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Record W2945439416 · doi:10.3138/chr.2018-0048

Research and Outcomes at the Truth and Reconciliation Commission

2019· article· en· W2945439416 on OpenAlexaffvenueabout
James R. Miller

Bibliographic record

VenueCanadian Historical Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCambodian History and Society
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCommissionMandateOpposition (politics)Political sciencePublic administrationGovernment (linguistics)CentralityLawPublic relationsPolitics

Abstract

fetched live from OpenAlex

Compared to other commissions of inquiry, the Truth and Reconciliation Commission (trc) that investigated residential schools in Canada has had a modest research output and influence on public policy. Although the commissioners worked hard to carry out their mandate and raise awareness of the importance of resolving the legacy of residential schooling and promoting reconciliation, their effectiveness was hampered by several factors. Opposition from some interest groups, including the federal government, complicated their efforts, while some of their own characteristics and approaches also contributed to their difficulties. The limitations imposed by the Indian Residential School Settlement Agreement that defined their assignment, the heavy reliance on legal talent within the commission, and the sheer size of the task they faced were some of the challenges confronting the trc. Ironically, the emphasis of the commission reports on the centrality of history and the commission’s definition of “reconciliation” might prove to be two of the most enduring elements of the trc’s legacy.

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)0.042
metaresearch head score (Gemma)0.085
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: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.798

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.085
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.023
Science and technology studies0.0080.008
Scholarly communication0.0120.006
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.101
GPT teacher head0.364
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 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
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
Published2019
Admission routes3
Has abstractyes

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