‘In a World of her Own…’: Re-presenting alienation and emotion in the lives and writings of women with autism
Bibliographic record
Abstract
The term autism derives from the Greek autos (meaning ‘self’)—it connotes separation, aloneness—and descriptions of those diagnosed with autistic spectrum disorders (ASDs) frequently suggest they are very much apart from the shared, experientially common space of others. The subjects of clinical literature are very often male children, perhaps unsurprising given the recognized need for early intervention and the fact that studies suggest four times as many boys receive an ASD diagnosis as girls. This understandable bias does, however, mean that a significant minority are often overlooked. This paper focuses on the experience of those girls and women who frequently struggle to obtain recognition and support for a predominantly male disorder. Drawing particularly on autobiographical accounts—including the narratives of Temple Grandin, Dawn Prince-Hughes and Donna Williams—the paper reveals a strongly felt need to communicate and thus connect their unusual spatial and emotional experience with others in a manner not typically associated with autism. It explores the complex challenges of ASD life-worlds, focusing in particular on the prevailing and powerful sense of alienation, and the ways in which ASD women use social and spatial strategies to cope with and contest the expectations and reactions of neuro-typical others.
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 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".