Reading for Alternatives: The Experiences of Young Women Who Read Sexuality-Themed Fiction Online
Bibliographic record
Abstract
This paper examines the reading experiences and practices of young women who read sexualitythemed Young Adult Literature online. The findings of this study reveal that young women tend to seek out fiction in online spaces when they have reading interests or questions about sexuality that are not addressed in conventional Young Adult Literature. These readers reported that, from an early age, they sought out literature online that had explicit sexual content or focused on nonnormative topics such as LGBTQ relationships. They also identified comments sections as a significant aspect of their online reading experience which led to a sense of belonging to a reading community that is transparent, supportive and constructive about topics of sexuality.Cet article examine les expériences de lecture et les pratiques des jeunes femmes qui lisent en ligne de la littérature pour adultes à thème sexuel. Les résultats de cette étude révèlent que les jeunes femmes ont tendance à chercher de la fiction dans les espaces en ligne lorsque leurs intérêts de lecture ou leurs questions sur la sexualité ne sont pas abordés dans la littérature pour jeune adulte conventionnelle. Ces lectrices ont signalé que, dès leur plus jeune âge, elles ont cherché de la documentation en ligne ayant un contenu sexuel explicite ou axée sur des sujets non normatifs tels que les relations LGBTQ. Elles ont également identifié les sections de commentaires comme un aspect important de leur expérience de lecture en ligne, ce qui a conduit à un sentiment d'appartenance à une communauté de lecture qui est transparente, aidante et constructive sur les sujets de sexualité.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".