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Record W2592714842 · doi:10.22329/wyaj.v33i2.4842

RECONCILIATION IN TRANSLATION: INDIGENOUS LEGAL TRADITIONS AND CANADA’S TRUTH AND RECONCILIATION COMMISSION

2017· article· en· W2592714842 on OpenAlexaffvenueabout
Kirsten Anker

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsMcGill University
FundersMinistry of Economy, Trade and Industry
KeywordsIndigenousCommissionMainstreamSensibilityLawSociologyPolitical scienceState (computer science)Computer science

Abstract

fetched live from OpenAlex

One of the key elements of reconciliation identified in the recent final report of the Truth and Reconciliation Commission of Canada [TRC] is the revitalization of Indigenous law and legal traditions. Indeed, the practices of the TRC itself have attempted to embody this principle. However, a concern about state-sponsored reconciliation is that the recognition of Indigenous legal traditions is an empty gesture without a robust engagement with them. This article offers one possible method for outsiders to engage with Indigenous traditions in a way that goes beyond lip service and beyond the limitations of superficial forms of recognition in which equivalence is too quickly assumed. By paying attention to the ways that Indigenous principles and practices are embedded in a network of ideas about the world, a picture of a whole “legal sensibility” emerges that, through comparison, shows the dominant legal sensibility to be one alternative among many. In this way, reconciliation is approached as a process of “unsettling” what is taken for 4granted in mainstream understandings of reconciliation and law.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.652

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.064
GPT teacher head0.330
Teacher spread0.266 · 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.

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

Citations13
Published2017
Admission routes3
Has abstractyes

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