Top-tier academic conferences are failing under the strain of two irreconcilable roles: (1) rapid dissemination of all sound research and (2) scarce credentialing for prestige and career advancement. This conflict has created a reviewer roulette and anonymous tribunal model - a zero-cost attack system - characterized by high-stakes subjectivity, turf wars, and the arbitrary rejection of sound research (the equivalence class problem). We propose the Impact Market (IM), a novel three-phase system that decouples publication from prestige. Phase 1 (Publication): All sound and rigorous papers are accepted via a PC review, solving the "equivalence class" problem. Phase 2 (Investment): An immediate, scarce prestige signal is created via a futures market. Senior community members invest tokens into published papers, creating a transparent, crowdsourced Net Invested Score (NIS). Phase 3 (Calibration): A 3-year lookback mechanism validates these investments against a manipulation-resistant Multi-Vector Impact Score (MVIS). This MVIS adjusts each investor's future influence (their Investor Rating), imposing a quantifiable cost on bad actors and rewarding accurate speculation. The IM model replaces a hidden, zero-cost attack system with a transparent, accountable, and data-driven market that aligns immediate credentialing with long-term, validated impact. Agent-based simulations demonstrate that while a passive market matches current protocols in low-skill environments, introducing investor agency and conviction betting increases the retrieval of high-impact papers from 28% to over 85% under identical conditions, confirming that incentivized self-selection is the mechanism required to scale peer review.
翻译:顶级学术会议正因两个不可调和的功能而陷入困境:(1) 快速传播所有可靠研究;(2) 为声望和职业发展提供稀缺认证。这一冲突催生了评审轮盘赌和匿名法庭模式——一种零成本攻击系统——其特征是高风险主观性、领地争夺以及对可靠研究的任意拒稿(等价类问题)。我们提出影响市场(IM),一种新颖的三阶段系统,将论文发表与声望解耦。第一阶段(发表):所有可靠且严谨的论文通过程序委员会评审被接受,解决“等价类”问题。第二阶段(投资):通过期货市场创建即时、稀缺的声望信号。资深社区成员向已发表论文投入代币,形成透明、众包的净投资分数(NIS)。第三阶段(校准):一个为期3年的回溯机制根据抗操纵的多维影响分数(MVIS)验证这些投资。该MVIS调整每位投资者未来的影响力(即投资者评级),对恶意行为施加可量化的成本,并奖励准确预测。IM模型以透明、可问责且数据驱动的市场取代了隐蔽的零成本攻击系统,使即时认证与长期验证的影响相统一。基于智能体的模拟表明,被动市场在低技能环境中与现有协议表现相当,而引入投资者能动性和信念投注后,在相同条件下高影响力论文的检索率从28%提升至85%以上,证实激励性自选择是扩展同行评审所需的核心机制。