Bibliographic record
Abstract
In light of the recent political attacks against trans and Black people worldwide, scholarship has increasingly taken an interest in Black trans critique. However, centering Black trans people in scholarship or activism may expose them to further violence, particularly when the focus is on the death of Black trans women. Shifting the focus away from Black trans death, this article examines how living activists in the present abolish interlinking white supremacy and transphobia. Through case studies of Black trans abolitionists Miss Major and CeCe McDonald, I argue that Black trans love and rage are central to living a revolutionary life that is constantly threatened by the Prison Industrial Complex and other white supremacist transphobic structures. Black trans rage is the fire to live life unbound. It is committed to the abolition of structures that imprison bodies according to gendered and racialized codes, often embracing violence to do so. Black trans rage works in tandem with Black trans love that heals the self and others from the injuries inflicted by white supremacy and transphobia so that one might continue raging. It cultivates community that will sustain the fight for freedom through different forms of love: self-love, agape, philia, storge, and eros. Each of these forms of love are tools for living well under oppression while remaining committed to abolition. Centering Black trans rage and love recognizes the affective resources that Black trans activists offer to revolutionary struggle that will destabilize the capitalist and colonial structures around us.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.030 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".