Transit network design depends not only on the optimization algorithm but also on who shows up to the public hearing. Current practice often collects one-directional comments from self-selected attendees, leaving participant mix as an uncontrolled source of outcome variation. We present AGORA, a framework that holds the network, demand, and solver fixed while systematically varying meeting composition through stakeholder agents, structured deliberation, and governance gates. Across two standard benchmark networks at different scales, we find that (i) aggregate outcomes vary little across compositions, but on tail risk and fairness disparity, representative sampling still tends to outperform skewed compositions; (ii) without deliberation, composition produces no variation at all, showing that deliberation is the mechanism through which who attends affects outcomes; and (iii) governance gates compress cross-profile variance without shifting the average outcome on Mandl, but low acceptance on Mumford0 shows thresholds require instance-specific calibration. These findings reframe participation bias from an uncontrollable input to a process-design problem: even without guaranteed representative attendance, well-structured deliberation and governance criteria can substantially reduce how much outcomes depend on who is in the room.

翻译：摘要：公交网络设计不仅依赖于优化算法，还取决于出席公听会的人员构成。当前实践中常收集自选参会者的单向评论，导致参与者组合成为结果变化的不可控源。我们提出AGORA框架，在固定网络、需求与求解器的同时，通过利益相关者智能体、结构化审议及治理门系统性地改变会议组成。针对不同规模的两个标准基准网络研究发现：(i) 总体结果随组成变化不大，但在尾部风险与公平性差异方面，代表性抽样仍优于偏斜组合；(ii) 无审议时，组成不产生任何变化，表明审议是参会人员影响结果的传导机制；(iii) 治理门在曼德尔网络中压缩跨剖面方差而不改变平均结果，但马姆福德标准中低接受率表明阈值需依实例校准。这些发现将参与偏差从不可控输入重构为流程设计问题：即便无法保证代表性出席，结构化审议与治理标准也能显著降低结果对参会人员构成的依赖程度。