Re-imagining Classification Systems in Remote Libraries. Issue 3 (3rd July 2019)

• Record Type: Journal Article
• Authors: Masterson, Maeva; Stableford, Carol; Tait, Anja
• Is Part Of: Journal of the Australian Library & Information Association. Volume 68:Issue 3(2019)
• Page Start: 278
• Page End: 289
• Publication Date: 2019-07-03
• Subjects: Classification -- aboriginal -- libraries -- Northern Territory -- Dewey Decimal System -- bias; Information science -- Periodicals; Information science -- Australia -- Periodicals; Information science -- Pacific Area -- Periodicals; Library science -- Periodicals; Library science -- Australia -- Periodicals; Library science -- Pacific Area -- Periodicals; Information science; Library science; Australia; Pacific Area; Periodicals; 020.5
• DOI: 10.1080/24750158.2019.1653611
• Languages: English
• ISSNs: 2475-0158

Abstract

ABSTRACT: This article is a research in practice paper that outlines a pilot project conducted at Galiwin'ku Community Library, East Arnhem Land in the Northern Territory, Australia. In 2017, the Northern Territory Library partnered with East Arnhem Regional Council to re-imagine a new and different classification system for the library's collection. The concept was to reform existing collection classification from a traditional Western structure to a culturally relevant user-oriented structure and layout. This article explores the background and current practices of Aboriginal Community Libraries within the Northern Territory and the methodology behind the development of the pilot. The literature review identifies classification systems as tools for colonisation, and at pathways for addressing cataloguing and classification in First Nations libraries. Implementation and findings of the pilot are discussed. Implications for practice suggest that information professionals, as gatekeepers to knowledge through the ownership of both cataloguing and classification schemes, have a responsibility to understand bias in classification and seek to support culturally relevant classification options that support the user.