C003 — Claim Definition¶


Research	R0057 — RLHF Yes-Men Claims v3
Run	2026-04-01
Claim	C003

Claim as Received¶

The formal analysis attributes sycophancy amplification to systematic bias in preference data, not algorithmic failures.

Claim as Clarified¶

The formal analysis attributes sycophancy amplification to systematic bias in preference data, not algorithmic failures.

BLUF¶

Confirmed. Shapira et al. explicitly identify mixed-pair bias in annotator preferences as the root cause, showing the RLHF algorithm correctly optimizes a biased objective rather than failing algorithmically.

Scope¶

Domain: AI sycophancy research
Timeframe: Current (2024-2026)
Testability: Verifiable against published research and public records

Assessment Summary¶

Probability: Very likely (80-95%)

Confidence: High

Hypothesis outcome: H1 is supported based on available evidence.

[Full assessment in assessment.md.]

Status¶

Field	Value
Date created	2026-04-01
Date completed	2026-04-01
Researcher profile	Phillip Moore
Prompt version	Unified Research Methodology v1
Revisit by	2027-04-01
Revisit trigger	If the distinction between data bias and algorithmic failure is shown to be false