From Event Contracts to Social Fact Engines: Gougoubi's Reconstruction of the Prediction Market Paradigm

Author: Gougoubi Labs

Compiled by: SONG DOGE

In the past few years, prediction markets have been repeatedly discussed in the context of cryptocurrency: they are like "more honest polls" and "more efficient information aggregators." However, when we zoom in, we find that the true form of most prediction markets is not really a "market," but rather an event contract packaged by a platform: the platform decides which topics can be listed, how they are categorized, when they are settled, which oracle to use, and who will arbitrate. The trading interface is quite decentralized, but the governance structure is highly centralized. As a result, prediction markets have remained as "available financial products" rather than becoming "reusable information infrastructure."

This is the fundamental contradiction of current prediction markets: they claim to produce public probabilities, yet rely on a few individuals to define what is worth predicting, who is qualified to submit facts, and how disputes are resolved. Consequently, as the market size grows, it tends to lean towards stronger centralization thresholds: stricter listing reviews, narrower topic ranges, a more order-book-like trading experience, and more "corporate" risk control. These measures are certainly effective, but this path will not push prediction markets towards a "social-level governance mechanism"; it will only solidify them into another category of derivatives.

Gougoubi's ambition is not to make prediction markets more like Polymarket, but to transform prediction markets from a "product" into a "protocol."

Its core assumption is that the true limit of prediction markets is not the efficiency of matching, but who is making the oracle, how the oracle is constrained, and how disputes are socially processed. In other words, the value of prediction markets lies not in "your ability to place bets," but in "your ability to have facts confirmed by the community without intermediaries."

In Gougoubi's design, predictions are not content supplied by the platform, but a sovereign expression of the community. Everyone can create their own prediction tracks and solidify those tracks into their own communities. A community is not a "chat group," but an on-chain organization centered around consensus and dissemination: each prediction is governed by the organization, and each condition is treated as a callable "conditional oracle." This means that prediction markets are no longer confined by centralized classifications such as sports, games, or politics; they can be segmented down to your daily work, life, industry judgments, and process decisions, forming a highly granular "social fact production line." Information explosion is not noise, but a marketable expression of professional knowledge from different fields, which can ultimately be settled and reused.

To make this work, "oracles" must be transformed from a single-point service into a social process. Gougoubi's key innovation is to break the entire process into governable state machines, requiring each critical link to be advanced through community decision-making, rather than relying on an eternally correct "external authority."

The state flow you provided is essentially a model of "low-friction optimistic governance + strong constraint final review": conditions are created first, then activated by a committee vote; after activation, the market opens for trading and liquidity; upon expiration, the Leader submits results to enter RESOLVED; then it goes into committee settlement voting and a two-round fallback mechanism; if consensus on settlement is difficult to achieve, it enters EXCEPTIONAL; if preliminary settlement is approved, it enters DISPUTED and opens a 24-hour dispute window, where anyone can initiate a dispute with stakes and evidence; ultimately, it is arbitrated by the supreme committee, or in the case of timeout, forcibly settled as DRAW, ensuring the system does not get stuck.

The significance of this design lies not in being "more complex," but in transforming the generation of facts into a public process that is accountable, challengeable, and terminable: rapid settlement without disputes, and making conflicts explicit with economic penalties to correct errors.

It shares similarities with UMA's approach (optimistic oracles, dispute windows, dispute stakes, final arbitration), but Gougoubi attempts to create a variant that is "more decentralized yet lower friction than UMA": decentralization is reflected in two aspects—first, disputes no longer rely on the passive participation of a few "default voters," but instead bring participation rights to the forefront of community structure through committee governance and challenge windows; second, final arbitration is not an abstract "voting system," but is bound to the responsibilities of the committee and the supreme committee, introducing Leader penalties and penalties for disputing parties, making errors not "unexpected due to lack of votes," but "costs that will be settled."

Low friction is reflected in three aspects—first, non-disputed paths are as short as possible: activation—trading—submission—voting—automatic settlement; second, two rounds of voting and the EXCEPTIONAL fallback reduce indefinite delays; third, timeout DRAW ensures the system is always convergent, avoiding governance paralysis from "waiting forever for an external person to vote."

At the trading level, Gougoubi also deliberately distinguishes itself from the traditional "platform-based market-making" approach: you designed two models, robust LP and risk LP, where robust LP does not participate in the final win-loss distribution, only earning fees and can exit with restrictions; risk LP participates in result distribution but cannot exit, sharing risks and benefits with the winners. Its philosophy is very clear: the value of liquidity providers is to "provide depth and reduce slippage," and they should not be forced to bear asset erosion caused by trading paths; participating in settlement is a proactive choice to bear result risks in exchange for higher long-term returns. This gives the market two types of capital preferences from the start: robust funds that prefer "infrastructure returns" and risk funds that prefer "opinion returns." More importantly, it separates "depth" from centralized market makers and returns it to community members.

If traditional prediction markets resemble "event casinos listed on platforms," then Gougoubi is closer to a "decentralized real-world governance system." It is not reforming a trading interface, but the three underlying norms of prediction markets.

The first norm is "facts must be governable." Traditional prediction markets outsource facts to oracle services or platform adjudication; Gougoubi turns facts into process states within the organization. Facts are no longer a single answer, but a retraceable on-chain history: who activated it, who submitted it, who voted, who challenged, who arbitrated, who was punished, and when it timed out. Facts shift from "believing in some authority" to "accepting an auditable procedure."

The second norm is "disputes must be priced." In many systems, disputes are product risks, customer service costs, and compliance burdens; in Gougoubi, disputes are a core function of the mechanism. Because many issues in the real world are not purely objective price feeds, but judgments with semantics, boundaries, and interpretive space. Making disputes explicit and constraining them with stakes, penalties, and time windows is equivalent to transforming "social conflicts" into "liquidatable economic processes." This is a financialized expression that is closer to real governance.

The third norm is "predictions must be reusable." Most prediction market probabilities only serve bettors; Gougoubi attempts to make each condition a callable oracle, allowing all prediction markets and applications to consume these "conditional results." When conditions can be reused, prediction markets are no longer just trading venues, but become an open public interface: DAOs can use it for proposal KPI binding and execution conditions, DeFi can use it for risk parameters and dynamic collateral, and even the embodied robot training you mentioned can use "human society's judgment of results" as an external signal source for action strategies—not letting AI guess boundaries through computational stacking, but allowing it to learn to act within social consensus, converge in disputes, and make risk-controllable decisions in uncertainty.

This is also the most philosophical aspect of Gougoubi: it elevates "prediction" from a profitable skill to a governance method. Human society will inevitably continue to produce results: whether policies are implemented, project successes or failures, market directions, collective emotions, technological routes, and ethical boundaries. Handing these "results" over to a few centralized entities for adjudication may be more efficient, but the cost is that the trust structure cannot be reused; handing them over to a completely random public opinion arena will lead to noise and distortion. Prediction markets provide a third path: expressing cognition through prices, constraining disputes through mechanisms, and producing facts through organizations.

Therefore, if Gougoubi succeeds, the trend it brings will not just be "another prediction market," but a return of prediction markets as a form of social infrastructure: it can transcend the significance of stock and cryptocurrency markets, not because it absorbs more trading volume, but because it begins to undertake a more fundamental function—transforming the tacit knowledge scattered around the world into a public truth that is liquidatable, accountable, and reusable. The truth no longer belongs to the platform or any oracle service provider, but to those who are willing to jointly safeguard it with rules, costs, and time. Gougoubi attempts to write this into the protocol, making "the truth belongs to the community" not just a slogan, but an operable on-chain process.