Academic publishing increasingly requires authors to disclose AI assistance, yet imposes reputational costs for doing so--especially when such assistance is substantial. This article analyzes that structural contradiction, showing how incentives discourage transparency in precisely the work where it matters most. Traditional venues cannot resolve this tension through policy tweaks alone, as the underlying prestige economy rewards opacity. To address this, the article proposes an alternative publishing infrastructure: a venue outside prestige systems that enforces mandatory disclosure, enables reproduction-based review, and supports ecological validity through detailed documentation. As a demonstration of this approach, the article itself is presented as an example of AI-assisted scholarship under reasonably detailed disclosure, with representative prompt logs and modification records included. Rather than taking a position for or against AI-assisted scholarship, the article outlines conditions under which such work can be evaluated on its own terms: through transparent documentation, verification-oriented review, and participation by methodologically committed scholars. While focused on AI, the framework speaks to broader questions about how academic systems handle methodological innovation.

翻译：学术出版日益要求作者披露AI辅助情况，但披露行为本身却会带来声誉代价——尤其是在AI辅助程度较高的情况下。本文分析了这一结构性矛盾，揭示了激励机制如何在最需要透明度的研究领域反而抑制透明度。传统出版平台无法仅通过政策调整解决这一矛盾，因为其底层的声望经济体系实质上奖励不透明行为。为此，本文提出一种替代性出版基础设施：在声望体系之外建立强制披露、支持可复现性评审、并通过详细记录保障生态效度的出版平台。作为该方法的具体示范，本文自身即作为AI辅助学术研究的案例呈现，附有代表性提示记录与修改日志，并遵循合理详细的披露标准。本文不采取支持或反对AI辅助学术的立场，而是通过透明记录、验证导向的评审机制以及方法论自觉的学者参与，勾勒出此类研究能够获得本真性评价的实践条件。虽然聚焦于AI领域，该框架对学术体系如何处理方法论创新这一更广泛议题具有启示意义。