The design, implementation and evaluation of a multi-document summarization system for sociology dissertation abstracts are described. The system focuses on extracting variables and their relationships from different documents, integrating the extracted information, and presenting the integrated information using a variable-based framework. Two important summarization steps – information extraction and information integration were evaluated by comparing system-generated output against human-generated output. Results indicate that the system-generated output achieves good precision and recall while extracting important concepts from each document, as well as good clusters of similar concepts from the set of documents.