Shipping Disability/Fanfiction: Disrupting Narratives of Fanfiction as Inclusive
Bibliographic record
Abstract
In this essay I will first give a definition of what fanfiction is within the wider online environment of online participatory cultures, as well examine whether inclusiveness holds up as a defining characteristic when disability is taken into consideration. I then examine how the development of fanfiction as a creative practice and of fanfiction-specific genres, have contributed to the queering of fanfiction spaces and practices Finally I argue that subversion and transgression are not best suited to conceptualize fanfiction, and that instead disruption can generate more apt interrogations. Specifically, disruption allows for us to explore fanfiction as both disrupting heteronormative narratives, gendered and fan behaviour expectations, and as disrupting the notion of the fan as a somehow homogenous construction. This affords disability the possibility of being disruptive in turn.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.041 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| 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".