'The Potential Diversity of Things We Call TV': Indigenous Community Television, Self-determination and NITV

'The Potential Diversity of Things We Call TV': Indigenous Community Television, Self-determination and NITV 

作者： Rennie, Ellie;   Featherstone, Daniel


作者職稱： Research Fellow, Institute for Social Research, Swinburne University of Technology ;  Media Coordinator, Ngaanyatjarra Media

資料來源：Media International Australia, Incorporating Culture & Policy, No. 129, Nov 2008: 52-66

Journal Title: Media International Australia, Incorporating Culture & Policy
Issue: 129
Pagination: 52-66
Peer Reviewed Article Indicator: Yes
Date of Publication: Nov 2008
Publication Year: 2008
Document Type: Journal Article
主題： Aboriginal Australians in mass media;   Ethnic television broadcasting -- Australia;   Television broadcasting policy -- Australia;   Television broadcasting -- History;   Aboriginal Australians -- Politics and government;   Local mass media

摘要：The National Indigenous Television (NITV) service was launched in July 2007. NITV's public service broadcasting model has arrived after two decades of successful community-based enterprise. Indigenous groups, guided by policies of self-determination, developed a robust grassroots media system based on community ownership and regional collaboration. The arrival of NITV raised important questions for the sector. Can locally sourced content provide the levels of leadership and national unity achieved by public service media during the broadcast era? How can Indigenous media play a greater role in the Australian public sphere? Can locally controlled media offer national narratives? Where does industry development begin and end? As the Indigenous media sector faces up to these issues, two distinct approaches are emerging. One presents a unified picture of Indigenous Australia; the other enables diverse groups to tell their own stories. This paper examines the tensions and possibilities of the new Indigenous media landscape by looking back at the self-determination governance model of the past.