Falling Back in Love with Trans-Inclusive Feminism: Canadian Creative Artists Re-Story Death and Choose Transformation
Bibliographic record
Abstract
Prevailing political and popular narratives often treat the issue of trans death as an inevitability and reduce complex stories of trans life to their endings. This paper investigates the transformative potential of creative forms of resistance—specifically a selection of Canadian poetry, personal essays, and comics—and how their artistic affordances engage with transfeminism as an approach to narratives of trans existence. Rooted in Canadian author Kai Cheng Thom’s reckoning with the shortcomings of trans-exclusionary feminist thought, and informed by Chinua Achebe’s conceptualization of re-storying, this article explores how I Hope We Choose Love and Falling Back in Love with Being Human by Kai Cheng Thom, Death Threat by Canadian creatives Vivek Shraya and Ness Lee, and comics from Assigned Male by trans activist and Canadian comic artist Sophie Labelle re-story “necessary” trans death to orient queer death spaces around a trans-for-trans (t4t) praxis of narrativization. Addressing the (inter)disciplinary possibilities of trans-inclusive feminism and comics studies, this article celebrates how these texts disavow and re-story the “Good” Trans Character, who dies to satisfy transmisogynistic ideologies, and theorizes the T4t Dead Trans Character, who dies to reclaim instances of trans death and recodify trans personhood as a site of hope, agency, and self-determination. In their re-storying, these texts recognize the transformative potential of trans existence and echo Thom in their urging of trans-inclusive feminism to renounce narratives of disposability and invest in the dignity of all human life.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.041 | 0.033 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".