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Record W4411033834 · doi:10.22161/ijels.103.68

“Our Home and/ on Native Land”- A Perpetual Condemnation and Combat of the Aboriginals— A Case Study of George Ryga’s The Ecstasy of Rita Joe

2025· article· en· W4411033834 on OpenAlexaboutno aff
Yukti Bhardwaj

Bibliographic record

VenueInternational Journal of English Literature and Social Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)EcstasyHistoryArtArt historySociologyAnthropology

Abstract

fetched live from OpenAlex

Through a critical reading of George Ryga's landmark play The Ecstasy of Rita Joe (1967), this essay examines the ongoing marginalization and resistance of Canada's Indigenous peoples. With its roots in Ryga's personal experience as a cultural outsider and its inspiration from a real-life case of an Aboriginal woman who was murdered, the play effectively exposes the systemic racism, gendered violence, and cultural erasure that Aboriginal communities face. The article frames the ongoing discussion about Indigenous rights with the symbolic act of resistance performed by singer Jully Black, who changed the Canadian national anthem to highlight settler colonialism. The play illustrates how dominant colonial structures like the legal system, the Church, and others criminalize, silence, and obliterate Indigenous identity through Rita Joe's tragic story. The study looks at how memory sequences give voice to subaltern experiences while characters like Father Andrew and the Magistrate enforce assimilation. The study makes the case that Rita and Jaimie both embody marginalized voices fighting against imposed identities and systemic violence, drawing on postcolonial theory, particularly Gayatri Spivak's concept of the subaltern.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.842

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0370.028
Scholarly communication0.0040.002
Open science0.0030.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.358
Teacher spread0.343 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English Literature and Social SciencesSame topicIndigenous Health, Education, and RightsFrench-language works237,207