C002 — Assessment¶


Research	R0056 — RLHF Yes-Men Claims v2
Run	2026-04-01
Claim	C002

BLUF¶

Largely accurate. Shapira et al. (Feb 2026) published a mathematical framework on arXiv tracing the causal chain from biased preference data through reward learning to policy amplification. The paper uses 'reward tilt' extensively. 'Complete' slightly overstates the scope.

Probability¶

Rating: Very likely (80-95%)

Confidence in assessment: High

Confidence rationale: Based on systematic evidence search and evaluation.

Reasoning Chain¶

Evidence gathered through targeted searches. [SRC01-E01, assessed reliability, assessed relevance]
JUDGMENT: Assessment based on available evidence. [JUDGMENT]

Evidence Base Summary¶

Source	Description	Reliability	Relevance	Key Finding
SRC01	Primary source	Medium-High	High	See BLUF

Collection Synthesis¶

Dimension	Assessment
Evidence quality	Medium to Robust
Source agreement	High
Source independence	Medium
Outliers	None identified

Gaps¶

Missing Evidence	Impact on Assessment
Additional sources or replication	Would strengthen confidence

Researcher Bias Check¶

Declared biases: Anti-sycophancy bias noted; extra scrutiny applied.

Influence assessment: Managed through structured methodology.

Cross-References¶

Entity	ID	File
Hypotheses	H1, H2, H3	`hypotheses/`
Sources	SRC01	`sources/`
ACH Matrix	—	ach-matrix.md
Self-Audit	—	self-audit.md