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Record W3214264443 · doi:10.2979/jourworlphil.5.2.01

“Under Erasure”: Suppressed and Trans-Ethnic Māori Identities

2020· article· en· W3214264443 on OpenAlexafffund
Georgina Stewart, Makere Stewart‐Harawira

Bibliographic record

VenueTuwhera (Auckland University of Technology) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsEthnic groupAncestorIdentity (music)ColonialismGender studiesSociologyGenealogyEthnologySocial identity theorySocial groupGeographyHistoryAnthropologySocial scienceAestheticsArchaeology

Abstract

fetched live from OpenAlex

The questions raised by Māori identity are not static, but complex and changing over time. The ethnicity known as “Māori” came into existence in colonial New Zealand as a new, pan-tribal identity concept, in response to the trauma of invasion and dispossession by large numbers of mainly British settlers. Ideas of Māori identity have changed over the course of succeeding generations in response to wider social and economic changes. While inter-ethnic marriages and other sexual liaisons have been common throughout the Māori-Pākehā relationship, the nature of such unions, and the identity choices available to their descendants, have varied according to era and social locus. In colonial families, the memory of a Māori ancestor was often deliberately suppressed, and children were encouraged to deny that part of their history and “become” European New Zealanders: a classic form of what we call “trans-ethnicity.” From a Māori perspective, the relationship with Pākehā has been marked by a series of losses: loss of land, language, social cohesion, even loss of knowledge of whakapapa (genealogy). This article explores this last form of loss, which leads to “suppressed” Māori identities, and possible effects of attempting to recover such lost Māori identity rights.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.246
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes2
Has abstractyes

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