  This paper is about an information retrieval evaluation on three different
retrieval-supporting services. All three services were designed to compensate
typical problems that arise in metadata-driven Digital Libraries, which are not
adequately handled by a simple tf-idf based retrieval. The services are: (1) a
co-word analysis based query expansion mechanism and re-ranking via (2)
Bradfordizing and (3) author centrality. The services are evaluated with
relevance assessments conducted by 73 information science students. Since the
students are neither information professionals nor domain experts the question
of inter-rater agreement is taken into consideration. Two important
implications emerge: (1) the inter-rater agreement rates were mainly fair to
moderate and (2) after a data-cleaning step which erased the assessments with
poor agreement rates the evaluation data shows that the three retrieval
services returned disjoint but still relevant result sets.
