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Record W4367666247 · doi:10.15691/0719-9112vol10n2a9

Transitional Justice in Established Democracies: Analysis of the Canadian, South African, and Chilean experiences

2022· article· en· W4367666247 on OpenAlexaboutno aff
Hugo Rojas, Salvador Millaleo Hernández, Miriam Shaftoe

Bibliographic record

VenueLatin American Legal Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLegal processes and jurisprudence
Canadian institutionsnot available
FundersAgencia Nacional de Investigación y Desarrollo
KeywordsTransitional justiceCommissionIndigenousPolitical scienceEconomic JusticeHuman rightsState (computer science)Cultural assimilationUnrestSociologyPolitical economyCriminologyPublic administrationLawEthnic groupPolitics

Abstract

fetched live from OpenAlex

In the last four decades, theories and mechanisms of transitional justice have been formulated and implemented in numerous countries, forming an interdisciplinary theoretical and practical corpus. This paper proposes to expand the scope of transitional justice so that it can be applied in stable democracies. The proposed reformulation could be useful to address structural injustices affecting indigenous peoples, that are a legacy of colonialism and assimilationist policies, and to address acts of state repression that constitute serious human rights violations. These reflections are formulated on the basis of three recent case studies: 1) from the Canadian experience, the Royal Commission on Indigenous Peoples, the Truth and Reconciliation Commission, and the National Inquiry into Missing and Murdered Indigenous Women and Girls are analyzed; 2) from South Africa, the Truth and Reconciliation Commission, the Constituent Process and the Land Reform are discussed; and 3) from the Chilean case, the link between social unrest and transitional justice, as well as the Constituent Process, are explained.

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)0.002
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.715

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0510.018
Scholarly communication0.0070.003
Open science0.0020.008
Research integrity0.0020.004
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 head0.023
GPT teacher head0.307
Teacher spread0.284 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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