Identity and demographics predict voter enrolment on the Māori electoral roll: Findings from a national sample
Resource type
Authors/contributors
- Greaves, Lara (Author)
- Osborne, Danny (Author)
Title
Identity and demographics predict voter enrolment on the Māori electoral roll: Findings from a national sample
Abstract
Statistics from the New Zealand Electoral Commission (2013) show that only 55% of those who indicate they are of Māori descent are enrolled on the Māori electoral roll. In this paper, we aim to find the statistical predictors of being enrolled to vote on the Māori roll versus being enrolled on the general roll. We present two models analysing demographic and psychological aspects of people’s subjective identification as Māori to predict enrolment on the Māori roll. In model 1, demographic variables from participants of Māori ancestry involved in a national probability sample (N=1,961) were analysed to predict enrolment on the Māori roll. In model 2, data from a subsample of people who identify as Māori (N=662) were analysed to assess the impact of both demographics and identity on electoral roll choice. The dimensions Higher Group Membership Evaluation (the extent to which someone thinks that being Māori is positive and part of their self-concept) and Higher Socio-Political Consciousness (engagement with Māori political issues) predicted enrolment on the Māori roll. Our findings will be useful for those looking to increase Māori roll enrolment and may also help to combat deficit-based arguments for the abolition of the Māori seats.
Publication
MAI Journal: A New Zealand Journal of Indigenous Scholarship
Date
2017
Volume
6
Issue
1
Journal Abbr
MAI Journal
Short Title
Identity and demographics predict voter enrolment on the Māori electoral roll
Language
English
Citation
Greaves, L., & Osborne, D. (2017). Identity and demographics predict voter enrolment on the Māori electoral roll: Findings from a national sample. MAI Journal: A New Zealand Journal of Indigenous Scholarship, 6(1). https://doi.org/10.20507/MAIJournal.2017.6.1.1
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