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Indigenous Peoples’ Cultural Rights in Transitional Justice

2025· book-chapter· en· W7084091520 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTransitional justiceHuman rightsIndigenous rightsRestorative justiceHarmEconomic JusticeWrongdoing

Abstract

fetched live from OpenAlex

Abstract The marginalization of cultural rights in transitional justice is inextricably intertwined with the field’s historical marginalization of Indigenous Peoples. While Indigenous Peoples endure the full spectrum of human rights violations, much of the harm they sustain is directed at their unique cultural identities and practices. Forced removals of Indigenous children, the banning of Indigenous languages and dress, restrictions on cultural and spiritual practices and various assimilationist policies have all been pursued by States to culturally eliminate Indigenous Peoples. In the wake of this violence, Indigenous Peoples consistently prioritize approaches that seek to reckon with a loss of culture. Thus, a cultural rights-based approach to transitional justice is most likely to take root in cases of large-scale harm perpetrated against Indigenous Peoples. This chapter charts the evolution of transitional justice’s interaction with Indigenous Peoples, ranging from wholesale neglect to the current emerging consensus that historical and contemporary wrongdoing against Indigenous Peoples can and should be addressed through some sort of transitional justice response. A cultural rights-based lens is then applied to three distinct transitional justice initiatives in the context of large-scale wrongdoing against Indigenous People: (1) Canada’s National Inquiry into Missing and Murdered Indigenous Women and Girls, (2) Victoria’s Yoorrook Justice Commission, and (3) the Peruvian theatre collective Yuyachkani. These diverse cases provide insights into the ways in which transitional justice programming has already begun to embrace a cultural rights-based approach in the case of large-scale harm perpetrated against Indigenous Peoples.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.040
Scholarly communication0.0080.005
Open science0.0010.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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 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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