Not too long ago I had the good fortune to read through Mary Midgley's�Beast And Man: The Roots of Human Nature.�An excellent work on human nature which I would highly recommend.
Among the many compelling points raised in the book, one in particular stood out, especially as someone familiar with the academic environment. She criticises the "battery-egg system of academic production" �and goes on to add:
Future historians will surely find it hard to believe that this system was actually accepted in practice?that, in this highly sophisticated age, academic work was assessed essentially in quantitative terms, by number of publications and sometimes even by number of pages published.
The point is not just that this arrangement encourages industrious mediocrity. It is that anyone, however gifted and original, who has to keep publishing at this rate is forced to choose small topics?usually negative ones?and to treat them at disproportionate length. Quality is indeed supposed to be kept up by requiring publication in "reputable journals." But the sheer mass of print flooding out is such that most of it cannot hope to find readers anyway. Nobody has time for such endless reading, even if it were likely to be useful.
Two key issues are raised here: �Firstly, what we consider to be valuable knowledge and secondly, knowledge overload.
What is valuable knowledge? Having come across my fair share of obscure research topics I have at times wondered how many people would find a specific piece of knowledge to be of value. Would the researcher's efforts be better placed in focusing on a different topic? How would one go about measuring the "value" of this knowledge? If publicly funded, at the very least a panel must have decided that this would be knowledge of value, and in any case a supervisor must have found the proposed source of research interesting and valuable enough to accept.
The first step in defining the usefulness of knowledge can be immediate relevance. Someone,�somewhere�must find this knowledge�immediately�valuable. If not, then the knowledge is created either to fulfil individual interests or in the hope that someone at a future point will find it useful. The latter would appear to be both a wasteful and time intensive/low reward approach to knowledge creation, but one can never be sure of what a single individual may go on to accomplish with the knowledge created. Given the inherent uncertainty surrounding such an approach, we may therefore choose present social relevance as the first step in defining the value of knowledge, i.e., someone else in the organisation or world should be interested enough to look at it upon its creation.
Where it gets problematic is assigning measures of value. For the sake of simplicity we will consider that all knowledge resources are accessible via a web-based platform where access to a particular piece of knowledge is quantifiable. Would the number of unique access and/or references be an indicator of value? It would surely be a measure of popularity, but again this is not a clear indication of value. A highly obscure piece of mathematical research may be of interest to no more than a dozen researchers worldwide, but it could potentially be the catalyst for a major discovery.
What if we consider the individuals accessing the knowledge? Would more senior/eminent individuals�(based on what?) be assigned a higher weight as knowledge customers? Perhaps modifying our knowledge value algorithm in this way would provide a more accurate value indicator. Again though, this ignores the �possibility that a lower grade individual or group may use this knowledge as an important catalyst/source of inspiration.
These are just some of the complex points raised in attempting to define knowledge value, and despite all attempts at developing quantifiable measures, it would still be no absolute guarantee of value. There are simply far too many complex factors at play to assign such a label. What we can do though is to use such algorithms as no more than general indicators. This of course is relevant only after the knowledge has been created. Attempting to define value before its creation is made even more complex, given that it is not always clear what will be discovered,�intentionally�or unintentionally.
For the sake of brevity I will discuss the issue of knowledge overload in my next post.�