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yogsoth-aiyogsoth-ai/convergence/skills/disagreement-cartography/SKILL.md

disagreement-cartography

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

Map the structure of disagreement across perspectives using Policy Delphi, Argument Delphi, or SAST methods.

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  1. Distinctive:

    Ensure each cluster has its strongest arguments represented

    line 51

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SKILL.md

Disagreement Cartography

Purpose: Rather than forcing convergence, map the topology of disagreement — identify clusters of opinion, the arguments supporting each cluster, and the fault lines between them. Useful for wicked problems where premature consensus would be harmful.

When to use:

  • Wicked problems with legitimate value conflicts
  • Policy questions where understanding disagreement matters more than resolving it
  • Situations where forced consensus would mask important minority views
  • Interdisciplinary disputes with incommensurable frameworks

Budget

ParameterConstraint
Rounds1–2 (mapping, not converging)
Perspectives≥4 independent
Cluster minimum≥2 distinct clusters to be useful

State Ledger

KeyTypeDescription
questionstringThe focal question or issue
perspectivesarrayList of perspective descriptions
judgmentsarrayRaw collected judgments
clustersarrayIdentified opinion clusters
argumentsarrayExtracted arguments per cluster
disagreement_mapobjectFinal visualization structure

Available Tactics

  • disagreement-mapping — Core flow: collect → cluster → extract arguments → visualize

Available SOPs

  • judgment-collection
  • cluster-analysis
  • argument-extraction
  • disagreement-visualization

Execution Guidance

  1. Frame the question to elicit diverse positions (not just ratings)
  2. Run disagreement-mapping tactic
  3. Ensure each cluster has its strongest arguments represented
  4. Produce disagreement map showing fault lines and bridging possibilities

Output Format

clusters:
  - id: <cluster_id>
    position: <summary>
    size: <number of perspectives>
    core_arguments: [...]
fault_lines:
  - between: [cluster_a, cluster_b]
    nature: <empirical/value/definitional>
bridging_possibilities: [...]

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