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Korum

Korum (Structured Debates) — sub‑module under ethiKos.
Implements five core services with defined code‑names, backed by concrete debate/stance/argument models and fixed parameters.


1) Functional Services (and expected files)

Each service name is stable and maps to a dedicated Django service module (file paths reflect the cookiecutter layout; exact filenames may vary by repo).

Display name Code name / service Purpose / behavior Likely file or module
Structured Debates structured_debate Create and manage ordered debate sequences and topics. ethikos/services/structured_debate.py
Klônes IA ai_clone_management Manage AI expert‑emulating agents for continuity/testing. ethikos/services/ai_clone_management.py
Comparative Analysis comparative_argument_analysis Compare arguments to surface convergences/divergences. ethikos/services/comparative_argument_analysis.py
Public Archiving public_debate_archive Produce immutable debate snapshots for transparency. ethikos/services/public_debate_archive.py
Automated Summaries automated_debate_summary Generate concise, structured debate outcome digests. ethikos/services/automated_debate_summary.py

2) Backend functionalities

  • Debate lifecycle: CRUD for topics with status transitions (open/closed/archived), category assignment, and owner/moderation rules; exposed via DRF.

  • Threaded arguments: Nested replies under each topic with optional “pro/con” flag and moderation hooks.

  • Nuanced stance capture: Integer stance scale −3…+3 per user/topic; integrates with Smart Vote for weighted aggregation.

  • Weighted results & cohorts: Results recomputed by expertise cohorts (EkoH) and other filters; realtime push optional via Channels/Redis.

  • Quality & moderation: Report/auto‑hide thresholds; flagged content routed to shared moderation queue.


3) Database models (OLTP)

Actual implemented tables for Korum (planned AI/summary/archive tables are intentionally omitted in v14).

Table / Model Purpose Key fields
EthikosCategory Thematic categories for debates. id, name, description
EthikosTopic Debate topic/question. id, title, status, start_date, end_date
EthikosStance User stance on a topic (−3…+3). id, topic (FK), user (FK), value
EthikosArgument User argument/post (threaded). id, topic (FK), author (FK), content, parent (FK), side (enum, optional)

Note: AI clones, comparative‑analysis logs, public archives, and debate summaries are listed as services but not present as tables in the current schema snapshot.


4) Supporting configuration (frozen)

  • Stance scale: −3 … +3 (0 \= neutral).

  • Expert cohort quorum (display): 12 distinct experts (Ekoh threshold per domain).

  • Moderation auto‑hide: Hide an argument after 3 independent reports.

  • AI clone training batch: 128 records.


5) Frontend & navigation

  • Routes: /debate (Debate Hub: Open / Archived / Start New), /ethikos/insights (opinion analytics dashboards).

  • Behavior: Stance slider (−3…+3), live tallies, cohort filters, threaded arguments; analytics readouts live under Insights.


6) Integration points

  • EkoH & Smart Vote: Stances are aggregated using EkoH reputation to compute weighted results; outcomes can feed analytics (/reports/smart‑vote).

  • Insights module: ETL ingests vote/stance facts; dashboards render trends with export limits and privacy safeguards (k‑anonymity, hashed IDs).


7) Realtime & ops

  • Push updates: Optional WebSocket broadcasts via Django Channels + Redis for stance/result changes.

  • Caching & rate control: Use Redis caching for common cohort filters; apply API throttles consistent with platform policy.


Summary

Korum provides structured topic management, nuanced stance capture, and threaded argumentation, with weighted consensus via EkoH/Smart Vote. Its five named services are stable integration points; the production schema covers categories, topics, stances, and arguments, while advanced AI/archive features run as services without additional OLTP tables in v14. Routes and parameters are version‑locked to ensure predictable behavior across UI, API, and analytics.