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Record W1692365474 · doi:10.25071/1718-4657.36565

Canadian Identity and Canada’s Indian Residential School Apology

2010· article· en· W1692365474 on OpenAlexaffvenueabout
Jason Stabler

Bibliographic record

VenueIntersections conference journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsIndigenousIdentity (music)Residential schoolState (computer science)SociologyPolitical scienceGender studiesLawSocioeconomicsAesthetics

Abstract

fetched live from OpenAlex

Canada’s more than century-long Indian Residential Schools system transferred Indigenous children from their homes and communities to state- and church-run schools with the goal offacilitating their assimilation into Canadian society. In 2008, Canada delivered an official apology for its role in the system and its legacy. This apology has the potential to heal Indigenous/Settler-state relations, but to do so it must transform existing relationships and further simple coexistence as a reconciliation mechanism. The social construction of Canadian identity as lawful and benevolent may present a barrier in achieving these goals and may ultimately hinder meaningful reconciliation with 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)0.003
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.181
Threshold uncertainty score0.950

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0540.013
Scholarly communication0.0110.002
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0210.001

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 head0.015
GPT teacher head0.302
Teacher spread0.288 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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