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Record W4286291881 · doi:10.3138/jeunesse-14.1.01

Healing Intergenerational Trauma through Cultural Reclamation in David Alexander Robertson’s Cree-Centric Retelling of <i>The Lion, the Witch and the Wardrobe</i>

2022· article· en· W4286291881 on OpenAlexvenueno aff
Petra Fachinger

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsWitchIndigenousNarrativeHistoryAnthropologyGender studiesEthnologySociologyLiteratureArtEcology

Abstract

fetched live from OpenAlex

In this article, I argue that Cree author David Alexander Robertson’s YA novel The Barren Grounds retells C.S. Lewis’s war trauma narrative The Lion, The Witch and the Wardrobe from a Cree perspective. The “war” addressed in The Barren Grounds is that of the violent acts of colonization that have disconnected several Indigenous generations from their ancestral cultures. The compulsion to reimagine this British classic story in a way that focuses on his own cultural background shows that there was something missing for Robertson in the source text: his Cree identity. Using as a framework Suzanne Methot’s approach to complex post-traumatic stress disorder (CPTSD), which results from repeated traumatic experiences over a prolonged period, I demonstrate that The Barren Grounds emphasizes the significance of cultural reclamation for the healing of intergenerational trauma, including trauma resulting from the foster care experience. The Indigenization of Lewis’s story recognizes children’s rights to an education that includes Indigenous children’s and YA literature and adopts nation-specific Indigenous knowledge as a framework for reading this literature.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score1.000

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)0.0010.000

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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