‘These ones will learn it too’: transforming relationships with Chelsea Vowel's ‘kitaskînaw 2350’
Bibliographic record
Abstract
Reading representations of relationships in Chelsea Vowel's story ‘kitaskînaw 2350’ from the graphic anthology This Place: 150 Years Retold, I consider how portrayals of expanded relationships are a call to action – a generative lens through which settler-colonial studies may engage with anticolonial teachings. I aim to demonstrate how reading Indigenous literatures can expand and transform the settler-colonial imagination that has been taught to understand the world through a lens of exclusive ideologies like white supremacy and, broadly, the linear and the binary in relation to gender, time, and ways of being. Looking to Vowel's story as an example, I contend that such work is of particular significance to the ongoing surge of Indigenous literary and creative production and to the dismantling of settler-colonial teachings in so-called Canada. This analysis of ‘kitaskînaw 2350’ underlines complex connections between settler-colonialism, knowledge creation, language, imagination, power, and Indigenous literatures. Joining many other scholars who are showing how Indigenous literatures generate new imaginaries that can transform colonial behaviors and systems, I read representations of Indigenous-led worlds and anticolonial teachings as an urgent call to action to heal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".