Contemporary Crises, Historical Antecedents: Refusing Vulnerability in Indigenous Speculative Fictions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cherie Dimaline’s (Métis) Empire of Wild (2019) and Jessica Johns’s (Cree) Bad Cree (2023) refuse to frame the violent events at their centre as isolated or incidental. Instead, authors situate crises within the long historical continuum of settler-colonialism and its impact on Indigenous communities in Canada. Catriona Mackenzie et al.’s expansive intersectional taxonomy of vulnerability defines its pathogenic variant as emerging from entrenched ‘sociopolitical oppression or injustice.’ Pathogenic vulnerability demonstrates how specific groups can experience conditions that render them more vulnerable to violence. In this article, I argue Dimaline and Johns utilise speculative tropes to interrogate widespread decontextualised state narratives of individual vulnerability. Violent events are alternatively narrated as products of their specific context – the conditions of pathogenic vulnerability conferred upon Indigenous peoples in settler-colonial nations. A central protagonist’s individual search for truth foregrounds narrative engagement with contemporary issues facing communities – Murdered and Missing Indigenous Women, Girls and Two-Spirit People (MMIWG2s) statistics, land grabs, state-sponsored industrialism and environmental and psychological devastation within post-extraction communities. Yet authors resist reasserting victim paradigms or employing a reconciliatory politics. Speculative tropes instead encourage what Jo-Ann Archibald (Stó:lō) calls storywork. Such tropes, which denaturalise violent encounters, encourage lateral thinking via nested narratives/metanarratives and embed both traditional monsters and alternative worlds, instigate storywork through inciting deeper reader engagement while foregrounding Indigenous agency, knowledge and resistance.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it