Power the Dark Lord Knows Not: The Fractal Serialities of Fanfiction
Bibliographic record
Abstract
Abstract This article examines contemporary fanfiction as a special type of engagement with popular serial narratives. It proposes the concept of fractal seriality as a lens through which to gauge the proliferation and popularization of fanfiction as a potentially fruitful strategy for critiquing fiction: part of fiction’s persuasiveness inheres in an author’s ability to consciously or unconsciously set the rules of the fictional world in ways that reinforce the author’s message and their vision of the real world, while fractal seriality allows fanfiction authors to change the focus and reorient stories in ways that will engage readers of the original series while refusing to circulate key aspects of the initial worldbuilding and moral values. E. J. Lomax’s boy with a scar builds on J. K. Rowling’s Harry Potter series not by continuing it chronologically but branching off from it in a series of “what-ifs” that broaden and deepen the wizarding world by focusing on characters, events, and circumstances that the original series has elided, oversimplified, or otherwise treated in ways that Lomax finds inadequate. VeroniqueClaire’s Volée, meanwhile, expands the action of three scenes from the Phantom of the Opera stage play into 25 chapters, realizing the potential for transformative justice already inherent, but unfulfilled, in the original.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".