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Record W4408823253 · doi:10.5194/oos2025-1237

Tangaroa Ararau:  Reimagining Ocean Governance by Integrating Indigenous Perspectives for a Sustainable Future

2025· preprint· en· W4408823253 on OpenAlexaff
Beth Tupara-Katene, Te Puoho Katene, Horiana Irwin-Easthope, Terence I. Walker

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsIndigenousCorporate governancePolitical scienceEnvironmental planningSociologyGeographyBusinessEcologyFinanceBiology

Abstract

fetched live from OpenAlex

Aotearoa New Zealand, like many other countries, has reached a point where increasing tensions and stressors afflicting our marine environment have highlighted a need for transformation. In order to promote the health and wellbeing of our oceans, the concepts, values and interests that drive human interactions, decision making and prioritisations in regard to the ocean must be revisited. This has been demonstrated, both locally and internationally, in the mounting momentum towards sustainability, increasing sensitivity to non-financial factors and the social license to operate in industries dependent on natural resources.This context paved the way for this research project Tangaroa Ararau – Te Tiriti o Waitangi, Tikanga Māori and the marine environment. For Māori, the indigenous people of Aotearoa New Zealand, Tangaroa is the deified term given to the physical ocean environment and all life within it.Māori pedagogies invoke direct genealogical connections to Tangaroa, a relationship that compels humans to act with a sense of familial responsibility: a set of behaviours and beliefs that, through this research, can be a foundational framework to put Tangaroa at the heart of the management and governance of the marine environment.This research aimed to reimagine Aotearoa New Zealand’s marine governance system, placing the ocean at its center, and upholding the rights guaranteed to Māori under Te Tiriti o Waitangi—the foundational Treaty between the British Crown and Māori. In collaboration with Māori experts, the research established core design principles grounded in indigenous knowledge. These principles provided a foundation for examining the challenges and biases in current marine governance frameworks and supported the development of new, future-focused models.Futures-thinking methods, such as futures triangles, causal layered analysis, and scenario planning, were also used to analyse key trends, anticipate disruptions, and design governance options that prioritise values-driven, inclusive, and ocean-centered decision-making. The findings emphasise the critical role of indigenous perspectives and values in creating an ocean-centered governance system that equally considers the wellbeing of the environment as well as the diverse communities that depend on it.Establishing transformative, ocean-centric governance models requires broad, principles-based alignment across the spectrum of institutions and communities. A holistic approach built on a foundation of Māori values, that empowers local communities and adopts intergenerational planning horizons, could form a resilient, equitable, and unique marine governance framework capable of addressing the challenges of the 21st century.Such a transformation requires shifting hearts and minds of all people with a connection to the ocean. In order to convey the findings of this research to a broader audience, the research was disseminated in culturally meaningful ways, including through an art exhibition event featuring toi Māori (Māori art), whakairo (carvings), waiata (song), and tā moko (tattooing), drawing a connection between the emotional connection of art and the sea to the prevailing policy issues of the time. This approach aims to inspire a shared commitment to an ocean-centered future for Aotearoa, uniting people in the effort to look after and care for our ocean.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.402
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.240
Teacher spread0.237 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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