kaal:claim:7261018-016
The present program's contribution is therefore not another benchmark but a treatment: a reputation-and-incentive layer imposed on a conventional, heterogeneous, ground-truthed task population, with the layer's presence or absence as the experimental variable.
Source quote, verbatim
The present program's contribution is therefore not another benchmark but a treatment: a reputation-and-incentive layer imposed on a conventional, heterogeneous, ground-truthed task population, with the layer's presence or absence as the experimental variable.
From
Wulf A. Kaal, Empirical Evaluation of the Agentic Reputation Substrate: Deliberation, the Composition of Error, and the Registered Measurement of Agency Costs in a Controlled Multi-Model Cohort (2026), II.A. The Multi-Agent LLM Empirical Literature, p. 9
https://ssrn.com/abstract=7261018 · source PDF
Cite as
Wulf A. Kaal, Empirical Evaluation of the Agentic Reputation Substrate: Deliberation, the Composition of Error, and the Registered Measurement of Agency Costs in a Controlled Multi-Model Cohort (2026). SSRN: https://ssrn.com/abstract=7261018
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designsupport: arguedai-and-agentsresearch-methodsrisk-and-incentives
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