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Record W7117879453 · doi:10.24908/jcri.v12i2.17751

Settler Colonial Saskatchewan and Gender-Based Violence Against Indigenous Women

2025· article· en· W7117879453 on OpenAlexaffvenueabout
Emily Grafton, Amber J. Fletcher

Bibliographic record

VenueJournal of Critical Race Inquiry · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsColonialismIndigenousState (computer science)Face (sociological concept)Power (physics)Historical trauma

Abstract

fetched live from OpenAlex

Women and gender non-conforming people living in Saskatchewan, Canada, face staggeringly high rates of gender-based violence (GBV). These rates are disproportionately experienced by Indigenous women, girls, and Two-Spirit or gender-queer individuals, which can be attributed to both historical and ongoing settler-colonial practices. This timely article provides a structural analysis linking GBV against women and gender non-conforming people to the province's settler colonial politics. It does so by applying a feminist intersectional research methodology to a literature review of legislation, policy, provincial budgets, peer-reviewed scholarship, industry-related reports, and media documents. As such, this article argues that GBV perpetrated against Indigenous women is central to settler colonial violence, enabling the settler state to foster settler colonial expansion and Indigenous dispossession, which are power imbalances in urgent need of redistribution. These settler colonial mechanics are readily observable in Saskatchewan, a province at the forefront of settler colonial development in Canada, partly through these staggering and disproportionate GBV rates.

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 score0.044
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.007
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.367
Teacher spread0.342 · 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 routes3
Has abstractyes

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