Evaluation and Reward

Traditional T2E platforms focus on quantity over quality, leading to poor incentives, spammy contributions, and low-quality feedback.

To fix this, 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 time 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.