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Record W803134965 · doi:10.18584/iipj.2012.3.1.4

Mãori Customary Law: A Relational Approach to Justice

2012· article· en· W803134965 on OpenAlexaffvenue
Stéphanie Vieille

Bibliographic record

VenueInternational Indigenous Policy Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsWestern University
Fundersnot available
KeywordsIndigenousEconomic JusticeRestorative justiceSociologyContext (archaeology)Embodied cognitionRepresentation (politics)Government (linguistics)CriminologyLawPolitical scienceEnvironmental ethicsEpistemologyGeographyPoliticsEcology

Abstract

fetched live from OpenAlex

This research paper examines the philosophy of justice embodied in tikanga Mãori, the Mãori traditional mechanism and approach to doing justice. Based on several months of fieldwork in New Zealand, this study contends that the Mãori approach to justice adopts a holistic and relational lens, which requires that justice be seen in the context of relationships and crimes dealt with in terms of the relationships they have affected. As a result, justice must be carried out within the community and the process owned by community members. Further discussion draws attention to the response of Mãori communities to the New Zealand government’s attempt to accommodate their traditions and warns against the global tendency to render traditional Indigenous approaches to justice ahistorical through their representation as restorative justice mechanisms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.027
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.369
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2012
Admission routes2
Has abstractyes

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