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Record W2040334088 · doi:10.3138/utlj.2418

Unsettling the lawyers: Other forms of justice in Indigenous claims of expropriation, abuse, and injustice

2014· article· en· W2040334088 on OpenAlexvenueno aff
Carrie Menkel‐Meadow

Bibliographic record

VenueUniversity of Toronto Law Journal · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsExpropriationInjusticeEconomic JusticeIndigenousCriminologyPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

This article considers, from the experience of the Indian Residential Schools Settlement, the limitations of the current formal justice system and the common ways that lawyers and parties act within it. Looking at the combinations of lawsuits, settlement negotiations, structured compensation schemes, truth and reconciliation processes, and memorial and education programs now provided for in the IRSS, the article suggests that we may need ‘process pluralism’ and different orientations to deal with modern mass harms: now recognized harms (like loss of culture, family, language, as well as physical, mental, and social injury) that the formal legal system has not yet developed the capacity to address. Placing the IRSS in a larger international context, the article suggests that some legal and social recognition of ‘new’ human harms and injuries has necessitated the development of different legal and quasi-legal processes. Whether called ‘restorative,’ ‘transitional,’ or ‘alternative’ justice, new forms of dealing with wrongs, harms, and conflicts will require redesigning legal processes and institutions; legal professional education; and social, cultural, and philosophical orientations to human injuries and ‘redress.’ Not all who are injured (both individually and in groups) want or require the same ‘remedies,’ and our conventional and historical common law and adversarial system must be adapted to the diverse needs of those who are injured by past and unconscionable wrongs, especially when inflicted by major governmental, religious, and civil society institutions and practices.

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)0.007
metaresearch head score (Gemma)0.015
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 score0.960
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0330.113
Scholarly communication0.0180.014
Open science0.0030.019
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.182
Teacher spread0.173 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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Same venueUniversity of Toronto Law JournalSame topicCorporate Law and Human RightsFrench-language works237,207