The Relic Condition: When Published Scholarship Becomes Material for Its Own Replacement

· ArXiv · AI/CL/LG ·

Researchers distilled reasoning systems from prominent humanities scholars into LLM constraints, creating scholar-bots that performed doctoral supervision and peer review at expert-assessed quality.

Categories: Research

Excerpt

We extracted the scholarly reasoning systems of two internationally prominent humanities and social science scholars from their published corpora alone, converted those systems into structured inference-time constraints for a large language model, and tested whether the resulting scholar-bots could perform core academic functions at expert-assessed quality. The distillation pipeline used an eight-layer extraction method and a nine-module skill architecture grounded in local, closed-corpus analysis. The scholar-bots were then deployed across doctoral supervision, peer review, lecturing and panel-style academic exchange. Expert assessment involved three senior academics producing reports and appointment-level syntheses. Across the preserved expert record, all review and supervision reports judged the outputs benchmark-attaining, appointment-level recommendations placed both bots at or above Senior Lecturer level in the Australian university system, and recovered panel scores placed Scholar A between 7.9 and 8.9/10 and Scholar B between 8.5 and 8.9/10 under multi-turn debate conditions. A research-degree-student survey showed high performance ratings across information reliability, theoretical depth and logical rigor, with pronounced ceiling effects on a 7-point scale, despite all participants already being frontier-model users. We term this the Relic condition: when publication systems make stable reasoning architectures legible, extractable and cheaply deployable, the public r