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Record W2918516443

Embracing Indigenous culture in military organizations: the experience of Māori in the New Zealand military

2018· article· en· W2918516443 on OpenAlexaffvenueabout
Grazia Scoppio

Bibliographic record

VenueJournal of military and strategic studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropology: Ethics, History, Culture
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsIndigenousGeneral partnershipOrganizational culturePolitical scienceIndigenous cultureInclusion (mineral)Public relationsSociologyLawSocial scienceEcology
DOInot available

Abstract

fetched live from OpenAlex

This article builds on a 2007 research on Indigenous peoples in the New Zealand Defence Force (NZDF) which identified best practices from New Zealand that Canada could draw upon to enhance participation of Indigenous peoples within the Canadian Armed Forces. Using organizational culture theory as a conceptual framework, this article further investigates the main approaches and practices that have enabled a positive partnership with Māori and the successful inclusion of Māori culture in the NZDF. Specifically, the paper investigates the mechanisms used by the NZDF and the internal and external environments of the organization supporting the participation of Indigenous groups in the New Zealand military. The discussion explores ways in which Indigenous practices and customs can be incorporated into other military systems and protocols. The paper concludes that, among military organizations, the NZDF is a leader in transforming the organizational culture by enabling the organization to embrace Indigenous culture and empowering Indigenous members within their ranks.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.351
Teacher spread0.304 · 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 designQualitative
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
Published2018
Admission routes3
Has abstractyes

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