I posted a little while ago about citing papers that you yourself have not read, for which Rob Hyndman came up with the catchy advice "Sight what you Cite". One cause of such sightless citations is that the original work is inaccessible. I've run across an example of this today: Nick Belkin, "Anomalous states of knowledge as a basis for information retrieval", Canadian Journal of Information Science, 1980, pp 133--143.
I'll first attempt to explain why you would want to cite this paper; if you're not interested in this rather long explanation, then please jump to the subsequent section.
ASK and best-match models
The Anomalous States of Knowledge (ASK) model holds that information-seeking behaviour begins from the user's awareness that their knowledge contains anomalies. ASK is a critical response to an earlier (and still predominant) model, which holds that a user's query is a direct statement of their information need. Under this earlier model, the information retrieval task is to find the document or documents that are the best match with the query, in the sense of being the most similar to it. Indeed, so pervasive is this understanding of IR that the algorithms used to determine which documents should be returned for each query are generally known as "similarity measures", because they are regarded as calculating document--query similarity.
The Anomalous States of Knowledge (ASK) theory replies that, on the contrary, while the user is aware that there is something they don't know but want to, they are not in general aware of precisely what it is they don't know. There is, therefore, a fundamental mismatch between documents and queries. A document is a statement of what its author knows; a query is a statement of what the user does not know. Attempting straightforwardly to match the two up is misguided.
The distinction between the best-match and ASK models may seem only a theoretical one, but it does have important practical consequences. The best-match model tends to portray the user's information need as static, and communicable in a single, well-formed query, an understanding that fits well with batch-mode information retrieval. In contrast, the ASK model acknowledges that the user's information need is generally hazy at the beginning, and is clarified and extended in response to exploring the information space; the model, therefore, presents an understanding of the information retrieval process that is intrinsically iterative and interactive.
The experience of the web supports the ASK model; thanks not least to its hypertext nature, the web strongly supports information exploration. Actual web search is a kind of iterative-batch hybrid: users iterate, but the search tool is essentially still a batch retrieval one, matching queries to documents. This may seem sub-optimal, but as Thomas Carlyle says, humans are tool-using animals; we are adept at using tools to achieve goals that the tool does not intrinsically encapsulate; and web search users have learnt the
appropriate effective use of search engines as highly sophisticated keyword-matchers. Indeed, simple, crude tools whose operation is readily comprehensible may well be preferable to complex, highly-tuned tools whose operations are opaque. And if the search experience is a hybrid, the predominant evaluation methods are still resolutely batch-mode; despite a number of attempts to introduce interactivity, mainstream IR system evaluation still consists of assessing the outputs of once-off query runs.
The proceeding was by way of underlining why a cite to Belkin's original paper on the ASK model is something that a researcher might want to make. Looking at the citation, though, one will immediately observe that the Canadian Journal of Information Science seems an obscure journal, as indeed it is. The journal is only available online from 2000 onwards; even the table of contents is not consistently available before that. Nevertheless, Belkin's article is cited 434 times, according to Google Scholar; nearly as often as the 545 citations for the later but more retrievable Belkin, Oddy, and Brooks, "ASK for information retrieval: Part I. Background and theory", Journal of Documentation, 1982, which I have been working off.
So, the first, more utilitarian, question is, does anyone have a digital version of the 1980 paper?
Fundamental papers in obscure places
The second, more interesting question is why it seems to happen so often that highly-cited, fundamental papers get published in such obscure locations. Belkin's paper is only one example of this; there is also Sparck Jones and van Risjbergen's 1975 report on the "ideal" test collection, a number of papers by Stephen Robertson that end up in inaccessible ASLIB proceedings, Ellen Voorhees's talk on the Cranfield paradigm at CLEF 2001 (retrievable for being produced in the Web age, but hardly an archival venue), and so forth. Even within mainstream journals, earlier articles of enduring interest tend to be surprisingly concentrated in nominally lower-ranked journals, such as Information Processing and Management or the Journal of Documentation, than their supposedly higher-impact peers, such as ACM Transactions on Information Systems or the Journal of the American Society for Information Science and Technology.
My surmise is that the obscurer or lower-status venues are more receptive to ideas and arguments that are outside the mainstream or do not fit into the discipline's predominant publication mould. Now of course the majority of these off-beat publications are probably just bad; but the greater freedom of expression and lower barriers to acceptance means that many of the new, original ideas end up here, as well.
A classic example of this process of academic rigidity banishing intellectual innovation in the Information Retrieval sphere is Brin and Page's paper on PageRank. It was rejected from SIGIR for insufficient experimental validation -- an absolute requirement for acceptance in the field -- and instead was published in the (academically) lower-status but less hide-bound proceedings of the WWW conference.