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Record W143215057 · doi:10.7202/1044312ar

Uncomfortable Comparisons: The Canadian Truth and Reconciliation Commission in International Context

2018· article· en· W143215057 on OpenAlexaffvenueabout
Matt James

Bibliographic record

VenueLes ateliers de l éthique · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTransitional justiceCommissionMandateContext (archaeology)Political scienceHuman rightsEconomic JusticeArgument (complex analysis)PoliticsAccountabilityAuthoritarianismPublic administrationLawPolitical economySociologyLaw and economicsDemocracyHistory

Abstract

fetched live from OpenAlex

The Canadian Truth and Reconciliation Commission on Indian Residential Schools is a novel foray into a genre previously associated with so-called “transitional” democracies from the post-Communist world and the global South. This basic fact notwithstanding, a systematic comparison with the broader universe of truth commission-hosting countries reveals that the circumstances surrounding the Canadian TRC are not entirely novel. This article develops this argument by distilling from the transitional justice literature several bases of comparison designed to explain how a truth commission’s capacity to promote new cultures of justice and accountability in the wake of massive violations of human rights is affected by the socio-political context in which the commission occurs; the injustices it is asked to investigate; and the nature of its mandate. It concludes that these factors, compounded by considerations unique to the Canadian context, all militate against success. If Canadian citizens and policymakers fail to meet this profound ethical challenge, they will find themselves occupying the transition-wrecking role played more familiarly by the recalcitrant and unreformed military and security forces in the world’s more evidently authoritarian states.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.297
Teacher spread0.263 · 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 designNot applicable
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

Citations19
Published2018
Admission routes3
Has abstractyes

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