theseus: extract from 2025-11-00-operationalizing-pluralistic-values-llm-alignment.md

- Source: inbox/archive/2025-11-00-operationalizing-pluralistic-values-llm-alignment.md
- Domain: ai-alignment
- Extracted by: headless extraction cron (worker 5)

Pentagon-Agent: Theseus <HEADLESS>

inbox/archive/2025-11-00-operationalizing-pluralistic-values-llm-alignment.md

@@ -7,9 +7,14 @@ date: 2025-11-01
 domain: ai-alignment
 secondary_domains: []
 format: paper
-status: unprocessed
+status: null-result
 priority: high
 tags: [pluralistic-alignment, demographic-composition, empirical, safety-inclusivity, real-human-feedback]
+processed_by: theseus
+processed_date: 2026-03-11
+enrichments_applied: ["community-centred norm elicitation surfaces alignment targets materially different from developer-specified rules.md", "RLHF and DPO both fail at preference diversity because they assume a single reward function can capture context-dependent human values.md", "some disagreements are permanently irreducible because they stem from genuine value differences not information gaps and systems must map rather than eliminate them.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "First large-scale empirical study quantifying the effect of demographic composition on alignment outcomes. Single high-confidence claim extracted with three enrichments to existing pluralistic alignment claims. Effect sizes (3-5 pp) are substantial and cannot be dismissed as noise with N=1,095."
 ---
 
 ## Content
@@ -37,3 +42,11 @@ Demonstrates that "whose feedback" matters as much as "how much feedback" for al
 PRIMARY CONNECTION: community-centred norm elicitation surfaces alignment targets materially different from developer-specified rules
 WHY ARCHIVED: Empirical evidence that "whose preferences" is a quantitatively important question, not just a fairness concern
 EXTRACTION HINT: Focus on the magnitude of demographic composition effects and what this means for single-population alignment training
+
+
+## Key Facts
+- Study included 27,375 ratings from 1,095 participants
+- Liberal feedback improved models 5.0 percentage points vs Conservative baseline
+- White feedback improved models 4.7 percentage points vs Black baseline
+- Female feedback improved models 3.4 percentage points vs Male baseline
+- Effects measured on emotional awareness and toxicity dimensions