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Record W2899524249 · doi:10.3366/ircl.2018.0270

The Triumph of Olemaun: Survivance, Empathic Unsettlement, and Restorying the History of Canadian Residential Schools

2018· article· en· W2899524249 on OpenAlexaboutno aff
Anah-Jayne Markland

Bibliographic record

VenueInternational Research in Children s Literature · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsResidential schoolIndigenousIgnoranceNarrativeMythologyCurriculumCONTESTCommissionIndigenous educationSociologyHistoryPedagogyLawPolitical scienceLiteratureArtClassics

Abstract

fetched live from OpenAlex

The ignorance of many Canadians regarding residential schools and their traumatic legacy is emphasised in the reports of the Truth and Reconciliation Commission (TRC) as a foundational obstacle to achieving reconciliation. Many of the TRC's calls to action involve education that dispels and corrects this ignorance, and the commission demands ‘age-appropriate curriculum on residential schools, Treaties, and Aboriginal peoples' historical and contemporary contributions to Canada’ to be made ‘a mandatory education requirement for Kindergarten to Grade Twelve students’ (Calls to Action 62.i). How to incorporate the history of residential schools in kindergarten and early elementary curricula has been much discussed, and one tool gaining traction is Indigenous-authored picturebooks about Canadian residential schools. This article conducts a close reading of Margaret Pokiak-Fenton and Christy Jordan-Fenton's picturebook When I Was Eight (2013). The picturebook gathers Indigenous and settler children together to contest master settler narratives regarding the history of residential schools. Using Gerald Vizenor's concept of ‘survivance’ and Dominick LaCapra's notion of ‘empathic unsettlement’, the article argues that picturebooks work to unsettle young readers empathetically as part of restorying settler myths about residential schools and implicating young readers in the work of reconciliation.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.745
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.318
Teacher spread0.270 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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