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This architecture improves behavioral control in large language models, suggesting effective governance strategies.
We present PHL (Ping, Hook, Lever), a three-layer architecture for governance-oriented behavioral control of large language models. Ping injects a structured essence packet at session start; Hook detects governance headers and switches operational mode automatically; Lever evaluates output quality using the ZYXTS scoring framework. Empirical evaluation across 255 sessions demonstrates a mean quality gain of Δtotal = +3.8 (ZYXTS: 0.6 → 4.4). This work is part of the MoCKA (Model of Cybernetic Knowledge Architecture) longitudinal publication series.
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masahito kimura (2026) studied this question.
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