A recent discussion between some colleagues on the utility (or otherwise) of subject classification in repositories prompted me to undertake a brief investigation whose results I present here. (I'll also send this to AMSCI, so apologies for any duplicate copies that you see.) The discussion has broadly been between computer scientists and librarians over whether subject classification schemes offer advantages over Google-style text retrieval; the study below looks at the evidence as demonstrated in the usage of one particular repository. As such it doesn't address the intrinsic value of classification, but it does offer some insight into the effectiveness of navigational tools (including subject classification) in the context of a repository. ---------------- The University of Southampton Institutional Repository has been in operation for a number of years and an official (rather than experimental or pilot) part of its infrastructure for just over a year. As part of its capabilities, it includes lists of most recently deposited material, various kinds of searches, a subject tree based on the upper levels of the Library of Congress Classification scheme and an organisational tree listing the various Faculties, Schools and Research Groups in the University and a list of articles broken down by year of publication. These all provide what we hope are useful facilities for helping researchers find papers (ie by time, subject, affiliation or content). Over a period of some 29.5 hours from 0400 GMT on March 7th 2006, 1978 "abstract" pages (ie eprints records) were downloaded from the repository (ignoring all crawlers, bots and spiders). Of the 1978 downloaded pages, the following URL sources (referrers, in web log speak) were responsible: 439 - (direct URL, perhaps cut and paste into a browser or clicked on from an email client) 225 EPRINTS SOTON pages 25 OTHER SOTON WEB pages 1264 EXTERNAL SEARCH ENGINES 21 EXTERNAL WEB PAGES ie the local repository facilities, including subject views and searches, led to only 225/1978 = 11% of all downloads.