blog posts are not the same kind of thing, and the tier system says so explicitly, so weak arguments can no longer hide behind volume.
5. Wikipedia, Google, and Stack Overflow Already Proved This Model Works
   The precedent. Every component here already works at scale somewhere: consolidation (Wikipedia), link analysis (Google), earned reputation (Stack Overflow). The ISE integrates proven parts rather than inventing new ones.

The Mechanism Behind the Series

These essays describe behaviors that have precise definitions. The ISE scoring engine defines the evidence-linking layer, the propagation cascade, and the Evidence Grounding Score that ranks beliefs by their contact with tiered evidence rather than by engagement, a schema that contains no clicks, shares, or dwell-time columns at all. The methodology lives on this wiki: ReasonRank for scoring arguments by their support structure, Evidence Scores and Linkage Scores for the two dimensions every source is judged on, and the Belief Analysis Template for building a page that puts it all to work.

Want to contribute? Each essay links to dedicated pages where you can explore detailed arguments, add beliefs, and help refine the structure of collaborative debate. Developers: the GitHub repository has scoped issues a stranger can pick up. Everyone else: reach out on X (@myclob) or start with One Page Per Topic.