The document presents research on rating scales for collective intelligence in innovation communities. It discusses how organizations face challenges in selecting the best ideas from large pools of information. The research aims to determine which rating mechanisms perform best for idea selection by examining the effects of rating scale granularity on rating accuracy and user satisfaction. An experiment compares a promote/demote scale, 5-star scale, and complex scale in their ability to correctly rate ideas. Results find the complex scale leads to higher rating accuracy and user satisfaction than simpler scales. The findings have implications for designing effective rating systems and extending theories of collective intelligence and creativity.