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Record W7143718650 · doi:10.34428/00013249

Indian Residential Schools and Unmarked Graves in Canada: the Question of Genocide

2022· article· en· W7143718650 on OpenAlexaboutno aff
HUGHES,, Robert

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicColonial History and Postcolonial Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideEthnic groupEthnographyIndigenous

Abstract

fetched live from OpenAlex

Understanding the history and dark legacy of what happened to Indigenous children at residential institutions in Canada is important because it offers a window into destructive colonial practices under the guise of education.There will always be residential school harm deniers.They will continue to insist that the church, government, and administrations had good intentions.They might also argue that violence against children was not uncommon at the time and disease was the culprit in high mortality.Residential schools were not an exception in government policy.They were part of a coordinated means to end a way of life.For those willing to investigate the truth about residential schools, Canada will never again be the country that they thought it was.

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)0.008
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: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.991

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0330.018
Scholarly communication0.0100.004
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.271
Teacher spread0.259 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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