JOURNAL ARTICLE

A Network of Actors Contributing to Arts Accessibility in New Zealand: A Case Study of Arts Access Aotearoa.

  • Published In: I-LanD Journal - Identity, Language & Diversity, 2023, n. 1. P. 107 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Xichen Sun 3 of 3

Abstract

Compared to the short history and low growth of subtitling for the deaf and hard of hearing and audio description on TV in New Zealand, accessibility services provided for audiences in museums, art galleries, theatres, and live events have been developed well by New Zealand local communities supported by the government, though no relevant legislation has been established. Arts Access Aotearoa, a New Zealand charitable trust focusing on increasing New Zealanders' access to arts, has been established for 28 years with a vast group of Arts For All Network members all over the country as well as many patrons, funders, supporters and donators from governments, organisations, or communities. Drawing from the Actor-Network Theory, an inclusive and extensive network of actors is mapped out to explore how it contributes to developing arts accessibility in New Zealand, which has been acknowledged internationally. A documentary research method is adopted to collect data stored on Arts Access Aotearoa's and other related actors' websites as well as any concerned information published online. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:I-LanD Journal - Identity, Language & Diversity. 2023/12, Issue 1, p107
  • Document Type:Article
  • Subject Area:Arts and Entertainment
  • Publication Date:2023
  • ISSN:2532-6368
  • DOI:10.26379/IL2023001_007
  • Accession Number:177126502
  • Copyright Statement:Copyright of I-LanD Journal - Identity, Language & Diversity is the property of Paolo Loffredo Iniziative Editoriali Srl and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.