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Record W7105627063 · doi:10.3138/ijcs-2025-0006

Settler-Colonial Violence and Commodification of Indigenous Bodies: Canada’s Missing and Murdered Indigenous Women and Girls in Marie Clements’ Play <i>The Unnatural and Accidental Women</i> and Carl Bessai’s Film <i>Unnatural &amp; Accidental</i>

2025· article· en· W7105627063 on OpenAlexvenueaboutno aff

Bibliographic record

VenueInternational Journal of Canadian Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCommodificationAccidentalPhenomenonWhite (mutation)State (computer science)

Abstract

fetched live from OpenAlex

The Missing and Murdered Indigenous Women and Girls (MMIWG) phenomenon has taken monstrous proportions in Canada, having become a national concern, with many organizations, institutions, communities, and individual groups dealing with missing loved ones in their midst. The state of Canada, academic studies, books, documentaries, short and feature films, art as well as theatre plays have taken on this phenomenon – all with the purpose of raising awareness in both Indigenous and non-Indigenous groups to wake up the nation to systemic rape and killing of Indigenous women and girls, and also to warn and train such women and girls to consciously work on not becoming the next victim. This article looks at the sexed and raced colonization and commodification of Indigenous women’s bodies and the genealogy of white male views on and stereotypes of Indigenous women in Canadian history and North American film history. Tied in with these discussions, the article analyzes and compares Marie Clements’s play The Unnatural and Accidental Women (2000) and Carl Bessai’s film Unnatural &amp; Accidental (2006) and looks at how both play and feature film expose the confluence of racist stereotypes and settler-colonial male violence and critically contextualize one mass murder case as emblematic of the MMIWG phenomenon.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.300
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 teacher head, not a consensus.

Study designObservational
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 routes2
Has abstractyes

Explore more

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