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Record W3205056147 · doi:10.25071/2564-4661.24

Graphic Reminders: Confronting Colonialism in Canada through Betty: The Helen Betty Osborne Story

2021· article· en· W3205056147 on OpenAlexaffabout
Raven Lovering

Bibliographic record

VenueContemporary Kanata Interdisciplinary Approaches To Canadian Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsYork University
Fundersnot available
KeywordsIndigenousInjusticeColonialismNarrativePoliticsHistorySociologyAnthropologyGender studiesArt historyMedia studiesArtLawLiteraturePolitical science

Abstract

fetched live from OpenAlex

David Alexander Robertson’s 2015 graphic novel Betty: The Helen Betty Osborne Story connects non-Indigenous Canadians to the racial realities of Canada’s intentionally forgotten past. Robertson translates Helen Betty Osborne’s biography into the accessible format of the graphic novel which allows for a wide range of readers to connect present day racial injustices to the past, generating new understandings surrounding violence against Indigenous peoples in Canada. Helen Betty Osborne, a young female Cree student was abducted and murdered in 1971, targeted for her race and gender. The horrors Betty experienced reveal the connection between her story and the contemporary narrative of Missing and Murdered Indigenous Women in Canada. Betty: The Helen Betty Osborne Story deconstructs Betty’s life from the violence she is subjected to, personifying a historical figure. The graphic novel allows for a visual collision of past and present to express the cycle of colonial violence in Canada ignored by non-Indigenous Canadians despite its continued socio-economic and political impact on Indigenous peoples. As an Indigenous author, Robertson preserves the integrity of Indigenous voice and revives an integral gendered and racialized historical perspective that is necessary to teach. This close reading of Betty: The Helen Betty Osborne Story explores how Robertson uses the graphic novel to revive history and in doing so, demonstrates connections between past and present patterns of racial injustice against Indigenous women in Canada today.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0510.022
Scholarly communication0.0110.003
Open science0.0020.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0120.001

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 head0.274
GPT teacher head0.278
Teacher spread0.004 · 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
Published2021
Admission routes2
Has abstractyes

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