Understanding the Voting System

Most online feeds say they are powered by "voting." In practice, they are powered by reactions.

The interface asks a loose question—like, dislike, upvote, downvote. It records views, shares, and watch time. These signals are treated as if they were expressions of collective judgment, but they are not the same thing. A "like" can mean "I agree," "this amused me," "my friend posted this," or simply "I tapped by habit." A long watch time can signal fascination, outrage, or confusion. None of these are deliberate statements about what each community as a whole should be seeing.

The problem is not bad faith; it is ambiguity. When the question is unclear, the answers are noisy. When there is no cost to careless voting, there is little incentive to think beyond one's immediate reaction. And when engagement metrics are treated as votes, the system rewards whatever captures attention, regardless of whether it informs, clarifies, or represents the considered view of the group.

Our approach begins from a different premise. Even the simplest democracy has four elements: a clearly defined question, a defined set of voters, equal weight of votes, and an outcome determined by majority rule. Feeds rarely have any of these. We built ours to approximate them as closely as a real-time platform allows.

From Expression to Prediction: The Prediction-Based Rating System (PBRS)

At the core of Veridonia is what we call the Prediction-Based Rating System (PBRS). Each voting round asks a narrow and explicit question: Should this post be shown more broadly within this community? Nothing more. Not whether it is true in some abstract sense, not whether one personally agrees, but whether it is worth collective attention.

A small group of members is randomly selected to answer that question. They do not choose the post; the system assigns it. After they vote, the majority outcome becomes the reference point. Individual ratings are then updated according to how well each participant's vote matched that outcome.

This turns voting into a form of forecasting. Each decision is implicitly a prediction about what the community, consulted more broadly, would decide. Participants who consistently anticipate that outcome gain rating. Those who consistently diverge lose rating. Over time, rating becomes a measure not of authority or virtue, but of predictive reliability.

The mechanism is deliberately relative and zero-sum. Rating cannot accumulate indefinitely. It must be maintained. Early arrival confers no permanent advantage; inactivity and misalignment gradually reduce standing. Influence flows toward those who demonstrate, repeatedly, that they understand how the community judges content, not those who shout the loudest or mobilise the most attention.

Rating affects influence in voting and posting, but not access to reading. The system shapes what rises to prominence; it does not restrict what individuals may view.

Approximating a Referendum: The Multi-Stage Voting Process (MSVP)

If we wanted perfect democratic legitimacy, we would ask every member to vote on every post. That would also make the feed unusably slow. The Multi-Stage Voting Process (MSVP) is our compromise: an approximation of a referendum, structured to remain practical at scale.

In the first stage, a randomly selected group evaluates the post. The goal here is filtration. Clearly, low-signal material is removed early, with minimal cost to the broader community. Because selection is random, no one can reliably insert themselves into specific decisions, and coordinated manipulation becomes uncertain and expensive.

Posts that pass move to a second stage. Here, a smaller group of higher-rated participants makes the final decision. Their role is to act as a statistical proxy, not a permanent elite. Because their ratings reflect a track record of alignment with community outcomes, using them reduces the number of required votes while preserving the expected result of a much larger consultation.

This second stage is not fixed in composition. Ratings change continuously. Participants can rise or fall based on performance. The structure remains bottom-up: representativeness is earned and defended, not granted once and held indefinitely.

Together, PBRS and MSVP allow the platform to simulate the logic of a referendum—clear question, defined voters, majority rule—without asking everyone every time.

Why This Was Necessary

It makes the feed reflective of what the community, taken as a whole, is likely to consider worth attention — not what generates the strongest immediate reactions. This allows a single, diverse community to converge on shared standards, rather than fragmenting into separate spaces divided by narrow biases.

It also changes incentives. When influence depends on predicting collective judgment, participants are pushed to look beyond their own preferences. Modelling the broader community becomes more rewarding than signalling to one's immediate circle. Over time, this reduces the payoff of extreme or purely partisan content that cannot survive wider scrutiny.

Manipulation also becomes more costly. Random selection prevents actors from targeting specific posts at specific times. Because influence must be earned through accurate prediction over many rounds, creating disposable accounts yields little durable power.

And because a post must pass through multiple rounds of structured, majority-based review, it cannot rely solely on energising a narrow slice of the community. To survive the full process, it must be understandable and acceptable to a broader cross-section of participants. In practice, this creates pressure toward material that is clearer, more proportionate, and less dependent on partisan reflex. Content capable of withstanding scrutiny beyond its immediate base.