Bibliographic record
Abstract
<p class="first-line-indent-western">The past two decades have witnessed a rise in the number of autistic characters in YA literature, particularly autistic protagonists. In line with progress made by researchers and the self-advocacy from organizations and activists that have brought nuance in our understanding of autism, YA novels are offering more diverse representation of the spectrum, even if there is still room for improvement – for instance, the inclusion of more non-white autistic characters, non-binary people, and queer love stories. Autistic characters are now romantic leads in their own rights, and authors explore the way they experience sexual desire and sexuality through their neurodifference (e.g., the need to accommodate their heightened sensory sensitivities). Their desirability is also underlined through the loving eyes of their love interests, sometimes in the form of alternating narratives. All this counters the societal tendency to desexualize autistic people, and disabled people in general. This article explores how desire emerges from a mix of alterity and kinship in my primary corpus: all the love interests are neurotypical and they recognize the differences of the autistic characters while also sharing some of their special interests and feeling out of step with the world. It also considers how authors make use of autistic traits, such as sensory hypersensitivities and doing extensive research on topics of interest, to invite readers to take their time and be well informed when it comes to sexual intimacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".