Classification in a social world: bias and trust

Jens‐Erik Mai
2010 Journal of Documentation  
explores issues of bias and trust in classification in his article "Classification in a social world: bias and trust." Deeply focused on the role of indexer in the establishment of aboutness, he seeks to establish pluralism as the new foundation for classification. In his article, the reader is taken from the traditional formation of classification systems to a new, and in Mai's opinion, ideal process for the creation of classification systems. In the traditional creation of a classification
more » ... tem, the creator is recognized as authoritative. Yet as Mai emphasizes, classification systems are created within a context. If a classification system is removed from its context, it ceases to appear as authoritative. The interesting implication is that context may provide authority to a classification system, instead of the authority residing in the classification system. The removal of a classification system from its context reveals the "arbitrary and conjectural nature," (Mai, p.628) and the bias of the creator. The elimination of bias from classification systems is an ideal, and considered impossible. Yet the important task may be to recognize the bias, even if cannot be removed. Bias is inherent in any classification system due to the fact that on some level the human creator of the classification system must make subjective decisions concerning the aboutness of the subject matter. Mai also expounds upon the long history within Information Science to seek the creation of the perfect system for classification. Despite the constant drive within Information Science to create the ideal classification system, Mai points out that the "exposition of the philosophical basis for classification have gone unnoticed for a good part of the last 140 years." (Mai, p.629) Following the thought that the philosophical foundation of classification has not been sufficiently examined, Mai cites Miksa concerning the philosophical assumptions of classification systems. These assumptions are that "knowledge categories are by nature hierarchical and logical in a classical, systematic sense," and that we "should try to produce the one best classification system that will serve all purposes." (Miksa, as cited by Mai, 2010, p.629) Mai further suggests that these assumptions fit paradigms neatly, especially in traditional sciences. Drawing on the work of Svenonius, Mai also concludes that classifications have traditionally been created to cross many disciplines in the search of commonalities. In order to dissect the issues of knowledge organization, Mai divides knowledge organization problems (KOP) into three categories. The categories are dubiously entitled, "Big KOP," "Medium KOP," and "Small Kop." (Mai, 2010, p.630) Big KOP describes large repositories of information such as large libraries. Medium KOP tends to be associated with an information collection that exists for a particular purpose. Small KOP are information
doi:10.1108/00220411011066763 fatcat:6osglvnno5cbrapeot3sze5mqu