# kaal:claim:7456999-017

**Claim.** Inter-annotator agreement rates are compatible with an incentive account, but ambiguity, plural values, rater error, underspecified instructions, heterogeneity, and legitimate preference diversity can produce the same rates.

**Type.** failure  **Support.** argued

**Holds when.**

- causal interpretation of the cited RLHF agreement rates

**Source quote.**

> The Ouyang et al. (2022) and Bai et al. (2022) agreement rates are compatible with the absence of material consequence for annotators, but they do not identify it as the cause. Ambiguity, plural values, rater error, underspecified instructions, distributional heterogeneity, and legitimate preference diversity can produce the same rates.

**From.** Wulf A. Kaal, *Reinforcement Learning from Reputation Feedback* (2026), II.A Pairwise Disagreement and Its Limits, page 7

**Cite as.** Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026). SSRN: https://ssrn.com/abstract=7456999

**Verify.** sha256 of source PDF `01016fbbcc25cad205cebd59ea686d8dfee8ae9b632095d86ba6c9a900456a4b` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202026%20-%20Reinforcement%20Learning%20from%20Reputation%20Feedback.pdf

**Topics.** ai-and-agents, research-methods, empirical-evidence

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