事件终局性的两种模型：Polymarket 与 Kalshi 上的功能对齐、可争议性与经验可比性
Two Models of Event Finality: Functional Alignment, Contestability, and Empirical Comparability on Polymarket and Kalshi
AI总结：
本文提出机制感知的比较证书，以功能角色对齐 Polymarket 与 Kalshi 的事件终局性端点，并给出大规模经验数据，指出跨场所数值比较需待后续论文提供可判定性时钟与语义注册表。
AI中文摘要：
事件合约通过不同的制度路径达到经济终局性。Polymarket 区分了预言机裁决、适配器消费、条件代币支付记录、技术可赎回性和可选持有者赎回。Kalshi 区分了场所裁定、公开终局化、生命周期消息和精确的 REST 结算字段。已解决、已结算和已终局化本身并不定义可比较的端点。我们定义了一种机制感知的比较证书，使用功能角色而非通用标签。只有当支付语义、端点功能、日历支持、删失、观察等级和依赖单位联合对齐时，跨场所的标量持续时间才是可允许的。我们区分了精确配对、区间限定配对和标准化非配对估计量。Polymarket 证据包含 108,638 个精确关联条件、99,283 条协议支付记录、92,158 次任意金额的观察赎回和 91,817 次观察到的正支付赎回。Kalshi 证据包含 152,694 个在注册边界处重建为有风险的普通市场和 7,611,594 个精确 MVE 市场对象。精确公开端点覆盖 71,657 个普通市场和 7,357,576 个 MVE 对象。精确确定到端点的配对总计普通市场 70,979 对和 MVE 126,806 对。这些是 Kalshi 原生的终局性结果，而非 Polymarket-Kalshi 估计。当精确生命周期路径稀疏时，REST 端点完整性可能很高，而传输间隙可以保留两个精确时钟，同时阻止对中间修订的主张。当前 MVE 计时器字段不识别历史版本一致的计时器规则，公开终局化也不识别成员现金。跨场所数值比较仍然受阻，直到论文 7.3 提供盲法第一/稳定可判定性时钟，并且语义/日历注册表建立真正可比较的事件和端点。
英文摘要：
Event contracts reach economic finality through different institutional paths. Polymarket distinguishes oracle adjudication, adapter consumption, Conditional Tokens payout recording, technical redeemability, and optional holder redemption. Kalshi distinguishes venue determination, public finalization, lifecycle messages, and exact REST settlement fields. Resolved, settled, and finalized do not themselves define comparable endpoints. We define a mechanism-aware comparison certificate using functional roles rather than common labels. A scalar cross-venue duration is admissible only when payoff semantics, endpoint functions, calendar support, censoring, observation grades, and dependence units are jointly aligned. We separate exact paired, interval-qualified paired, and standardized unpaired estimands. Polymarket evidence contains 108,638 exact-linked conditions, 99,283 protocol payout records, 92,158 observed redemptions of any amount, and 91,817 observed positive-payout redemptions. Kalshi evidence contains 152,694 ordinary markets reconstructed as at risk at the enrollment boundary and 7,611,594 exact MVE market objects. Exact public endpoints cover 71,657 ordinary markets and 7,357,576 MVE objects. Exact determination-to-endpoint pairs total 70,979 for ordinary markets and 126,806 for MVE. These are Kalshi-native finality results, not Polymarket-Kalshi estimates. REST endpoint completeness can be high when exact lifecycle paths are sparse, and transport gaps can preserve two exact clocks while preventing claims about intermediate revisions. Current MVE timer fields do not identify historical version-consistent timer rules, and public finalization does not identify member cash. Cross-venue numerical comparison remains blocked until Paper 7.3 supplies blind first/stable decidability clocks and a semantic/calendar registry establishes genuinely comparable events and endpoints.
