The Goodness of Gilmore: Examining the Moralization of Reading in the Rory Gilmore-inspired Readathons of BookTube
Bibliographic record
Abstract
This paper seeks to find out how assumptions surrounding the moralization of reading appear in the BookTube videos of readers inspired by Rory Gilmore, the bibliophilic protagonist of the Warner Bros. comedy-drama series Gilmore Girls. In doing so, it aims to illuminate the ways in which the myth of the “moralization” of reading is used to disguise complex relations between class, privilege, and meritocracy, both within Gilmore Girls and without. Building from the scholarship of Harvey J. Graff, Deborah Brandt, Q. D. Leavis, and Janis Radway, I first analyze how literacy has come to be associated with goodness and what sort of literature is thought to be related to moral righteousness. Using this framework, I then analyze the appearance of reading in Gilmore Girls itself, concluding that beliefs surrounding the virtue of reading linger even in the fictional world of Stars Hollow. Finally, I analyze two Rory Gilmore-inspired readathon videos, arguing that by echoing Rory’s own perspectives on reading, BookTubers demonstrate that the belief that reading is an unequivocal moral good persists, even if readers themselves are not aware of it.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".