User Incentive Mechanism

Contributor Rewards: Allocated based on five metrics where applicable, namely, engagement, quality, difficulty, reputation, and comprehensiveness. Contributors automatically receive tokens upon task completion, with higher-quality tasks earning greater rewards.

Task Difficulty Incentives: More challenging tasks offer additional token rewards to motivate users to take on challenges and score bigger points for their faction.

Bonuses and Exclusivity: Contributors demonstrating exceptional performance receive faction-based, seasonal, and exclusive rewards to acknowledge and validate their efforts.

DataCrowd introduces a five-metric evaluation and reward system designed to surface useful contributions and fairly compensate contributors:

• Engagement – Tracks how active and consistent a contributor is across tasks

• Quality – Assesses alignment with expected output and peer consensus

• Difficulty – Weighs how complex or ambiguous the prompt or task is

• Reputation – Builds over Zenseie based on prior performance and validation accuracy

• Comprehensiveness – Measures how complete, nuanced, or contextually helpful a response is

This system ensures that rewards aren't just about volume—but actual impact. Contributors are paid relative to the value they provide.