Collecting relevance judgments (qrels) is an especially challenging part of building an information retrieval test collection. This paper presents a novel method for creating test collections by offering a substitute for relevance judgments. Our method is based on an old idea in IR: a single information need can be represented by many query articulations. We call different articulations of a particular need query aspects. By combining the top k documents retrieved by a single system for multiple query aspects, we build judgment-free qrels whose rank ordering of IR systems correlates highly with rankings based on human relevance judgments.